CN111860626B - Water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing and object-oriented classification - Google Patents
Water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing and object-oriented classification Download PDFInfo
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Abstract
The invention relates to the technical field of water and soil detection, in particular to a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing and object-oriented classification, wherein the method comprises the following steps: s10: acquiring a historical water and soil detection image, and then cutting the historical water and soil detection image to obtain an image to be analyzed; s20: respectively acquiring water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results; s30: scoring the images to be decided according to the classification result, and marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value to obtain key detection data; s40: and acquiring unmanned aerial vehicle detection information from the key detection data, and triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection information. The invention has the effect of improving the efficiency of water and soil conservation detection.
Description
Technical Field
The invention relates to the technical field of water and soil detection, in particular to a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing and object-oriented classification.
Background
At present, soil and water conservation (soil and water conservation) is the work of preventing and controlling soil and water loss, protecting, improving and reasonably utilizing soil and water resources and establishing a good ecological environment. Unmanned plane is a unmanned aerial vehicle which is a remote-controlled flyable device, and unmanned plane technology is a technology which realizes tasks through radio control and terminal equipment program setting, and the implementation of the technology is mainly realized by the cooperation of a ground control system, a flight system and a task system.
The invention patent application of China with publication number of CN107844802A discloses a water and soil conservation monitoring method based on unmanned aerial vehicle low-altitude remote sensing and object-oriented classification, which comprises the steps of shooting a water and soil conservation monitoring target area by using an unmanned aerial vehicle carried with a visible light camera, and collecting control points; carrying out coordinate system registration, region integral adjustment and multi-view image dense matching on an original image photo to generate dense point cloud, further generating a TIN triangular net, and generating a real three-dimensional model of a region to be detected through texture mapping; calculating and dividing the three-dimensional model to obtain an actually optimal dividing scale suitable for the water and soil conservation monitoring target area; determining characteristic parameter indexes participating in object-oriented classification, and performing supervision classification and extraction; and calculating the total classification precision and Kappa coefficient by adopting a precision evaluation method based on the position information and a confusion matrix, and evaluating the classification precision of the model. The invention is suitable for water and soil conservation monitoring. The method solves the problems of poor applicability and low working efficiency of the existing monitoring method.
The prior art solutions described above have the following drawbacks:
in the project of detecting soil and water conservation for a long time, when the soil and water loss is detected, the soil and water loss is treated according to the specific condition of the soil and water loss, and after the treatment is finished, the detection is periodically repeated on the area, so that the working efficiency is affected, and therefore, the improvement space is left.
Disclosure of Invention
The invention aims to provide a water and soil conservation monitoring method and system based on unmanned aerial vehicle remote sensing and object classification, which improve the efficiency of water and soil conservation detection.
The first object of the present invention is achieved by the following technical solutions:
a water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object-oriented classification, the water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object-oriented classification comprising the steps of:
s10: acquiring a historical water and soil detection image, and then cutting the historical water and soil detection image to obtain an image to be analyzed;
s20: respectively acquiring water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results;
s30: scoring the images to be decided according to the classification result, and marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value to obtain key detection data;
s40: and acquiring unmanned aerial vehicle detection information from the key detection data, and triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection information.
By adopting the technical scheme, each image to be analyzed can be analyzed in a distributed and targeted manner by cutting the historical water and soil detection image, so that the efficiency and the accuracy of analysis are improved; classifying the images to be analyzed by using the water and soil detection results of each image to be analyzed, and marking the images to be decided according to the classification results, so that key detection data can be obtained; the corresponding water and soil conservation detection message is triggered according to the key detection data, so that the key detection of the areas with serious water and soil loss conditions can be realized, the repeated detection of the whole water and soil conservation areas is not needed, the detection pertinence is ensured, and the detection efficiency is improved.
The present invention may be further configured in a preferred example to: the step S10 includes:
s11: acquiring a water and soil detection area diagram from the historical water and soil detection image, and acquiring area characteristic information from the water and soil detection area;
s12: and cutting the historical water and soil detection image according to the regional characteristic information to obtain the image to be analyzed.
By adopting the technical scheme, the historical water and soil detection image is segmented according to the regional characteristic information, so that the integrity of the characteristics of the obtained image to be analyzed can be improved, and the accuracy of a subsequent analysis result is improved.
The present invention may be further configured in a preferred example to: step S20 includes:
s21: acquiring corresponding detection indexes according to the image to be analyzed, and constructing a water-soil conservation simulation graph according to the detection indexes;
s22: and comparing the image to be analyzed with the corresponding water and soil conservation simulation image, and obtaining a corresponding water and soil detection result according to the comparison result.
Through adopting above-mentioned technical scheme, through using the detection index that corresponds, simulate out the water and soil conservation analog diagram that corresponds, can correspond with waiting to analyze the image, through the mode that the picture compares, can obtain water and soil testing result more fast and more accurately to the efficiency of analysis water and soil testing result has been promoted.
The present invention may be further configured in a preferred example to: step S40 includes:
s41: acquiring unmanned aerial vehicle detection coordinates and corresponding unmanned aerial vehicle detection gesture information from the key detection data, and taking the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information as the unmanned aerial vehicle detection information;
s42: and triggering the soil and water conservation detection message according to the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information.
By adopting the technical scheme, the unmanned aerial vehicle can be controlled to go to the corresponding position for detection by acquiring the detection coordinates of the unmanned aerial vehicle; through obtaining corresponding unmanned aerial vehicle detection attitude information, can make unmanned aerial vehicle detection's result more accurate.
The present invention may be further configured in a preferred example to: step S42 includes:
s421: setting corresponding detection weights for the key detection data according to the scores, and setting the cycle detection quantity according to the detection weights;
s422: and detecting the key detection data according to the cycle detection quantity.
Through adopting above-mentioned technical scheme, through setting up corresponding detection weight, set up corresponding circulation detection quantity through this detection weight, can set up the work load of corresponding detection according to the circumstances of soil erosion to detection efficiency has been promoted.
The second object of the present invention is achieved by the following technical solutions:
a water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object-oriented classification, the water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object-oriented classification comprising:
the image segmentation module is used for acquiring a historical water and soil detection image, and then segmenting the historical water and soil detection image to obtain an image to be analyzed;
the image classification module is used for respectively acquiring water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results;
the marking module is used for scoring the images to be decided according to the classification result, marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value, and obtaining key detection data;
and the circulation detection module is used for acquiring unmanned aerial vehicle detection information from the key detection data and triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection information.
By adopting the technical scheme, each image to be analyzed can be analyzed in a distributed and targeted manner by cutting the historical water and soil detection image, so that the efficiency and the accuracy of analysis are improved; classifying the images to be analyzed by using the water and soil detection results of each image to be analyzed, and marking the images to be decided according to the classification results, so that key detection data can be obtained; the corresponding water and soil conservation detection message is triggered according to the key detection data, so that the key detection of the areas with serious water and soil loss conditions can be realized, the repeated detection of the whole water and soil conservation areas is not needed, the detection pertinence is ensured, and the detection efficiency is improved.
In summary, the present invention includes at least one of the following beneficial technical effects:
1. by segmenting the historical water and soil detection images, each image to be analyzed can be analyzed in a distributed and targeted manner, and the efficiency and the accuracy of analysis are improved;
2. the corresponding water and soil conservation detection message is triggered according to the key detection data, so that the key detection of the areas with serious water and soil loss conditions can be realized, the repeated detection of the whole water and soil conservation area is not needed, the detection pertinence is ensured, and the detection efficiency is improved;
3. by using the corresponding detection indexes, a corresponding water and soil conservation simulation diagram is simulated, so that the water and soil conservation simulation diagram can correspond to an image to be analyzed, and a water and soil detection result can be obtained more quickly and accurately in a picture comparison mode, so that the efficiency of analyzing the water and soil detection result is improved;
4. through setting up corresponding detection weight, set up corresponding circulation detection quantity through this detection weight, can set up the work load of corresponding detection according to the circumstances of soil erosion to detection efficiency has been promoted.
Drawings
FIG. 1 is a flow chart of a method for monitoring soil and water conservation based on drone remote sensing and object oriented classification in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart showing the implementation of step S10 in a water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object oriented classification in an embodiment of the invention;
FIG. 3 is a flowchart showing an implementation of step S20 in a soil and water conservation monitoring method based on unmanned aerial vehicle remote sensing and object oriented classification in an embodiment of the present invention;
FIG. 4 is a flowchart showing an implementation of step S40 in a soil and water conservation monitoring method based on unmanned aerial vehicle remote sensing and object oriented classification in an embodiment of the present invention;
FIG. 5 is a flowchart showing the implementation of step S42 in a method for monitoring soil and water conservation based on unmanned aerial vehicle remote sensing and object oriented classification in accordance with an embodiment of the present invention;
fig. 6 is a schematic block diagram of a water and soil conservation monitoring device based on drone remote sensing and object oriented classification in an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Embodiment one:
in an embodiment, as shown in fig. 1, the invention discloses a water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object-oriented classification, which specifically comprises the following steps:
s10: and acquiring a historical water and soil detection image, and then cutting the historical water and soil detection image to obtain an image to be analyzed.
In this embodiment, the historical soil and water detection image refers to an area in which the soil and water conservation condition is required to be detected by using the unmanned aerial vehicle remote sensing technology in the last time. The image to be analyzed is an image which needs to be analyzed under the conditions of water and soil conservation and water and soil loss.
Specifically, after each detection of an area requiring detection of the soil and water conservation condition by adopting an unmanned aerial vehicle remote sensing technology, the historical soil and water detection image is obtained. When the detection is carried out, corresponding instructions are sent to the unmanned aerial vehicle terminal, corresponding flight height, route, overlapping rate and other parameters are set, so that the unmanned aerial vehicle can detect the water and soil conservation of the area, and the history detection image is obtained.
Further, a preset segmentation rule is obtained, and after the historical water and soil detection image is segmented, a plurality of images to be analyzed are obtained. The specific number of images to be analyzed can be determined according to the size of the historical water and soil detection image and the segmentation rule.
S20: and respectively acquiring water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results.
In the present embodiment, the soil and water detection result refers to a result of detecting the soil and water conservation condition of the region represented by the image to be analyzed. The image to be decided refers to an image for which judgment as to whether or not repeated detection is required.
Specifically, the water and soil detection result of each image to be analyzed is obtained by detecting and analyzing the standard of the water and soil conservation degree and the corresponding image to be analyzed.
Further, the images to be analyzed are classified according to the water and soil detection results corresponding to each image to be analyzed, the specific classification standard can be that the images to be analyzed are scored according to the water and soil detection results, the grading is carried out according to the scoring results, the images to be analyzed corresponding to the same grade are classified into one class by taking the grading as the classification standard, and then the corresponding images to be decided are obtained.
S30: and scoring the images to be decided according to the classification result, and marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value to obtain key detection data.
In this embodiment, the key detection data refers to determining a region in which the detection of water and soil conservation needs to be repeated again according to the score of the region corresponding to the image to be determined in the water and soil detection result.
Specifically, corresponding scoring criteria are preset, and the scoring threshold is set in the scoring criteria. Further, after the score corresponding to each class of classification result is obtained, the score is compared with a corresponding score threshold, and the image to be decided corresponding to the score threshold is marked to obtain corresponding key detection data.
S40: and acquiring unmanned aerial vehicle detection information from the key detection data, and triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection information.
In this embodiment, the unmanned aerial vehicle detection information refers to flight data when the unmanned aerial vehicle photographs and detects the key detection data when the historical water and soil detection image is acquired. The soil and water conservation detection message is data for controlling the unmanned aerial vehicle to repeatedly perform soil and water conservation detection on the region corresponding to the key detection data.
Specifically, when a historical water and soil detection image is obtained through an unmanned aerial vehicle remote sensing technology, parameters of aerial photography of the unmanned aerial vehicle are obtained, and then the parameters are corresponding to each image to be analyzed. Further, since the key detection data are obtained by classifying and marking the images to be analyzed, corresponding unmanned aerial vehicle detection information is obtained through the association relation between the key detection data and the corresponding images to be analyzed.
Further, after the soil and water conservation treatment is performed on the area corresponding to the key detection data, for example, soil quality is improved, green plants are planted or other soil and water conservation related means are planted, the soil and water conservation detection message is triggered, and the soil and water conservation improvement condition of the area is detected.
In the embodiment, by segmenting the historical water and soil detection images, each image to be analyzed can be analyzed in a distributed and targeted manner, so that the efficiency and the accuracy of analysis are improved; classifying the images to be analyzed by using the water and soil detection results of each image to be analyzed, and marking the images to be decided according to the classification results, so that key detection data can be obtained; the corresponding water and soil conservation detection message is triggered according to the key detection data, so that the key detection of the areas with serious water and soil loss conditions can be realized, the repeated detection of the whole water and soil conservation areas is not needed, the detection pertinence is ensured, and the detection efficiency is improved.
In one embodiment, as shown in fig. 2, in step S10, i.e. acquiring a historical water and soil detection image, the historical water and soil detection image is segmented to obtain an image to be analyzed, which specifically includes the following steps:
s11: acquiring a water and soil detection area diagram from the historical water and soil detection image, and acquiring area characteristic information from the water and soil detection area.
In the present embodiment, the soil and water detection area map refers to a plan view of an area where soil and water conservation is required. The region feature information refers to features of the topography of the region.
Specifically, a water and soil detection area map corresponding to the historical water and soil detection image may be acquired in the satellite map. Further, after the soil and water detection region map is obtained, the image features of the soil and water detection region map are identified as the region feature information through a corresponding deep learning model, such as CNN, LSTM, and the like.
S12: and cutting the historical water and soil detection image according to the regional characteristic information to obtain an image to be analyzed.
Further, similarity comparison is performed on the regional characteristic information, the regional characteristic information is the same or similar, and the regional characteristic information adjacent to each other in position is classified into one type. When similarity comparison is carried out, corresponding feature vectors are established through the regional feature information, corresponding similarity is calculated through a cosine similarity algorithm, and when similarity is judged, a similarity threshold value, for example, 0.8, 0.85 or 0.9 is set, and the regional feature information reaching the similarity threshold value is used as similarity.
Further, according to the classification of the regional characteristic information as a segmentation rule, and according to the segmentation rule, the historical water and soil detection image is segmented to obtain an image to be analyzed.
In one embodiment, as shown in fig. 3, in step S20, the water and soil detection results corresponding to the images to be analyzed are obtained respectively, the images to be analyzed are classified according to the water and soil detection results, and the corresponding images to be decided are obtained according to the classification results, which specifically includes the following steps:
s21: and obtaining corresponding detection indexes according to the image to be analyzed, and constructing a water and soil conservation simulation graph according to the detection indexes.
In this embodiment, the detection index refers to a criterion of the degree of water retention. The water and soil conservation simulation map refers to a simulation map of the due topography of the region when the detection standard is met.
Specifically, the standard of the water and soil conservation condition of the area corresponding to the historical water and soil detection image is obtained, and the standard of the water and soil conservation condition is divided according to the standard of the image to be analyzed obtained by segmentation, so that the detection standard corresponding to each image to be analyzed is obtained.
Further, a water and soil conservation simulation corresponding to each image to be analyzed is constructed by the detection standard, such as the green plant coverage rate to be achieved. During construction, the soil and water detection areas can be distinguished according to the standard of cutting the images to be analyzed, the area base map corresponding to each image to be analyzed is obtained, and the topography condition meeting the standard is simulated in the area base map according to the detection standard to be used as a soil and water conservation model.
S22: and comparing the image to be analyzed with the corresponding water and soil conservation simulation image, and obtaining a corresponding water and soil detection result according to the comparison result.
Specifically, an image recognition technology is used for comparing an image to be analyzed with a water and soil conservation simulation image, and the comparison result is used as a corresponding water and soil detection result. When comparing, the similarity value obtained by comparing can be used as a water and soil detection result, preferably, when comparing, key points or key areas, such as areas where green plants are planted, can be selected in advance in the water and soil conservation simulation image, and when comparing the key points or the key areas, fitting values are increased according to actual conditions, namely the influence of the similarity degree of the key points and the key areas of the actual image to be analyzed and the key points and the key areas of the water and soil conservation simulation image on the finally obtained water and soil detection result is increased, so that the water and soil detection result is more accurate.
In one embodiment, as shown in fig. 4, in step S40, that is, the unmanned aerial vehicle detection information is obtained from the key detection data, and the soil and water conservation detection message is triggered according to the unmanned aerial vehicle detection information, the method specifically includes the following steps:
s41: and acquiring unmanned aerial vehicle detection coordinates and corresponding unmanned aerial vehicle detection gesture information from key detection data, and taking the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information as unmanned aerial vehicle detection information.
In this embodiment, the unmanned aerial vehicle detection coordinates refer to the position where the unmanned aerial vehicle stays when performing aerial photography. The unmanned aerial vehicle detection attitude information refers to information of inclination angles when the unmanned aerial vehicle performs aerial photography.
Specifically, positional information of the unmanned aerial vehicle staying when the unmanned aerial vehicle shoots an image to be analyzed corresponding to the key detection data is acquired from the key detection data, wherein the positional information is represented by longitude and latitude coordinates and is used as unmanned aerial vehicle detection coordinates. And acquiring information of the inclination angle when shooting the data of the key detection area from a storage terminal of the unmanned aerial vehicle, and taking the information as unmanned aerial vehicle detection attitude information.
Further, the obtained unmanned aerial vehicle detection coordinates and unmanned aerial vehicle detection posture information are used as unmanned aerial vehicle detection information.
S42: triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information.
Specifically, according to the unmanned aerial vehicle detection coordinates and unmanned aerial vehicle detection posture information, a water and soil conservation detection message is triggered, so that when the unmanned aerial vehicle detects key detection data again, the unmanned aerial vehicle shoots by using the same position and posture, and the accuracy of a result obtained by re-detection is ensured.
In one embodiment, as shown in fig. 5, in step S42, a soil and water conservation detection message is triggered according to the detected coordinates of the unmanned aerial vehicle and the detected attitude information of the unmanned aerial vehicle, which specifically includes the following steps:
s421: and setting corresponding detection weights for the key detection data according to the scores, and setting the cycle detection quantity according to the detection weights.
In this embodiment, the detection weight refers to the severity of the water loss and soil erosion of the region corresponding to the key detection data. The number of loop detection means the number of repeated detection of the important detection data.
Specifically, the detection weight is set according to the score of the key detection data, so that the lower the score is, the higher the corresponding detection weight is.
Further, the detection weight with the lowest value is obtained, the cycle detection number of the detection weight is set according to the actual situation, and the cycle detection number corresponding to each key detection data is calculated according to the ratio of the detection weights among the key detection data.
S422: and detecting the heavy point detection data according to the cycle detection quantity.
Specifically, each key detection data is detected according to the number of cyclic detections of each key detection data, wherein a time threshold is preset for each detection, for example, 7 days, 10 days, 14 days, or the like, and each time the time threshold is spaced, the region corresponding to the number of key detection data is detected.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
Embodiment two:
in an embodiment, a water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object classification is provided, and the water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object classification corresponds to the water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object classification in the embodiment one by one. As shown in fig. 6, the water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object-oriented classification comprises an image segmentation module 10, an image classification module 20, a marking module 30 and a cycle detection module 40. The functional modules are described in detail as follows:
the image segmentation module 10 is used for acquiring a historical water and soil detection image, and segmenting the historical water and soil detection image to obtain an image to be analyzed;
the image classification module 20 is configured to respectively obtain water and soil detection results corresponding to the images to be analyzed, classify the images to be analyzed according to the water and soil detection results, and obtain corresponding images to be decided according to the classification results;
the marking module 30 is configured to score the to-be-decided image according to the classification result, and mark the to-be-decided image corresponding to the score lower than the preset score threshold value to obtain key detection data;
the circulation detection module 40 is configured to obtain unmanned aerial vehicle detection information from the key detection data, and trigger a soil and water conservation detection message according to the unmanned aerial vehicle detection information.
Preferably, the image segmentation module 10 includes:
the feature acquisition submodule 11 is used for acquiring a water and soil detection area diagram from the historical water and soil detection image and acquiring area feature information from the water and soil detection area;
the image segmentation module 12 is configured to segment the historical water and soil detection image according to the regional characteristic information, so as to obtain an image to be analyzed.
Preferably, the image classification module 20 includes:
the simulation diagram constructing submodule 21 is used for acquiring corresponding detection indexes according to the image to be analyzed and constructing a water-soil conservation simulation diagram according to the detection indexes;
the detection sub-module 22 is configured to compare the image to be analyzed with the corresponding soil and water conservation simulation image, and obtain a corresponding soil and water detection result according to the comparison result.
Preferably, the cycle detection module 40 includes:
the parameter obtaining sub-module 41 is configured to obtain an unmanned aerial vehicle detection coordinate and corresponding unmanned aerial vehicle detection gesture information from the key detection data, and take the unmanned aerial vehicle detection coordinate and the unmanned aerial vehicle detection gesture information as unmanned aerial vehicle detection information;
the circulation detection submodule 42 is used for triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information.
Preferably, the cycle detection sub-module 42 comprises:
a number setting unit 421 for setting corresponding detection weights for the key detection data according to the scores, and setting the cycle detection number according to the detection weights;
the loop detection unit 422 is configured to detect the heavy point detection data according to the loop detection number.
Specific limitations regarding the water and soil conservation monitoring system based on the unmanned aerial vehicle remote sensing and the object-oriented classification can be found in the above description of the water and soil conservation monitoring method based on the unmanned aerial vehicle remote sensing and the object-oriented classification, and will not be described in detail herein. The modules in the water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and object-oriented classification can be fully or partially realized by software, hardware and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Claims (8)
1. The water and soil conservation monitoring method based on unmanned aerial vehicle remote sensing and object-oriented classification is characterized by comprising the following steps of:
s10: acquiring a historical water and soil detection image, and then cutting the historical water and soil detection image to obtain an image to be analyzed;
s20: respectively obtaining water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results, wherein the step S20 comprises the following steps:
s21: acquiring corresponding detection indexes according to the image to be analyzed, and constructing a water-soil conservation simulation graph according to the detection indexes;
s22: comparing the image to be analyzed with the corresponding water and soil conservation simulation image, and obtaining a corresponding water and soil detection result according to the comparison result;
s30: scoring the images to be decided according to the classification result, and marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value to obtain key detection data;
s40: and acquiring unmanned aerial vehicle detection information from the key detection data, and triggering a water and soil conservation detection message according to the unmanned aerial vehicle detection information, wherein the unmanned aerial vehicle detection information refers to flight data when the unmanned aerial vehicle shoots and detects the key detection data when acquiring the historical water and soil detection image.
2. The unmanned aerial vehicle remote sensing and object-oriented classification based soil and water conservation monitoring method according to claim 1, wherein step S10 comprises:
s11: acquiring a water and soil detection area diagram from the historical water and soil detection image, and acquiring area characteristic information from the water and soil detection area;
s12: and cutting the historical water and soil detection image according to the regional characteristic information to obtain the image to be analyzed.
3. The unmanned aerial vehicle remote sensing and object-oriented classification based soil and water conservation monitoring method according to claim 1, wherein step S40 comprises:
s41: acquiring unmanned aerial vehicle detection coordinates and corresponding unmanned aerial vehicle detection gesture information from the key detection data, and taking the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information as the unmanned aerial vehicle detection information;
s42: and triggering the soil and water conservation detection message according to the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information.
4. A method of monitoring soil and water conservation based on unmanned aerial vehicle remote sensing and object oriented classification as claimed in claim 3, wherein step S42 comprises:
s421: setting corresponding detection weights for the key detection data according to the scores, and setting the cycle detection quantity according to the detection weights;
s422: and detecting the key detection data according to the cycle detection quantity.
5. Water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and face object classification, characterized in that, water and soil conservation monitoring system based on unmanned aerial vehicle remote sensing and face object classification includes:
the image segmentation module is used for acquiring a historical water and soil detection image, and then segmenting the historical water and soil detection image to obtain an image to be analyzed;
the image classification module is used for respectively acquiring water and soil detection results corresponding to the images to be analyzed, classifying the images to be analyzed according to the water and soil detection results, and obtaining corresponding images to be decided according to the classification results, and comprises:
the simulation diagram construction submodule is used for acquiring corresponding detection indexes according to the image to be analyzed and constructing a water-soil conservation simulation diagram according to the detection indexes;
the detection sub-module is used for comparing the image to be analyzed with the corresponding water and soil conservation simulation image, and obtaining a corresponding water and soil detection result according to the comparison result;
the marking module is used for scoring the images to be decided according to the classification result, marking the images to be decided corresponding to the scoring lower than a preset scoring threshold value, and obtaining key detection data;
the circulation detection module is used for acquiring unmanned aerial vehicle detection information from the key detection data and triggering water and soil conservation detection information according to the unmanned aerial vehicle detection information, wherein the unmanned aerial vehicle detection information refers to flight data when the unmanned aerial vehicle shoots and detects the key detection data when the historical water and soil detection image is acquired.
6. The unmanned aerial vehicle remote sensing and object oriented classification based soil and water conservation monitoring system of claim 5, wherein the image segmentation module comprises:
the characteristic acquisition sub-module is used for acquiring a water and soil detection area diagram from the historical water and soil detection image and acquiring area characteristic information from the water and soil detection area;
and the image segmentation module is used for segmenting the historical water and soil detection image according to the regional characteristic information to obtain the image to be analyzed.
7. The unmanned aerial vehicle remote sensing and object oriented classification based soil and water conservation monitoring system of claim 5, wherein the cycle detection module comprises:
the parameter acquisition sub-module is used for acquiring unmanned aerial vehicle detection coordinates and corresponding unmanned aerial vehicle detection gesture information from the key detection data, and taking the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information as the unmanned aerial vehicle detection information;
and the circulation detection sub-module is used for triggering the soil and water conservation detection message according to the unmanned aerial vehicle detection coordinates and the unmanned aerial vehicle detection gesture information.
8. The unmanned aerial vehicle remote sensing and object oriented classification based soil and water conservation monitoring system of claim 7, wherein the cycle detection submodule comprises:
a number setting unit configured to set a corresponding detection weight for the key detection data according to the score, and set a cycle detection number according to the detection weight;
and the cycle detection unit is used for detecting the key detection data according to the cycle detection quantity.
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