KR101782868B1 - System and method for constructing database of dangerous reservoir using unmanned aerial vehicle - Google Patents
System and method for constructing database of dangerous reservoir using unmanned aerial vehicle Download PDFInfo
- Publication number
- KR101782868B1 KR101782868B1 KR1020160026570A KR20160026570A KR101782868B1 KR 101782868 B1 KR101782868 B1 KR 101782868B1 KR 1020160026570 A KR1020160026570 A KR 1020160026570A KR 20160026570 A KR20160026570 A KR 20160026570A KR 101782868 B1 KR101782868 B1 KR 101782868B1
- Authority
- KR
- South Korea
- Prior art keywords
- reservoir
- risk
- delete delete
- images
- database
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 16
- 230000008859 change Effects 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 7
- 230000002787 reinforcement Effects 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 238000012502 risk assessment Methods 0.000 claims description 6
- 239000000463 material Substances 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 2
- 239000003086 colorant Substances 0.000 claims 1
- 238000007781 pre-processing Methods 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 241000237502 Ostreidae Species 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000014509 gene expression Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 235000020636 oyster Nutrition 0.000 description 2
- 239000002689 soil Substances 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000008921 facial expression Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 239000002893 slag Substances 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
- 230000008685 targeting Effects 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
Images
Classifications
-
- G06F17/30241—
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/14—Receivers specially adapted for specific applications
-
- G06F17/30345—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30184—Infrastructure
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Remote Sensing (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Software Systems (AREA)
- Tourism & Hospitality (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- Primary Health Care (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Computer Graphics (AREA)
- Development Economics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Processing Or Creating Images (AREA)
- Instructional Devices (AREA)
Abstract
The present invention relates to a disaster risk reservoir database building system and method. The disaster risk reservoir database building system of the present invention stores information about an unmanned aerial vehicle (UAV), a reservoir for shooting a reservoir, And a plurality of images photographed on the unmanned airplane are pre-processed, a plurality of preprocessed images are joined, orthogonal images and a DSM (Digital Surface Model) are generated from the combined images, and the orthoimage and DSM Dimensional model of the reservoir, analyzing the risk of the reservoir through the 3D stereoscopic model, and updating the database by reflecting the analyzed data. According to the present invention, by collecting data on a disaster information reservoir by using an unmanned airplane, operation cost is low, and reservoir information can be obtained quickly and accurately.
Description
The present invention relates to a system and method for constructing a disaster risk reservoir database, and more particularly, to a system and method for constructing a disaster risk reservoir database using an unmanned airplane.
The causes of the collapse of reservoirs are frequent due to the extreme weather phenomena in the world. The factors that result from this are the deterioration of the reservoir stability due to the aging of the reservoir, the increase of the local storm, the reservoir management system of the municipality, And lack thereof.
In order to manage the reservoir more systematically in this situation, it is necessary to complement the local reservoir DB and to upgrade the DB of the National Disaster Management System (NDMS).
Unmanned Aerial Vehicle (UAV) means an aircraft that does not carry a person on board. In the aviation law of Korea, the term "unmanned aerial vehicle" Of unmanned aerial vehicles or unmanned aerial vehicles, or unmanned aerial crafts of less than 180 kilograms and not exceeding 20 meters in length, excluding the weight of fuel.
Unmanned aerial vehicles are relatively inexpensive and easy to operate, so they have been widely used for military purposes mainly for reconnaissance and targeting in the past. Recently, they have been used extensively in fields of agriculture, fishery, meteorological observation, have. In spite of this widespread use, in the field of surveying, it was relatively limited to detect change of the topography or to grasp the status. However, in recent years, there have been increasing attempts to improve the performance of a digital camera and to utilize a navigation device such as a GPS / IMU for lightweighting and improving the precision and the like, for making a map using an unmanned aerial vehicle and for monitoring the land. Terrain monitoring using such unmanned aerial vehicles is relatively inexpensive to operate and has the advantage that data can be obtained quickly and accurately.
Disclosure of the Invention The present invention has been conceived to solve the above-mentioned problems. It is an object of the present invention to provide a system for more efficiently managing a reservoir DB of a National Disaster Management System (NDMS) The present invention provides a system and method for constructing a disaster risk reservoir database that can generate numerical information and 3D terrain models for reservoirs and utilize them as basic data for estimating reservoir risk.
The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.
In order to achieve the above object, the disaster risk reservoir database building system of the present invention includes a unmanned aerial vehicle (UAV) for photographing a reservoir, a database for storing information on a reservoir, A plurality of captured images are received and preprocessed, a plurality of preprocessed images are joined, an orthoimage image and a DSM (Digital Surface Model) are generated from the merged image, a 3D stereoscopic model of the reservoir is generated from the orthoimage and DSM Analyzing the risk of the reservoir through the 3D stereoscopic model, and updating the database by reflecting the analyzed data.
The server inserts a ground control point (GCP), which is measured using a GPS (Global Positioning System), at a plurality of preprocessed image joining processes, and extracts cross-sectional information Can be derived and corrected.
The server periodically collects the 3D stereoscopic model and can analyze the degree of change of the numerical value information of the reservoir to calculate the quantitative risk of the reservoir.
The reservoir numerical information may include softness, sugar height, sugar length, sugar width, watertightness, oyster, material and cross-sectional information.
The server can evaluate the risk of a reservoir at a specific time, and as a result of the risk analysis, it is possible to calculate the estimated damage of the reservoir.
In one embodiment of the present invention, the server may display the risk of the reservoir on a map by color.
The server can assess the risk to a plurality of reservoirs and select a maintenance and reinforcement priority order for the reservoirs according to the result.
A method for constructing a disaster risk reservoir database in a disaster risk reservoir database construction system using an unmanned aerial vehicle (UAV) for shooting a reservoir by flying the air space of the present invention, Generating a stereoscopic image of a reservoir from the orthoimage and the DSM, and generating a 3D stereoscopic model of the reservoir from the orthogonal image and the DSM, Analyzing the risk of the reservoir through the 3D stereoscopic model, and updating the database reflecting the analyzed data.
Further comprising the step of inserting a ground control point (GCP) surveyed using GPS (Global Positioning System) in the step of joining the plurality of preprocessed images, The cross-sectional information of the article can be corrected and derived.
The 3D stereoscopic model is periodically collected and the degree of change of the reservoir numerical information is analyzed to calculate the quantitative risk of the reservoir. Here, the reservoir numerical information may include softness, sugar height, sugar length, sugar width, watertightness, oyster, material, and section information.
In the step of analyzing the risk of the reservoir, the risk of the reservoir can be evaluated at a specific time, and the expected damage scale of the reservoir can be calculated as a result of the risk analysis.
In the step of analyzing the risk of the reservoir, the risk of the reservoir may be color-coded and displayed on a map.
In the step of analyzing the risk of the reservoir, the risk for the plurality of reservoirs can be evaluated, and the maintenance and reinforcement priority order for the reservoirs can be selected according to the result.
According to the present invention, by collecting data on a disaster information reservoir by using an unmanned airplane, operation cost is low, and reservoir information can be obtained quickly and accurately.
In addition, in the present invention, there is an advantage that it is possible to easily grasp the damages and the cross-sectional loss of the reservoir by collecting the reservoir data periodically and repeatedly by using an unmanned airplane.
In addition, the present invention is expected to provide a 3D model of a reservoir to enable a user of a national disaster management information system to systematically maintain a disaster risk reservoir through a physical model.
FIG. 1 is a block diagram showing a configuration of a system for building a disaster risk reservoir database using an unmanned airplane according to an embodiment of the present invention. Referring to FIG.
FIG. 2 is a flowchart illustrating a method for constructing a disaster risk reservoir database using an unmanned airplane according to an embodiment of the present invention. Referring to FIG.
3 is a diagram illustrating a process of creating a 2D and 3D topographical map using an unmanned aerial vehicle according to an embodiment of the present invention.
FIG. 4 is a view showing an example of a photo joint according to an embodiment of the present invention.
5 is a view illustrating a process of inserting a ground reference point according to an embodiment of the present invention.
FIG. 6 is a screen view illustrating orthoimages and DSMs according to an embodiment of the present invention.
7 is a view showing a 3D stereoscopic model according to an embodiment of the present invention.
While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.
Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted in an ideal or overly formal sense unless expressly defined in the present application Do not.
In the following description of the present invention with reference to the accompanying drawings, the same components are denoted by the same reference numerals regardless of the reference numerals, and redundant explanations thereof will be omitted. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail.
FIG. 1 is a block diagram showing a configuration of a system for building a disaster risk reservoir database using an unmanned airplane according to an embodiment of the present invention. Referring to FIG.
Referring to FIG. 1, a disaster risk reservoir database building system according to an embodiment of the present invention includes an unmanned aerial vehicle (UAV) 10, a
The unmanned airplane (10) serves to shoot the reservoir by flying over the sky. The types of the
The
The
FIG. 4 is a view showing an example of a photo joint according to an embodiment of the present invention.
FIG. 4 shows an example of a photojunction using a Postflight Terra 3D program and a photojunction using an external facial expression element.
Then, the
FIG. 6 is a screen view illustrating orthoimages and DSMs according to an embodiment of the present invention.
6 (a) is an orthoimage image, and FIG. 6 (b) is an example of a screen showing a DSM.
Then, the
7 is a view showing a 3D stereoscopic model according to an embodiment of the present invention.
7A is a side view of the 3D stereoscopic model, and FIG. 7B is a front view of the 3D stereoscopic model.
The
In the present invention, after 3D stereoscopic model generation, the cross-sectional information of the reservoir section can be inaccurately measured due to the vegetation distribution. Therefore, in the present invention, it is necessary to correct the error due to such vegetation distribution.
Accordingly, the
5 is a view illustrating a process of inserting a ground reference point according to an embodiment of the present invention. In FIG. 5, an example of a screen for inserting a total of 12 ground reference points is shown.
In the present invention, the
In one embodiment of the present invention, the
As a result of the risk analysis, the
In one embodiment of the present invention, the
In addition, the
FIG. 2 is a flowchart illustrating a method for constructing a disaster risk reservoir database using an unmanned airplane according to an embodiment of the present invention. Referring to FIG.
Referring to FIG. 2, a method for constructing a disaster risk reservoir database using an unmanned airplane according to an embodiment of the present invention first measures a ground control point (GCP) using a GPS (Global Positioning System) ).
Then, a plurality of images photographed by the
Then, a ground reference point is inserted (S207).
Then, an orthoimage and a digital surface model (DSM) are generated from the jointed image in which the ground reference point is inserted (S209). In the present invention, the cross-sectional information of the reservoir suspension can be derived from the image in which the ground reference point is inserted through step S209.
Then, a 3D solid model of the reservoir is generated from the orthoimage and the DSM (S211).
Then, the risk of the reservoir is analyzed through the 3D solid model (S213). In the step of analyzing the risk of the reservoir (S213), the risk of the reservoir can be evaluated at specific times. For example, the risk of summer heavy rain is assessed.
Then, the database is updated by reflecting the analyzed data (S215).
In one embodiment of the present invention, 3D stereoscopic models are periodically collected and the degree of change of the reservoir numerical information is analyzed to calculate the quantitative risk of the reservoir. At this time, the reservoir numerical information may include softness, sugar height, sugar length, sugar width, watertightness, fountain, material and cross-sectional information.
In the step S213 of analyzing the risk of the reservoir of the present invention, it is possible to calculate the expected damage scale of the reservoir as a result of the risk analysis.
In an embodiment of the present invention, in the step of analyzing the risk of the reservoir (S213), the risk of the reservoir may be color-coded and displayed on a map.
Also, in step S213 of analyzing the risk of the reservoir, it is possible to evaluate the risk to a plurality of reservoirs, and to select a maintenance / reinforcement priority order for the reservoirs according to the result.
3 is a diagram illustrating a process of creating a 2D and 3D topographical map using an unmanned aerial vehicle according to an embodiment of the present invention.
In the embodiment shown in FIG. 3, a fixed wing unmanned airplane is used.
Referring to FIG. 3, in the present invention, a flight path is set using a fixed wing unmanned airplane (a).
(B) The fixed wing unmanned airplane takes the reservoir along the flight path.
Then, the captured image is preprocessed (c).
Then, the preprocessed image is joined (d).
Then, an orthoimage is extracted (e), and a 2D plan view and a 3D topographical map are created (f).
In the present invention, the stability of the reservoir system and the waterway can be evaluated by using an unmanned aerial vehicle system.
For example, it is possible to evaluate the stability of dam floor height, slag clearance, slope inclination, etc. in reservoir deposits. In addition, it is possible to evaluate the stability of the Yeosu Soil Wall, Yeosu Soil Wall, Watertight Wall Wall, and Reduction Wall Walls.
While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit of the invention and the scope of the appended claims.
10
120 databases
Claims (16)
A database for storing information about reservoirs; And
A plurality of images captured by the unmanned airplane are received and preprocessed, a plurality of preprocessed images are joined, ortho images and a DSM (Digital Surface Model) are generated from the merged images, and 3D images of the reservoir A server for generating a three-dimensional model, analyzing the risk of the reservoir through the 3D stereoscopic model, and updating the database reflecting the analyzed data,
The server inserts a ground control point (GCP), which is measured using a GPS (Global Positioning System), at a plurality of preprocessed image joining processes, and extracts cross-sectional information And then,
The server periodically collects the 3D stereoscopic model and analyzes the degree of change of the numerical value information of the reservoir to calculate a quantitative risk of the reservoir. The reservoir numerical information includes light, sugar height, sugar length, sugar width, And includes material and cross-sectional information,
The server evaluates the risk of the reservoir at a specific time, calculates a damage magnitude of the reservoir as a result of the risk analysis,
The server divides the risk of the reservoir into colors and displays it on a map.
Wherein the server evaluates the risk for a plurality of reservoirs and selects a maintenance and reinforcement priority order for the reservoirs according to the result.
Receiving and preprocessing a plurality of images photographed by the unmanned airplane;
Joining a plurality of preprocessed images;
Generating a regular image and a digital surface model (DSM) from the combined image;
Generating a 3D stereoscopic model of the reservoir from the orthoimage and the DSM;
Analyzing the risk of the reservoir through the 3D stereoscopic model; And
Updating the database by reflecting the analyzed data,
Further comprising the step of inserting a ground control point (GCP) surveyed using a Global Positioning System (GPS) in the step of joining the plurality of preprocessed images,
The cross-sectional information of the reservoir assembly is corrected from the image in which the ground reference point is inserted,
The 3D stereoscopic model is periodically collected, and the degree of change of the reservoir numerical information is analyzed to calculate a quantitative risk of the reservoir. The reservoir numerical information includes a softness, a sugar height, a sugar length, a sugar solution width, And cross-sectional information,
In the step of analyzing the risk of the reservoir, the risk of the reservoir is evaluated at a specific time, the expected damage scale of the reservoir is calculated as a result of the risk analysis,
In the step of analyzing the risk of the reservoir, the risk of the reservoir is displayed on the map by color,
Wherein the step of analyzing the risk of the reservoir evaluates the risk for the plurality of reservoirs and selects the maintenance and reinforcement priority order for the reservoirs according to the result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020160026570A KR101782868B1 (en) | 2016-03-04 | 2016-03-04 | System and method for constructing database of dangerous reservoir using unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| KR1020160026570A KR101782868B1 (en) | 2016-03-04 | 2016-03-04 | System and method for constructing database of dangerous reservoir using unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| KR20170103535A KR20170103535A (en) | 2017-09-13 |
| KR101782868B1 true KR101782868B1 (en) | 2017-09-28 |
Family
ID=59967612
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020160026570A KR101782868B1 (en) | 2016-03-04 | 2016-03-04 | System and method for constructing database of dangerous reservoir using unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| KR (1) | KR101782868B1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102533928B1 (en) | 2022-11-01 | 2023-05-19 | (주) 지오씨엔아이 | Method and System for Automatically Detecting Reservoirs Using the 3D Spatial Imagery Datasets |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101858035B1 (en) * | 2017-10-26 | 2018-05-16 | (주)아세아항측 | Method for building of high precision 3D cultural heritage and web service |
| KR102118802B1 (en) * | 2018-10-29 | 2020-06-26 | 건국대학교 산학협력단 | Method and system for mornitoring dry stream using unmanned aerial vehicle |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120101796A1 (en) | 2010-10-25 | 2012-04-26 | Lindores Robert J | Water erosion management incorporating topography, soil type, and weather statistics |
-
2016
- 2016-03-04 KR KR1020160026570A patent/KR101782868B1/en active IP Right Grant
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120101796A1 (en) | 2010-10-25 | 2012-04-26 | Lindores Robert J | Water erosion management incorporating topography, soil type, and weather statistics |
Non-Patent Citations (2)
| Title |
|---|
| 박준규. 수치영상 기반의 방재지도를 활용한 방재정보시스템 개발. 한국지형공간정보학회지. 제19권, 제4호. 47~53페이지. 2011년12월. |
| 이준구 외 3명. 무인비행체를 활용한 저수지의 하류부 공간정보 취득, KCID VOL. 22, No. 1. 2015.08.12. |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102533928B1 (en) | 2022-11-01 | 2023-05-19 | (주) 지오씨엔아이 | Method and System for Automatically Detecting Reservoirs Using the 3D Spatial Imagery Datasets |
Also Published As
| Publication number | Publication date |
|---|---|
| KR20170103535A (en) | 2017-09-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR101933216B1 (en) | River topography information generation method using drone and geospatial information | |
| KR101859947B1 (en) | System and method for constructing database about safety diagnostic of dangerous reservoir using unmanned aerial vehicle | |
| Gómez-Gutiérrez et al. | Surveying coastal cliffs using two UAV platforms (multirotor and fixed-wing) and three different approaches for the estimation of volumetric changes | |
| Leitão et al. | Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas | |
| Ajayi et al. | Modelling farmland topography for suitable site selection of dam construction using unmanned aerial vehicle (UAV) photogrammetry | |
| Piermattei et al. | Suitability of ground-based SfM–MVS for monitoring glacial and periglacial processes | |
| Barry et al. | Field accuracy test of RPAS photogrammetry | |
| KR102007567B1 (en) | Stereo drone and method and system for calculating earth volume in non-control points using the same | |
| Hendrickx et al. | The use of stereoscopic images taken from a microdrone for the documentation of heritage–An example from the Tuekta burial mounds in the Russian Altay | |
| KR102195179B1 (en) | Orthophoto building methods using aerial photographs | |
| Raczynski | Accuracy analysis of products obtained from UAV-borne photogrammetry influenced by various flight parameters | |
| KR20180070070A (en) | System and method for making inundation trace map using unmanned aerial vehicle | |
| KR101782868B1 (en) | System and method for constructing database of dangerous reservoir using unmanned aerial vehicle | |
| Hrůza et al. | Monitoring of forest hauling roads wearing course damage using unmanned aerial systems. | |
| Zietara | Creating Digital Elevation Model (DEM) based on ground points extracted from classified aerial images obtained from Unmanned Aerial Vehicle (UAV) | |
| Jiménez-Jiménez et al. | Quantification of the error of digital terrain models derived from images acquired with UAV | |
| Backes et al. | River morphology monitoring of a small-scale alpine riverbed using drone photogrammetry and LiDAR | |
| RU2716477C1 (en) | System for monitoring forest use and forest pathological changes | |
| Mtui | Tropical rainforest above ground biomass and carbon stock estimation for upper and lower canopies using terrestrial laser scanner and canopy height model from unmanned aerial vehicle (UAV) imagery in Ayer-Hitam, Malaysia | |
| CN115638772A (en) | Method for extracting landslide disaster information in high mountain canyon region based on unmanned aerial vehicle image data | |
| Nguyen et al. | Flight height of UAV and its influence on the precise digital elevation model at complex terrain | |
| Garcia et al. | Using terrestrial laser scanner and RPA-based-photogrammetry for surface analysis of a landslide: a comparison | |
| Pandjaitan et al. | Efficient mapping for fodder cultivation with commercial small drone | |
| Casierra et al. | Methodology for Infrastructure Site Monitoring using Unmanned Aerial Vehicles (UAVs) | |
| Hostens et al. | Assessing the Role of sUAS Mission Design in the Accuracy of Digital Surface Models Derived from Structure-from-Motion Photogrammetry |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A201 | Request for examination | ||
| E902 | Notification of reason for refusal | ||
| E701 | Decision to grant or registration of patent right | ||
| GRNT | Written decision to grant |