CN110648120B

CN110648120B - Online forest resource supervision method based on mobile internet

Info

Publication number: CN110648120B
Application number: CN201910937024.2A
Authority: CN
Inventors: 李谭宝; 彭松; 李崇贵; 王吉斌; 张仙爱; 于宝义; 李宏韬; 谭靖; 陈铮; 闵志强; 韩宇; 南科; 饶日光; 阮林佳; 张凯; 吴信社; 刘倩叶; 马振华; 王志宏; 刘友林
Original assignee: Beijing Aerospace Titan Technology Co ltd; Xi An Remote Sensing Science & Technology Of Information Co ltd; Northwest Survey Planning And Design Institute Of State Forestry And Grassland Administration
Current assignee: Beijing Aerospace Titan Technology Co ltd; Xi An Remote Sensing Science & Technology Of Information Co ltd; Northwest Survey Planning And Design Institute Of State Forestry And Grassland Administration
Priority date: 2019-09-29
Filing date: 2019-09-29
Publication date: 2022-12-27
Anticipated expiration: 2039-09-29
Also published as: CN110648120A

Abstract

The invention belongs to the technical field of forest resource supervision, and discloses an online forest resource supervision method based on mobile interconnection, which collects various types of data, processes the data and then puts the data into a warehouse and releases the data; a user fills registration information on a mobile terminal, and a manager authorizes the user to obtain corresponding authority according to the registration information; the mobile terminal manages users with different authorities and distributes tasks, and the users access or download the tasks according to the corresponding authorities; after field investigation and interior treatment are carried out according to the distributed tasks, the results are updated and reported on line and off line according to whether the results are involved in secret, and finally, the results are submitted, managed and other management services are carried out after summary examination; the beneficial effects of the invention are: in the method provided by the invention, the image data of the early and late stages of interpretation related to the confidentiality of the coordinate information is processed in batches to form standardized data, and then the decryption is carried out by utilizing a buffer technology, grid cutting and batch processing, so that the operation is more convenient and faster.

Description

Online forest resource supervision method based on mobile internet

Technical Field

The invention belongs to the technical field of forest resource supervision, and relates to an online forest resource supervision method based on mobile internet.

Background

Forest resources are distributed widely and have large areas, daily tasks of field investigation, monitoring and patrol are heavy, and equipment needs to be carried and purchased additionally depending on a GPS, a PDA and a tablet personal computer. The traditional field data investigation and acquisition system needs technicians to process and import data such as images and vector data in advance, the process is complicated, and the acquired information cannot be returned in real time. This all causes inconvenience to the field work under a hard condition.

In the aspect of internal management, the traditional forest resource supervision and management system cannot upload and synchronize data in real time, so that the efficiency of management departments at all levels of forestry in the working links such as task allocation, data updating, editing and processing, progress management and control is low, and the real-time supervision is lacked in the processes of quality inspection, data summarization, statistical reporting and the like. In addition, because the equipment conditions are limited, potential safety hazards easily exist in the working links related to issuing, processing, submitting and the like of confidential information.

At present, many systems are developed based on public cloud servers, and data related to government departments and needing confidentiality and privacy have great potential safety hazards. The private cloud is small in vulnerable target, targeted in security prevention and more suitable for managing non-public service data of government departments.

Disclosure of Invention

The invention provides an online forest resource supervision method based on mobile internet, which is used for solving the problems of poor timeliness of forest resource supervision and management, low data transmission efficiency of field survey tasks and poor safety of data management and storage.

The invention is realized by the following technical scheme:

an informatization solution method for a forest resource supervision method comprises the following operations:

1) Collecting forest resource data including interpretation pattern spot vector data in a supervision range;

2) Carrying out normalization pretreatment on the interpretation pattern spot vector data to form base map data and establish a survey map layer; establishing a buffer range for the interpretation pattern spots in the base map data to generate mask pattern spots, and if the area of the mask pattern spots does not exceed a threshold value, releasing the mask pattern spots to the registered mobile terminal on line; if the area of the mask pattern spot exceeds the threshold value, the mask pattern spot is segmented and then is issued to the registered mobile terminal on line;

3) When the online release is carried out, if the registered user is a unit below the county level, the cloud server or a manager issues a task to the mask pattern spot within the supervision range, otherwise, the manager issues an independent task;

4) According to the issued task and the existing reference image, the investigator carries out field work investigation on line through the mobile terminal in the network environment to form investigation data and uploads the investigation data to the cloud server;

or after downloading the tasks offline, the investigator performs field investigation through the mobile terminal to form investigation data, performs online updating in a network environment through the mobile terminal, and uploads the investigation data to the cloud server;

5) The management personnel locally download the survey data uploaded to the cloud server; then performing internal processing in a safe environment: performing additional recording of secret-related factors, finishing of graphs and quality inspection before submitting survey data, and completing statistical analysis;

6) Summarizing and examining the survey data subjected to statistical analysis; if the survey data of the summary examination is not confidential, the survey data is summarized through a cloud server and then is reported on line; otherwise, after physical isolation, offline summarizing and reporting;

7) The online and offline updating and reporting of the survey data are both checked by a user managed by a survey unit and then submitted to a superior unit for checking and acceptance; during auditing and acceptance, the superior unit screens a sample for spot check on the cloud server according to the summarized examination content and judges whether the sample is qualified or not; if the data is not qualified, returning to the investigation unit and then auditing again by the management user, and if the data is qualified, submitting the investigation data successfully;

and the cloud server hands over suspected illegal graphic spots in the finally submitted successful data, and archives and processes the offline file and the online data after supervision and supervision.

Furthermore, the collected forest resource data comprises interpretation pattern spot vector data, earlier-stage image data, current-stage image data and administrative region boundary data;

carrying out data field standardization on collected interpretation pattern spot vector data to form survey data, and warehousing the survey data; for the collected early-stage image data or the current-stage image data, performing mask cutting processing after coordinate system registration to form early-stage investigation reference image data and current-stage investigation reference image data, performing data grading slicing on the early-stage investigation reference image data and the current-stage investigation reference image data, and then issuing;

the early-stage investigation reference image data and the current-stage investigation reference image data also comprise buffer image spot data formed by buffering the interpretation image spot data for 50 meters, and the mask cutting processing is carried out on the buffer image spot data;

the early-stage survey reference image data and the current-stage reference image data are terrain-free data of regions in a non-military confidential area and with the area smaller than 6 square kilometers.

Further, the registered users are investigators who individually register through the mobile terminal or register in batch through the cloud server;

when the mobile terminal is independently registered, the investigator completes the registration by providing basic information including name, mobile phone number, unit and role; the mobile terminal configures organization, system, role and working range according to the filled basic information; if the registration information of the user is judged to be the blacklist user through the mobile terminal, registration failure is displayed, otherwise, the registration is successfully activated by the user after the audit of superior management personnel.

Furthermore, after the tasks are issued, managers manage and distribute the tasks through the cloud server, and mark the unallocated tasks on a map through the color of the map spots;

for unallocated tasks, managers allocate task patches to users through map framing or through a pattern attribute screening mode; each user acquires the task pattern through a data interface and synchronizes the acquired task pattern to the mobile terminal;

if the tasks are not distributed properly, the managers redistribute the tasks through resetting the tasks; before the task is reset, information confirmation is carried out on the information of the management personnel; the approved task is not allowed to perform the operation of resetting the task.

Further, the field survey comprises the following steps:

s1: each user acquires roles and a working range according to the registered and granted permissions;

s2: the mobile terminal downloads the distributed tasks according to the account authority of the login user;

s3: the mobile terminal acquires survey pattern spots, front and back stage images and reference stage image data according to the authority and the working range;

s4: the investigator arrives at the appointed position through navigation and position service according to the acquired data;

s5: after the specified position is reached, the investigator obtains the interpretation pattern spot through the existing authority;

s6: carrying out field investigation according to the acquired interpretation pattern spots and storing the investigation pattern spots into the mobile terminal; the investigator also edits and modifies the graph of the information acquired in the on-site investigation and synchronously uploads the graph to the cloud server;

s6: after the field investigation is completed, the investigator exports the data stored in the mobile terminal.

Further, the graphic editing comprises GPS point collection drawing, continuous point collection drawing, picture drawing, cross point drawing, coordinate point drawing, point shifting, point adding, point deleting and trimming, line segmentation, merging, edge sharing, surface segmentation, scattering, translation, deletion, cancellation and recovery;

the modification comprises the steps of comparing front and rear-stage images by rolling curtains, newly adding occupied pattern spots, editing attributes, performing superposition analysis and assignment, verifying a fine spot number, and carrying out on-site photos and video information;

wherein, the comparison of the front and back stage image rolling shutters is executed according to the following steps:

after clicking the roller shutter, a finger displays all layers on a screen, and each layer is used for displaying images in the front and rear stages; the user clicks and selects an early-stage image or a later-stage image in the 'selection rolling map list', a finger is slid to pull the screen after the image is selected, and a contrast boundary line appears in the range of the screen by the mobile terminal; the direction of the pulled screen is any direction, and the contrast change pattern spots are viewed from two sides of the contrast boundary line by pulling the screen at the position where the earlier and later image patterns are displayed and changed;

the newly added occupied pattern spot is executed according to the following steps: drawing and recording new occupied pattern spots in situ through each drawing mode, and uploading the new occupied pattern spots to a cloud server;

the property editing is performed according to the following steps: selecting a spot to enter an attribute interface to edit the spot attribute, editing and changing each attribute field by a user according to a corresponding attribute survey form, finishing editing, clicking and storing, and finishing editing the attribute;

the stack analysis assignment is performed according to the following steps: selecting two or more surface layer pattern spots with overlapped positions, performing superposition analysis on the counted field attributes, and generating a counted field result for comparing the counted layer with the position superposition layer;

the verification of the thin spot number is carried out according to the following steps that after the image spots are segmented, the mobile terminal verifies the thin spot number, the thin spot number inherits and judges the image spot number, and the number of the segmented parts of the original image spots is the number of the thin spots.

Further, the performing of the entry of the secret related factors and the trimming of the graph includes: the attribute factor of the data exported by the mobile terminal after field investigation is perfected through geographic information, and the graphic data is corrected and perfected;

the quality inspection before the submission of the survey data comprises the following steps: selecting a quality inspection scheme comprising logic quality inspection and spatial topology inspection, and exporting error information of the quality inspection after the cloud server finishes the quality inspection according to the quality inspection scheme;

carrying out statistical verification on error information exported after the quality inspection is finished; the statistic verification comprises data statistics and data updating; the data statistics is to classify, count and summarize the data passing the data quality inspection according to categories;

the data update is as follows: updating the interpretation pattern spot data processed by the internal work into a cloud server; the cloud server stores the data in a warehouse and updates the corresponding data, and only the latest corrected data content is displayed; the original data is put into a historical database for storage, and the historical database is used for storing the data content which is modified by a user through multiple surveys.

Further, the step of the aggregate review is:

the cloud server firstly detects the current survey shift state information, and if the current survey shift state information is accepted and audited, the information cannot be submitted; filtering sensitive attribute factors by the investigation data meeting the conditions, uploading the investigated multimedia files to a file service module, and associating the investigated multimedia files with the current investigation class;

the management user receives the information of the data to be audited and then audits the information; transversely comparing the interpretation data with the survey data during auditing; auditing the return of the data which do not meet the requirements of the user, and filling a return opinion; the investigator modifies and submits the investigation data again; the cloud server feeds back the audit state of the audit investigation data to the mobile terminal of the investigation user;

the checking of the superior unit comprises the following steps: the method comprises the following steps that a superior management user enters a cloud server and receives a message to be checked to remind, the cloud server displays checking data information according to a checking state, and the superior management user checks submitted data through map checking or small shift list checking;

comparing the interpretation shift data with the survey data during auditing, detecting the pattern spots with larger area change difference and prompting; by combining the condition of domestic re-check, the auditors select to carry out spot check on the data;

the superior management user performs return processing on the data which do not meet the requirements and fills in return comments; auditing the returned data to the last node of the submitted data, and if the returned data is returned to the investigator, modifying and submitting the returned opinions of the investigation data according to the superior management user;

the spot check comprises the following steps:

when a superior unit audits, performing spot check processing on data submitted by a subordinate investigation user, and assigning the spot checked spot to a designated user for field verification by a superior management user through checking a spot or listing a spot; the verification personnel carry out field operation verification on the spot check class by holding the mobile terminal by hand and report the investigation result through the mobile terminal;

the spot check comprises a full check, a designated spot check and a spot check; the full-check is to copy all graphs and factors related to the survey data to a spot check layer; the appointed spot check is carried out by selecting any class or any class in the region; the spot check is performed by randomly extracting a small class according to ABS rules; and after the spot check is finished, submitting the spot check data of field work verification to a cloud server through the mobile terminal.

Further, the handover of the suspected illegal spot is performed according to the following steps:

s1: handing over suspected illegal pattern spots: transferring the rechecked forest supervision pattern spots to each specialist, and marking illegal pattern spots;

s2: supervising and supervising illegal pattern spots: according to the rechecking result, distributing the investigation task of the illegal graphic spot to a specific user, and checking the execution condition of a specific main body;

s3: managing the progress of supervision and supervision: the management personnel supervise the forest to supervise the working progress, supervise the investigation of the illegal pattern spots to urge each province city to complete on time and report the self-checking and rectification results;

s4: filing the files for supervising and supervising: establishing a forest supervising and illegal database, registering illegal problem clues into a warehouse, and checking the sales numbers one by one.

Furthermore, the method also comprises the step of carrying out management service on the archived offline files and online data; the management service comprises notification announcement, progress management, comprehensive display analysis, work condition supervision, video connection and unmanned aerial vehicle video processing;

the middle notification announcement comprises the following steps: the administrator selects all notifications or issues notification announcements according to a specific organization, the issued notification announcements comprise content and attachment information, other users look up the notification announcements after logging in the system and download attachments in the notification announcements;

the mobile terminal displays progress management on the cloud server through a chart, wherein the progress management comprises investigation progress, examination and approval progress, verification progress and progress early warning analysis;

the comprehensive display analysis comprises the following steps: the mobile terminal analyzes and arranges key index information from the service system data, displays the key index information on the cloud server through a report or a statistical chart, and performs ranking display on each level of supervision progress, self-checking results and interpretation area difference indexes; the report and the statistical chart comprise the issued suspected small shifts, the actual suspected small shifts, the county reported small shifts, the un-checked small shifts in the provincial examined monitoring area, the checked small shifts in the monitoring area and the current summarized small shifts;

the work condition supervision is as follows: according to online personnel list information provided by an organization, a room of a video conference is created through a connecting function, and other users are invited to join the room of the video conference;

the video conference comprises the following steps: the management user manually creates a video conference room and invites other users to join in the video conference room; the video conference is used for sharing data documents, application programs and audio and video files;

the unmanned aerial vehicle video is: uploading a video shot by an unmanned aerial vehicle to a mobile terminal to realize real-time picture information display of the video; meanwhile, the data of the unmanned aerial vehicle is combined with the geographic information, and the current position and route information of the unmanned aerial vehicle are displayed.

Compared with the prior art, the invention has the beneficial effects that:

the method provided by the invention provides various online data through the mobile terminal, including the front-stage interpretation images, the back-stage interpretation pattern spots and the annual forest land change data, and also pushes the background interpretation pattern spots in real time according to the period, thereby facilitating the timely and flexible monitoring and management of forest resources by users. And according to the service hierarchical management requirements, a permission and authorization system is set, so that the role definition is enhanced, and the scope is more definite. The information such as task allocation, work progress, quality inspection, statistical report forms and the like is displayed on line in real time, so that the operation is more convenient; in a word, the user can realize the online process service of the forest supervision business through the mobile terminal;

in the method provided by the invention, for the image data of the interpretation of the early and late stages related to the confidentiality of the coordinate information, standardized data is formed by batch processing, and then decryption is carried out by using a buffer technology, a grid cutting technology and a batch processing technology, so that the data is published on line by relying on a cloud computing and tile grading technology, and the operation is more convenient and faster;

the user realizes the functions of navigation positioning, space inquiry, track acquisition, coordinate correction, coordinate photo acquisition, positioning editing and the like through the mobile terminal; the management end user can acquire and display the position and the state of field workers in real time, and performs task allocation and conference live broadcast based on the position; instant communication functions such as video connection, unmanned aerial vehicle remote connection, information sending and the like can be realized between the mobile terminals or between the mobile terminal and the management terminal; the field survey is more convenient, and the obtained data can be transmitted back in real time.

Drawings

FIG. 1 is a flow chart of the present invention;

FIG. 2 is a block diagram of a data preparation process of the present invention;

FIG. 3 is a block diagram of the registration and authorization process of the present invention;

FIG. 4 is a block diagram of a task delivery process of the present invention;

FIG. 5 is a block diagram of the field survey process of the present invention;

FIG. 6 is a block diagram of a process flow for industry in accordance with the present invention;

FIG. 7 is a block diagram of an aggregate review process of the present invention;

FIG. 8 is a block diagram of a handoff supervision flow of the present invention;

FIG. 9 is a block diagram of the management service flow of the present invention.

Detailed Description

The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

Referring to fig. 1-8, an informatization solution method for a forest resource supervision method includes the following operations:

2) Carrying out normalized preprocessing on the interpretation pattern spot vector data to form base map data and establish a survey map layer; establishing a buffer range for the interpretation pattern spots in the base map data to generate mask pattern spots, and if the area of the mask pattern spots does not exceed a threshold value, releasing the mask pattern spots to the registered mobile terminal on line; if the area of the mask pattern spot exceeds the threshold value, the mask pattern spot is segmented and then is issued to the registered mobile terminal on line;

4) According to the issued tasks and the existing reference images, the investigators perform field investigation on line through the mobile terminal in a network environment to form investigation data and upload the investigation data to the cloud server;

5) The management personnel locally download the survey data uploaded to the cloud server; then performing internal processing in a safe environment: performing quality inspection before the completion of the supplement and recording of the secret-related factors, the trimming of the graph and the submission of survey data, and completing statistical analysis;

6) Summarizing and examining the survey data subjected to statistical analysis; if the survey data to be summarized and examined are not confidential, the survey data are summarized through a cloud server and then reported on line; otherwise, after physical isolation, the data are collected off line and reported;

7) The on-line and off-line survey data updating reports are both checked by the management user of the survey unit and then submitted to the higher-level unit for checking and acceptance; during auditing and acceptance, the superior unit screens out a sample for spot check on the cloud server according to the summarized audit content and judges whether the sample is qualified or not; if the data is not qualified, returning to the investigation unit and then auditing again by the management user, and if the data is qualified, submitting the investigation data successfully;

and the cloud server hands over suspected illegal graphic spots in the finally submitted successful data, and archives and processes the offline files and the online data after supervision and supervision.

The collected forest resource data comprises interpretation pattern spot vector data, early-stage image data, local-stage image data and administrative division boundary data;

the early-stage survey reference image data and the current-stage reference image data are terrain-free data in a non-military confidential area and an area smaller than 6 square kilometers.

The registered user is that the investigator registers independently through a mobile terminal or registers in batch through a cloud server;

After the tasks are issued, management personnel manage and distribute the tasks through the cloud server, and mark the unallocated tasks on the map through the color of the pattern spots;

for unallocated tasks, managers allocate task patches to users through map framing or through a pattern attribute screening mode; each user acquires a task pattern spot through a data interface and synchronizes the acquired task pattern spot to the mobile terminal;

if the tasks are not distributed properly, the managers redistribute the tasks through resetting the tasks; information confirmation is carried out on the information of management personnel before the task is reset; the approved task is not allowed to perform the operation of resetting the task.

The field survey comprises the following steps:

s1: each user acquires roles and a working range according to the registered and granted authority;

s4: the investigator arrives at the designated position through navigation and position service according to the acquired data;

s5: after reaching the appointed position, the investigator obtains the interpretation pattern spot through the existing authority;

s6: carrying out field investigation according to the obtained interpretation pattern spots and storing the investigation pattern spots into the mobile terminal; the investigator also edits and modifies the graph of the information acquired in the on-site investigation and synchronously uploads the graph to the cloud server;

s6: and after the field survey is finished, the surveyor exports the data stored in the mobile terminal.

the modification comprises the steps of comparing front and rear-stage images by rolling screens, newly adding occupied pattern spots, editing attributes, performing superposition analysis and assignment, verifying the number of thin spots, and carrying out on-site photos and video information;

wherein, the front-back period image rolling shutter comparison is executed according to the following steps:

clicking the 'rolling screen' by a finger to display all layers on the screen, wherein each layer is used for displaying front and rear stage images; the user clicks and selects an early-stage image or a later-stage image in the 'selection rolling map list', a finger is slid to pull the screen after the image is selected, and a contrast boundary line appears in the range of the screen by the mobile terminal; the direction of the screen is pulled to be any direction, and the contrast change pattern spots are checked from two sides of the contrast boundary line by pulling the screen at the position where the earlier and later image patterns are displayed to change;

the overlay analysis assignment is performed according to the following steps: selecting two or more surface layer pattern spots with overlapped positions, performing superposition analysis on the counted field attributes, and generating a statistical field result for comparing the statistical layer with the position superposition layer;

The supplementary recording of the secret related factors and the trimming of the graph are carried out as follows: the attribute factor of the data exported by the mobile terminal after field investigation is perfected through geographic information, and the graphic data is corrected and perfected;

the quality inspection before the submission of the survey data is as follows: selecting a quality inspection scheme comprising logic quality inspection and spatial topology inspection, and exporting error information of the quality inspection after the cloud server finishes the quality inspection according to the quality inspection scheme;

the data update is as follows: updating the interpretation pattern spot data processed by the internal work into a cloud server; the cloud server stores the data in a warehouse and updates the corresponding data, and only the latest corrected data content is displayed; original data is brought into a historical database for storage, and the historical database is used for storing data contents which are investigated and corrected by a user for many times.

The steps of summarizing and examining are as follows:

the management user audits after receiving the information of the data to be audited; transversely comparing the interpretation data with the survey data during auditing; auditing the return of the data which do not meet the requirements of the user, and filling the return opinions; the investigator modifies and submits the investigation data again; the cloud server feeds back the audit state of the audit investigation data to the mobile terminal of the investigation user;

the method comprises the following steps of: the superior management user enters the cloud server and receives the prompt of the message to be audited, the cloud server displays audit data information according to the audit state, and the superior management user audits submitted data through map check or small class list check;

the spot check method comprises the following steps:

when a superior unit audits, performing spot check processing on data submitted by a subordinate investigation user, and assigning the spot checked spot to a designated user for field verification by a superior management user through checking a spot or listing a spot; the verification personnel carry out field operation verification on the spot check class by holding the mobile terminal, and report the investigation result through the mobile terminal;

spot checks include full check, designated spot check and spot check; the full-check is to copy all the graphs and factors related to the survey data to a spot check layer; the appointed spot check is to select any one class or any one class in the region to carry out appointed spot check; the spot check is to randomly draw a small class for spot check according to ABS rules; and after the spot check is finished, submitting the spot check data of field work verification to a cloud server through the mobile terminal.

The handover of the suspected illegal pattern spot is executed according to the following steps:

s3: managing the progress of supervision and supervision: a manager supervises and manages the forest to check the working progress, supervises and urges each provincial city to complete the illegal graphic spot on time, and reports self-checking and rectification results;

The method also comprises the step of carrying out management service on the archived offline files and online data; the management service comprises notification announcement, progress management, comprehensive display analysis, work condition supervision, video connection and unmanned aerial vehicle video processing;

the middle notification announcement is: the administrator selects all notifications or issues notification announcements according to a specific organization, the issued notification announcements comprise content and attachment information, other users look up the notification announcements after logging in the system and download attachments in the notification announcements;

the comprehensive display analysis comprises the following steps: the mobile terminal analyzes and arranges key index information from the service system data, displays the key index information on the cloud server through a report or a statistical chart, and performs ranking display aiming at each level of supervision progress, self-check result and interpretation area difference index; the reporting and statistical chart comprises the issued suspected small shifts, the actual suspected small shifts, the county-level reported small shifts, the number of unchecked small shifts in the provincial-level checked monitoring area, the number of checked small shifts in the monitoring area and the number of currently summarized small shifts;

the work scene supervision is as follows: according to online personnel list information provided by an organization, a room of a video conference is created through a connecting function, and other users are invited to join the room of the video conference;

the video of the unmanned aerial vehicle is as follows: uploading a video shot by an unmanned aerial vehicle to a mobile terminal to realize real-time picture information display of the video; meanwhile, the data of the unmanned aerial vehicle is combined with the geographic information, and the current position and route information of the unmanned aerial vehicle are displayed.

Data preparation is performed according to the following steps:

1. data collection: collecting interpretation pattern spot vector data, earlier-stage image data, current-stage image data, administrative division boundary data and the like;

2. data processing

(1) Standardizing the interpretation pattern spot data according to fields to form survey data;

(2) Judging the pattern spot data, and buffering for 50 meters to form buffered pattern spot data;

(3) Performing coordinate system registration on the image data in the previous period and the current period, and uniformly registering the image data into CGCS2000;

(4) Performing overlapped mask cutting on the buffered image spot data and the image data to form a reference early-stage image and a reference current-stage image of the survey; the standard of the reference image is a non-military confidential area, less than 6 square kilometers and no terrain data;

3. data warehousing and publishing: and warehousing the interpretation pattern spots and the survey pattern spots, grading and slicing the reference images in the early stage and the current stage, and issuing the reference images into WMTS service.

Registration and authorization is performed according to the following steps:

1. the user can register the user through the mobile terminal and the PC terminal and fill in registration information;

2. the user authorization control carries out hierarchical authorization control through the organization, the system, the role and the working range in which the user authorization control is positioned; users in the same role in the same system can have different data view authorities;

3. in order to prevent malicious registration, the cloud server adopts a blacklist system to perform filtering control;

4. after receiving the user registration information prompt, the superior management user can check and activate the user in time through the mobile terminal or the PC terminal.

The task issuing is executed according to the following steps:

1. a manager grasps a task distribution condition through the cloud server task statistical information, and distinguishes task distribution states through the colors of the image spots on the map;

2. for unallocated tasks, the manager allocates the tasks to corresponding investigators by framing the task spots on the map or by screening the attributes of the spots; the method comprises the following steps that a surveyor obtains a task pattern spot through a data interface and synchronizes to a mobile terminal;

3. the image spots of the distributed tasks can be redistributed through the reset tasks; in order to prevent misoperation, the reset task requires verification of the identity information of the current personnel for confirmation; the reset operation is not allowed to be carried out on the tasks which are approved;

the field survey is carried out according to the following steps

1. Task downloading

After a user registers a login account, a background distributed task is obtained through a server: basic data such as the pattern spots, the interpretation pattern spots, the front-back period images and the like are investigated, and the latest data of the corresponding authority on the server can be obtained after each account is successfully logged in; the mobile terminal downloads data and graphs from the server, the downloaded data is in a json character string format, and the downloaded graph is in a Wkt format;

the initial data downloaded to the mobile terminal by the user through the server is CGCS2000 longitude and latitude data, when a map scale is more than or equal to 1;

2. verification of rights and scope of operation

A background manager can distribute different authorities according to the identity of a user, the user inputs an account and a password to click login after taking the account, and the system displays all working ranges within the authorities according to the authorities of the login account so as to achieve the consistency of the authorities and the working ranges;

inputting a management authority account, clicking to log in, popping up a service selection interface, namely forest and grass key project monitoring, forest supervision and natural protection, and clicking to enter the service interface by a user as required; inputting a survey staff account password, clicking and logging in, and enabling the system to enter a service interface with corresponding authority;

the system is composed of a plurality of subsystems, and different subsystems download and acquire different data from a server; the subsystem downloads and acquires corresponding data stored on the server from the server by taking county as a unit after a user logs in an account;

the loading of the survey image spot, the early and late stage images and the reference stage image is carried out according to the following steps:

the acquisition of the survey pattern spot comprises the following operations:

the system loads the survey map layer on a vector map layer management module, and a user logs in an account to obtain the survey map layer which contains all survey maps; the method comprises the following steps that users with different authorities acquire different survey patterns, the higher the authority is, the more survey patterns can be acquired, and an administrator or a user with high authority can click 'data download' to download different survey patterns in different regions in the jurisdiction range; a user can add, export and remove the layers in the vector layer module as required, and can also render the layers;

the acquisition of the front and the rear images comprises the following operations:

the system embeds the front-stage and back-stage images in a network map management module, a user logs in an account, the system loads the front-stage and back-stage images with corresponding authorities according to the authority of the user account, clicks layer management-network map management, opens the visibility of the front-stage and back-stage images, and can check the front-stage and back-stage images acquired with corresponding authorities on a survey interface;

loading the reference image comprises the following operations:

in the grid base map management module, a user can add a reference image according to actual needs, click addition and add a grid base map conforming to a coordinate system of an investigation project into a system to finish loading the reference image;

the navigation and location application is executed according to the following steps:

wherein the navigation positioning comprises the following steps

The system can call the high-resolution navigation and the Baidu navigation, when the distance from a target place is far, a user calls the high-resolution map or the Baidu map navigation by using the system, when the navigation is close to a survey spot, the system calls the self-contained image navigation, and the system provides 5 built-in image navigation modes which are respectively as follows: graphic navigation, coordinate navigation, point-taking navigation, file navigation and photo navigation. Determining an image navigation mode, selecting a target file, and navigating a user to a target point through the coordinates of the file by the system according to the selected target file;

when the GPS is used for positioning, a user clicks the position, the system determines the real-time position of the user according to satellite positioning, and real-time position information can be uploaded to a server when network connection exists;

the steps of obtaining and uploading the user position information comprise the following operations:

the mobile terminal user transmits the position information to the server in real time through satellite positioning, and a background manager acquires and checks the position information of the mobile terminal user in real time through the server;

the position deviation correction comprises the following operations:

a user positions the current position through a satellite or looks up a large-range map by using a grid base map and an online map, clicks the 'correction deviation' of a position deviation map layer such as the 'grid base map' or the 'network map' when determining and comparing that the current position has deviation from a target position, inputs the horizontal and vertical deviation amount or selects more than 1 reference point, and corrects the actual position.

Acquiring the interpretation pattern spot comprises the following operations:

the method comprises the following steps that users with different authorities download and obtain interpretation pattern spots from a server after logging in an account, the more interpretation pattern spots can be downloaded and obtained by users with higher authorities, management personnel can selectively download and obtain the interpretation pattern spots, and investigators can only download the interpretation pattern spots within the authorities of the investigators;

the in-situ survey includes the following operations:

the user obtains the pattern spot according to the authority and starts the on-site survey operation by using the corrected position point

The graph is edited as follows: setting survey pattern spots to make the map layer of the survey pattern spots editable, and providing the following modes for drawing and modifying the graph by the system

The GPS sampling point is plotted as follows: after the GPS is positioned, clicking 'drawing', moving the position, clicking 'GPS sampling point' to draw a node, sequentially drawing the point, moving the system to draw the node on a screen through the position movement of a user, clicking 'finishing', closing the first point and the last point by the system, and finishing the drawing of the graph;

the continuous sampling point is plotted as follows: the drawing mode is the same as that of GPS sampling, and the difference is that the continuous sampling can be performed in a set sampling mode and sampling rate;

the picture drawing is as follows: clicking 'drawing', clicking 'picture', generating a point by the system according to the clicked position once on the screen, drawing the point in sequence, forming a surface by three points or more, and clicking 'finishing' to close the first and last points to generate a graph;

clicking the drawing tool to make the cross hair coincide with the boundary point to be drawn, clicking the cross drawing point, drawing a node at the position, drawing a plurality of points in sequence, and clicking the closed first and last points to generate a graph;

the coordinate plotting point is drawn by clicking the coordinate plotting point and manually inputting the point coordinate or importing the coordinate. Manually inputting coordinates, inputting coordinate points, and also inputting azimuth angles and distances between the coordinate points and the previous node, and generating nodes by the system according to the input coordinates to draw a graph; importing coordinates, importing a coordinate file prepared in the early stage, generating a plurality of nodes by the system according to the file coordinates, and clicking the first and last points of the 'finished' coordinate file to close to generate a graph;

the point shifting operation is as follows: selecting a graph, clicking 'shift points', dragging any node of the graph, finishing 'points', and finishing the editing of the graph;

the point increasing operation comprises the following steps: selecting a graph, clicking 'adding points', and adding a node on any edge of the graph by the system after the point is added on the edge;

the point deletion operation is as follows: selecting a graph, clicking 'deleting points', clicking any node on the graph, and deleting the points by the system;

the trimming operation is as follows: selecting a graph, clicking 'trimming', drawing a trimming range on a screen in any drawing mode, clicking 'finishing', and finishing the modification of the graph by a system;

the line segmentation operation is as follows: selecting a graph, clicking 'line segmentation', drawing two or more points passing through two sides in the graph on a screen, finishing 'the points', and systematically segmenting the graph;

the merging operation is as follows: selecting two or more than two graphs, clicking 'merging', popping up an attribute selection prompt by the system, determining an attribute selection point, and finishing the merging of the selected graphs by the system;

the edge sharing operation comprises the following steps: selecting two or more than two graphs, point 'common edge', drawing the graph in the selected graph in any mode, point 'finishing', and taking the edge of the newly drawn graph as the common edge of the selected graph;

the surface division operation is: selecting two or more than two graphs with overlapped parts, clicking 'surface segmentation', selecting a cutting graph, determining points, and cutting the rest graphs and the overlapped parts of the selected graphs;

the scattering operation is as follows: selecting a graph synthesized by two or more graphs without overlapped parts, clicking to break up, and breaking up the graph into independent graphs by the system;

the translation operation is as follows: clicking a selected graph, clicking ' translation ', dragging a circle to a target place, clicking a hook for ending graph movement ', and finishing the translation of the graph;

the deleting operation is: clicking a selection graph, clicking 'delete', 'confirm', and deleting the graph; cancel, cancel delete;

the undo operation is: clicking 'undo', undoing the previous operation, then clicking 'undo', and continuing the undoing operation;

the recovery operation is as follows: clicking recovery to recover the cancelled operation, then clicking recovery to continue to recover the cancelled operation;

the front and back image rolling contrast is as follows: clicking a 'rolling screen', wherein all visible image layers appear on the screen, when front and back images are visible, clicking in a 'selection rolling screen map list' to select a front-stage image or a back-stage image, pulling the screen after selecting the image, wherein a red line appears in the range of the screen when pulling the screen, the red line is a contrast boundary line, the screen can be pulled from all directions, and the front-stage and back-stage images can be used for viewing contrast change pattern spots from two sides of the red line by pulling the screen at a changed place, so that rolling screen contrast of the front-stage and back-stage images is realized;

the newly added occupied pattern spots are: drawing and recording new occupied pattern spots in situ by the drawing mode, uploading the new occupied pattern spots to a server, and completing the new occupation pattern spots;

the property is edited as: selecting a spot to enter an attribute interface to edit the spot attribute, editing and changing each attribute field by a user according to a corresponding attribute survey form, finishing editing, clicking and storing, and finishing editing the attribute;

the overlay analysis assigns the following values: selecting two or more than two graphic spots with position superposition surface layers, clicking 'tool' -more tools '-superposition analysis', selecting a statistical layer and a statistical field, clicking 'execution statistics', and analyzing and comparing statistical field results of the statistical layer and the position superposition layer by a system; according to actual requirements, the comprehensive superposition analysis comparison of different fields of each layer with the position superposition layers can be realized in the superposition analysis toolbar;

checking the number of the fine spots, namely checking the number of the fine spots by a system after the image spots are segmented, wherein the number of the fine spots inherits the number of the judgment image spots, and the number of the segmented parts of the original image spots is the number of the fine spots;

the in-place photo and video information comprises that a user investigates and draws a spot in the in-place, clicks 'attribute' -to take a picture when filling in the attribute, and users with different authorities can download different amounts of multimedia information such as photos, videos, sound recordings, manual drawing and the like on a server; clicking 'taking a picture', 'recording a video', 'recording an audio' and 'drawing a sketch' to add multimedia information to the attribute of the pattern spot; photos can be imported, deleted and exported in the multimedia interface;

the application and processing of the terminal data file are executed according to the following steps:

the mobile terminal data file export comprises the following steps:

there are several ways to export a terminal data file: clicking ' layer management ' -vector diagram layer management ', selecting a layer to be exported, clicking a ' export ' icon, naming a export layer, and exporting the selected layer to a fixed path in an shp format by a system; clicking 'query statistics' to select a layer, a field and a query condition, clicking to query and find out a data file to be searched, selecting a file format (an excel file, an f2x layer, a shp file and a gpx file) to name a file, and exporting the selected data file to a fixed directory by a system; opening file management on the mobile terminal, and exporting required data files in a 'forest and grass watching' folder;

the data import update comprises the following operations:

the exported data file is imported and updated to the mobile terminal after being processed by the internal operation;

the online synchronous uploading of the data comprises the following operations:

after the work of drawing the pattern spots, collecting information, filling and changing attributes and the like is completed, clicking work management-data synchronization, still uploading attribute data in a json character string format and uploading graphic data in a Wkt format to a server by the mobile terminal, and using the uploaded data by a background manager to perform summarizing and examining.

The interior processing is performed according to the following steps:

1. the data file of the field investigation is derived from the mobile terminal, and the local geographic information software is used for perfecting the attribute factor and correcting and perfecting the graphic data; the attribute editing supports data format verification, illegal format check and prompt; the sequence numbers are arranged in sequence through data number arrangement, and the sequence numbers are guaranteed to be unique.

2. And (3) data quality inspection: the data quality inspection method comprises the steps that a quality inspection scheme is selected firstly, the quality inspection scheme comprises a plurality of quality inspection rules and supports the user-defined quality inspection rule, and data are subjected to quality inspection according to the quality inspection rules in the quality inspection scheme; and the survey data is subjected to logical quality inspection and spatial topology inspection according to data quality inspection, and detailed information of quality inspection errors can be checked and exported.

3. And (3) data statistics: the data passing the data quality inspection is classified, counted and summarized according to categories, so that a user can further master the verification condition of the local authentication;

4. and (3) updating data: synchronously updating the spot data subjected to the interior processing into the cloud server by introducing an updating function; and the cloud server stores the data in a warehouse and updates the corresponding data, the original data is brought into a historical database for storage, and the cloud server only displays the latest corrected data content. The historical database stores data contents which are investigated and corrected by the user for many times, and the user can conveniently compare and check the data contents

The collective review is performed according to the following steps:

1. auditing and reporting by survey units

Data investigated by investigators are submitted to a cloud server through a data synchronization function, the cloud server firstly detects the current state information of the investigation class, and if the current state information is accepted and audited, the data cannot be submitted; and filtering sensitive attribute factors by the survey data meeting the conditions, uploading the surveyed multimedia files (pictures, videos and the like) to a file server, and associating the surveyed multimedia files with the current survey class.

The management user receives the information of the data to be audited on the cloud server interface, and the data to be audited timely reminds the management user of auditing; the interpretation data and the survey data can be transversely compared during auditing; the attributes and the pattern spot changes among the data can be visually seen, and the judgment of an audit user is facilitated; the auditing user can audit the submitted data, return the data which does not meet the requirements and fill in return comments. The investigator can modify and submit the investigation data again.

The data which passes the audit can feed back the audit state of the data to the terminal of the investigation user. Meanwhile, the data result submission of the survey unit is divided into an online submission mode (without sensitive attribute factors) and an offline submission mode of data files and reports.

2. Higher level unit audit

The superior management user enters the system and receives the prompt of the message to be audited, displays the audit data information according to the audit state, and audits the submitted data through map check or small class list check.

The data auditing interface system compares the interpretation shift data with the survey data, detects the pattern spots with larger area change difference and prompts the pattern spots, and auditors can choose to carry out spot check on the data by combining the condition of homework review.

The unsatisfactory data may be returned and a return comment may be filled in. And auditing returns to the last node of the data submission, and if returning to the investigator, the investigator can modify and submit the data for review again.

3. Spot check

When the superior unit audits, the superior unit can carry out spot check on the data submitted by the subordinate unit, check out a pattern spot or list a small class, assign the small class to be checked out to a certain user of field verification, similar to task allocation, carry out field verification on the small class to be checked out by a verifier with the mobile terminal, and report the result of the investigation through the mobile terminal. Spot checks are divided into three cases:

(1) And (4) full inspection: copying graphs and factors related to all survey data to a spot survey layer;

(2) Specifying: selecting a certain class or a class in an area to carry out designated spot check;

(3): randomly extracting a small class for spot check according to ABS rules; after the spot check is completed, the verification personnel submits the spot check data of field work verification to the system.

The county level unit quantity extracted by each province is not less than 10% of the county level unit quantity of the whole province, and not less than 10 patches with large area difference between the self-checking result and the interpretation condition are extracted by each county. And simultaneously extracting 1-3 county-level units which do not report self-checking results and report zero illegal projects from each province, and performing spot check on 8 typical change patterns in each county.

When the spot check work is carried out, the following indexes are specifically considered as references:

1) The self-checking result indexes are not reported: displaying the county level unit information and the number of the unreported self-checking results;

2) Reporting indexes of 'zero' illegal items: displaying and reporting county level unit information and quantity undoubtedly similar to the image spots;

3) Difference index between self-check result and interpretation area: ABS (issued suspected small shift area-reported small shift area)/issued suspected small shift area, and the results are arranged in descending order according to the formula calculation and used as a spot check reference. And the user synchronizes the suspected picture shift of the spot check to the spot check picture layer.

The handover supervision is performed according to the following steps:

1. and transfer of illegal patches: and transferring the rechecked forest supervision pattern spots to each specialist (the work of the direct courtyard is finished).

2. Supervising and supervising: and according to the self-checking result, the construction and execution condition check of the target responsibility system for protecting and developing the forest resources is carried out in a targeted manner.

3. And (3) progress management: and supervising the forest to supervise the work progress, supervising and urging each province city to finish on time, and reporting self-checking and rectification results.

4. Filing the file: establishing a forest supervising and illegal database, registering illegal problem clues into a warehouse, and checking the sales numbers one by one.

The management service is executed according to the following steps:

1. notification announcement

The system administrator can select all notifications or publish the notification notifications according to a certain organization, the notification notifications comprise content and attachment information, other people can see detailed information of the notification notifications after logging in the system, and downloading of the attachments and online viewing of the attachments in conventional formats (pictures, videos, words, excels, pdfs and the like) are supported.

2. Progress management

The analysis content including the investigation progress, the examination and approval progress, the checking progress and the progress early warning is displayed in a chart mode in a combined mode, and management personnel at all levels can conveniently check the working progress of each business at any time.

3. Comprehensive display analysis

And analyzing and sorting out the key index information most concerned by the leader from the service system data, and visually displaying through a report and a statistical chart, so that the leader can conveniently browse and check the key index information, and a decision reference basis is provided for the leader. The method mainly comprises the steps of issuing suspected small shifts, actually reporting the suspected small shifts, reporting the small shifts at county level, reporting the number of the uninspected small shifts in a provincial-level audited monitoring area, reporting the number of the small shifts after the audited small shifts in the monitoring area, reporting the number of the currently summarized small shifts, and the like. Drilling analysis on administrative divisions and the like is realized in a mode of linkage of a graph, a table and a map. And ranking and displaying the county level, the provincial level, the expert level, the monitoring area level, the national summary level, the national supervision progress, the self-checking result and the interpretation area difference index.

4. Work station

The method realizes the display of the real-time position information of the online personnel of the mobile terminal personnel, provides online personnel list information according to an organization, creates a room of a video conference through a connecting function, and can invite other users to join in the video conference room.

5. Video conference

The management user can manually create a video conference room and invite other users to join; the method supports PPT, WORD, excel, PDF, TXT and other data documents, and simultaneously supports sharing of application programs and audio and video files to participants; the conference host and the participants can carry out public chat, private chat, character interaction and voice and video interaction; the management user has conference control authority, including the functions of muting the whole, conference password, camera control, microphone control, video recording and the like. The video conference supports access of cloud servers such as Windows, IOS, android and WeChat small programs.

6. Aerial live broadcast

The real-time picture information of the video shot by the unmanned aerial vehicle is displayed by the unmanned aerial vehicle, multi-terminal live broadcast and watching are supported, and meanwhile, the data of the unmanned aerial vehicle is combined with the geographic information cloud server to display the current position, air route and other information of the unmanned aerial vehicle. Unmanned aerial vehicle information of taking photo by plane combines together with the videoconference, the judgement of supplementary user to the site conditions.

Referring to fig. 1-8, when the method of the invention is used for forest resource supervision, the method is implemented according to the following steps:

(1) Data collection: collecting the interpretogram vector data of 2019-year interpretation of a certain province, the image data of the current and previous periods, the administrative division boundary vector data of cities, counties and forest administration offices subdivided into the whole province, and other data such as a data dictionary table.

(2) Data processing: on a cloud server, carrying out standardization preprocessing including coordinate system unification, graph topology inspection and attribute field integrity inspection on the image spot vector data of the introspection interpretation to form base map data, and establishing 50 standardized fields as investigation layers for basic data of later investigation. And establishing a mask pattern spot according to the interpretation pattern spot buffer of 50 meters, judging whether the area (including coincidence) of the pattern spot is more than 6 square kilometers, and performing mask cutting on the excessive divided processing batch. The mask clipping includes processes of data superposition, data clipping, data inspection after clipping, and the like, and aims to project a coordinate system I to a GCS2000 coordinate system before processing an image for generating an interpretation image which can be used for data publishing so as to solve the problem of band crossing of data in the province.

(3) Data release: by using the tile technology, 11 levels of processing and reading image spots, base map vector data and front and back stage reading images are divided, and online data publishing is carried out. The storage and release processes of the data are managed by means of the built private cloud.

(4) Registration and authorization: the registration of users in the province is managed by a real-name system, the users can register in a front-end APP or background batch mode, and the registration provides basic information such as names, mobile phone numbers, units, roles and the like. After the registration information is submitted, the system needs a corresponding administrator to configure user roles, organizations and working ranges according to the user registration information. And (4) listing users with illegal or irregular behaviors in a blacklist, and forbidding login.

(5) And (3) task and issuing: the method can be distributed according to registration range and county level units, and can also be issued by an authorizer according to the task of a policeman. The system also provides flexible task reset functionality.

(6) Field investigation: taking county level units as an example, investigators can perform field investigation according to online tasks and reference images under a network environment, and can also select offline downloading to perform the investigation. The local survey is mainly carried out by depending on the APP terminal. The surveyor firstly selects a survey path according to navigation and position information, realizes the consistency of position and data according to the position deviation rectifying function, and judges the change of the previous period and the later period by utilizing the rolling screen contrast, wherein the edition comprises attribute edition, graph edition and photo and video acquisition. The system also provides auxiliary functions of superposition analysis assignment, fine spot number verification, point stepping according to a GPS, on-site unmanned aerial vehicle connection and the like. And finally, the system performs online updating in a network environment and uploads the updated online updating to a management background.

(7) And (3) performing interior work treatment: the user can download the data locally according to the requirement. And under a safe environment, performing additional recording of secret-related factors, trimming graphs, quality inspection (attributes and graphs) before data result submission, and completing statistical analysis according to a self-contained statistical program of the cloud server.

(8) And (4) summarizing and examining: the non-secret-involved part can be directly gathered by a background, and the secret-involved part needs physical isolation and offline gathering. The superior department can rely on the system to perform spot check according to the summary content, and the system provides the existing class for extracting, editing and uploading functions.

(9) Handing over and supervising: after the research results of provincial units are handed over to the gathering department, the results are handed over to relevant departments to supervise and supervise. The system has the functions of supervising and supervising roles. And finally, archiving the data.

(10) And (3) management service: the system also has the management service functions of notification announcement, progress management, comprehensive display analysis, work condition, site consultation and the like.

The foregoing description is only exemplary of the preferred embodiments of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention according to the present application is not limited to the specific combination of the above-mentioned features, but also covers other embodiments where any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims

1. An online forest resource supervising method based on mobile internet is characterized by comprising the following operations based on a mobile terminal and a cloud server:

1) Collecting forest resource data including interpretation pattern spot vector data in an inspection range;

the collected forest resource data comprise interpretation pattern spot vector data, early-stage image data, local-stage image data and administrative division boundary data; carrying out data field standardization on collected interpretation pattern spot vector data to form survey data, and warehousing the survey data; for the collected early-stage image data or the current-stage image data, performing mask cutting processing after coordinate system registration to form early-stage investigation reference image data and current-stage investigation reference image data, performing data grading slicing on the early-stage investigation reference image data and the current-stage investigation reference image data, and then issuing;

2) Carrying out normalization pretreatment on the interpretation pattern spot vector data to form base map data and establish a survey map layer; establishing a buffer range for the interpretation pattern spots in the base map data to generate mask pattern spots, and if the area of the mask pattern spots does not exceed a threshold value, releasing the mask pattern spots to the registered mobile terminal on line; if the area of the mask pattern spot exceeds the threshold value, performing segmentation processing on the mask pattern spot, then performing mask cutting, and then issuing the mask pattern spot to the registered mobile terminal on line; the mask cutting comprises data superposition, data cutting and data inspection after the cutting so as to generate an interpretation image for data release, and the coordinate system is uniformly projected to a GCS2000 coordinate system;

3) When the online release is carried out, if the registered user is a unit below the county level, the cloud server or the management personnel issues the tasks of the mask pattern spots within the supervision range, otherwise, the management personnel issues the independent tasks;

or after downloading the tasks offline, the investigators perform field investigation through the mobile terminal to form investigation data, perform online updating in a network environment through the mobile terminal, and then upload the investigation data to the cloud server;

after the tasks are issued, management personnel manage and distribute the tasks through the cloud server, and mark the unallocated tasks on the map through the color of the pattern spots; for unallocated tasks, managers allocate task patches to users through map framing or through a pattern attribute screening mode; each user acquires the task pattern through a data interface and synchronizes the acquired task pattern to the mobile terminal; if the tasks are not distributed properly, the managers redistribute the tasks by resetting the tasks; information confirmation is carried out on the information of management personnel before the task is reset; the approved task is not allowed to carry out the operation of resetting the task;

the step of performing the additional recording of the secret-related factors and the trimming of the graph comprises the following steps: the attribute factor of the data exported by the mobile terminal after field investigation is perfected through geographic information, and the graphic data is corrected and perfected;

the quality inspection before the submission of the survey data comprises the following steps: selecting a quality inspection scheme comprising logic quality inspection and spatial topology inspection, and exporting error information of the quality inspection after the cloud server performs quality inspection according to the quality inspection scheme;

carrying out statistical verification on error information exported after the quality inspection is finished; the statistical verification comprises data statistics and data updating; the data statistics is to classify, count and summarize the data passing the data quality inspection according to categories;

the data update is as follows: updating the interpretation pattern spot data processed by the internal work into a cloud server; the cloud server stores the data in a warehouse and updates the corresponding data, and only the latest corrected data content is displayed; original data are brought into a historical database for storage, and the historical database is used for storing data contents which are investigated and corrected by a user for many times;

7) The online and offline updating and reporting of the survey data are both checked by a user managed by a survey unit and then submitted to a superior unit for checking and acceptance; during auditing and acceptance, the superior unit screens out a sample for spot check on the cloud server according to the summarized audit content and judges whether the sample is qualified or not; if the data is not qualified, returning to the investigation unit and then auditing again by the management user, and if the data is qualified, submitting the investigation data successfully;

and the cloud server hands over suspected illegal image spots in the finally submitted successful data, and archives and files the offline file and the online data after supervision and supervision.

2. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein:

the early-stage survey reference image data and the current-stage survey reference image data also comprise buffer image spot data formed by buffering the interpretation image spot data for 50 meters, and the image spot data is subjected to mask cutting processing;

3. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein: the registered user is that the investigator registers independently through a mobile terminal or registers in batch through a cloud server;

4. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein: the field survey comprises the following steps:

5. The online forest resource supervision method based on the mobile internet as claimed in claim 4, wherein:

the graphic editing comprises GPS point collection drawing, continuous point collection drawing, picture drawing, cross point drawing, coordinate point drawing, point moving, point adding, point deleting and trimming, line segmentation, merging, edge sharing, surface segmentation, scattering, translation, deletion, cancellation and recovery;

clicking the roller shutter by a finger to display all layers on a screen, wherein each layer is used for displaying front and rear images; the user clicks and selects an early-stage image or a later-stage image in the 'selection rolling map list', a finger is slid to pull the screen after the image is selected, and a contrast boundary line appears in the range of the screen by the mobile terminal; the direction of the pulled screen is any direction, and the contrast change pattern spots are viewed from two sides of the contrast boundary line by pulling the screen at the position where the earlier and later image patterns are displayed and changed;

the newly increased occupation pattern spot is executed according to the following steps: drawing and recording the newly occupied pattern spots in situ through each drawing mode, and uploading the newly occupied pattern spots to a cloud server;

the property editing is performed according to the following steps: selecting a pattern spot to enter an attribute interface to edit the pattern spot attribute, editing and changing each attribute field by a user according to a corresponding attribute survey form, finishing editing and clicking to save, and finishing editing and processing the attribute;

the stack analysis assignment is performed according to the following steps: selecting two or more surface layer pattern spots with overlapped positions, performing superposition analysis on the counted field attributes, and generating a statistical field result for comparing the statistical layer with the position superposition layer;

6. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein:

the steps of the summary examination are as follows:

the cloud server firstly detects the current survey shift state information, and if the current survey shift state information is approved, the current survey shift state information cannot be submitted; filtering sensitive attribute factors by the survey data meeting the conditions, uploading the surveyed multimedia files to a file service module, and associating the surveyed multimedia files with the current survey class;

the management user audits after receiving the information of the data to be audited; transversely comparing the interpretation data with the survey data during auditing; auditing the return of the data which do not meet the requirements of the user, and filling a return opinion; the investigator modifies and submits the investigation data again; the cloud server feeds back the audit state of the audit approved survey data to the mobile terminal of the survey user;

comparing the interpretation class data with the survey data during auditing, detecting the pattern spots with larger area change difference and prompting; in combination with the condition of the domestic recheck, an auditor selects to carry out spot check on the data;

the spot check comprises the following steps:

the spot check comprises a full check, a designated spot check and a spot check; the full-check is to copy all graphs and factors related to the survey data to a spot check layer; the appointed spot check is carried out by selecting any class or any class in the region; the spot check is to randomly extract a small class for spot check according to ABS rules; and after the spot check is finished, submitting the spot check data of field work verification to a cloud server through the mobile terminal.

7. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein:

8. The online forest resource supervision method based on the mobile internet as claimed in claim 1, wherein:

the comprehensive display analysis comprises the following steps: the mobile terminal analyzes and arranges key index information from the service system data, displays the key index information on the cloud server through a report or a statistical chart, and performs ranking display aiming at each level of supervision progress, self-check result and interpretation area difference index; the report and the statistical chart comprise the issued suspected small shifts, the actual suspected small shifts, the county reported small shifts, the un-checked small shifts in the provincial examined monitoring area, the checked small shifts in the monitoring area and the current summarized small shifts;

the unmanned aerial vehicle video is as follows: uploading the video shot by the unmanned aerial vehicle to a mobile terminal to realize real-time picture information display of the video; meanwhile, the data of the unmanned aerial vehicle is combined with the geographic information, and the current position and route information of the unmanned aerial vehicle are displayed.