A natural condition evaluation method, device and medium based on watershed unit

Abstract

The present application discloses a method, device and medium for evaluating natural conditions based on watershed units, wherein the method includes: determining an initial monitoring section set of a target river; clipping target digital elevation model data based on watershed vector data; transforming the target digital elevation model data into a horizontal coordinate system through projection to perform hydrological analysis to extract a first watershed unit set; eliminating redundant monitoring sections to obtain an intermediate monitoring section set; using the intermediate monitoring section in the intermediate monitoring section set as a pouring point to extract a second watershed unit set; merging the first watershed unit set with the second watershed unit set to obtain a third watershed unit set, and evaluating the natural conditions based on the third watershed unit set and visible light satellite remote sensing images. Evaluating the health status of a river from the scale of a watershed unit can make full use of remote sensing image data resources and can be applied to rivers in watersheds of different scales.

Description

Technical Field

[0001] The present application relates to the field of river monitoring, and specifically to a natural condition evaluation method, equipment and medium based on a watershed unit. Background Art

[0002] River health refers to the achievement and maintenance of river management that is compatible with the ecological environment and economic and social characteristics of the river basin and based on the harmony between people and water, and the good ecological status and social service functions of the river. Existing technologies evaluate the health of rivers and lakes from four criteria levels, namely "basin", "water", biology, and social service functions, based on the concept of river and lake health. The "basin" criterion level mainly examines the integrity of the river's morphological structure, and the indicators include the river's longitudinal connectivity index, the natural condition of the shoreline, the riverbank width index, and the degree of illegal development and utilization of the shoreline of the water area.

[0003] The natural condition of the shoreline is a mandatory indicator of the river evaluation index system, including two aspects: riverbank stability and shoreline vegetation coverage. Its survey scope or sampling monitoring location is usually the river bank. In the prior art, a monitoring river section is set at the monitoring point according to the characteristics of the evaluation index. The monitoring river section range is determined by a fixed length method or a multiple of the river water surface width method. Each monitoring river section can be set with several monitoring sections.

[0004] This method of dividing the monitored river sections and monitoring sections to evaluate the natural conditions of the shoreline has the following disadvantages: it fails to cover the areas in the river that really need attention, especially the health of the tributaries, resulting in the monitoring results being unable to fully reflect the actual situation of the river; the overly broad setting of the monitored river sections may lead to too many monitoring points, thereby increasing the monitoring cost and workload and reducing data processing efficiency. Summary of the invention

[0005] In order to solve the above problems, the present application proposes a natural condition evaluation method, device and medium based on a watershed unit, wherein the method includes:

[0006] Obtain river data corresponding to the target river, the river data including river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; based on the river system data, use a fixed length method or a river surface width multiple method to determine the initial monitoring section set of the target river; based on the watershed vector data, cut out the target digital elevation model data within the target river; transform the target digital elevation model data into a horizontal coordinate system through projection, and perform hydrological analysis to extract the first watershed unit set; in the initial monitoring section set The redundant monitoring sections are eliminated to obtain an intermediate monitoring section set; the intermediate monitoring sections in the intermediate monitoring section set are used as pouring points to extract the second watershed unit set; the third watershed unit set is obtained by merging the first watershed unit set with the second watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gap, and the number of detection sections in each third watershed unit is lower than a preset threshold; based on the third watershed unit set and visible light satellite remote sensing images, the natural state of the target river is evaluated.

[0007] In one example, the natural state evaluation of the target river based on the third watershed unit set specifically includes: preprocessing the visible light satellite remote sensing image to obtain preprocessed remote sensing image data; calculating the normalized vegetation index, normalized water body index and normalized building index corresponding to the preprocessed remote sensing image data; taking the part of the normalized water body index higher than a preset threshold as the water body, and extracting the water body vector from the preprocessed remote sensing image; based on the normalized vegetation index and the water body vector, determining the vegetation coverage rate corresponding to each pixel in the preprocessed remote sensing image; performing land use classification on each pixel in the preprocessed remote sensing image; and evaluating the natural state of the target river based on the vegetation coverage rate and the land use classification.

[0008] In one example, the natural state of the target river is evaluated based on the vegetation coverage rate and the land use classification, specifically including: determining the vegetation coverage rate score of each pixel in the preprocessed remote sensing image based on the vegetation coverage rate; determining the human activity intensity score corresponding to each pixel in the preprocessed remote sensing image based on the land use classification; determining the average vegetation coverage rate score and the average human activity intensity score corresponding to each third watershed unit based on the vegetation coverage rate score and the human activity intensity score; determining the natural condition score within the third watershed unit based on the average vegetation coverage rate score, the average human activity intensity score and preset weights corresponding to each third watershed unit.

[0009] In one example, the human activity intensity scores corresponding to each pixel in the preprocessed remote sensing image are determined based on the land use classification, specifically including: determining the human activity intensity scores corresponding to different land use types; assigning the corresponding human activity intensity scores to the pixels based on the land use types corresponding to each pixel; converting the assigned remote sensing image from a vector result to raster data; and calculating the human activity intensity corresponding to each pixel through a normalization formula.

[0010] In one example, the calculation of the normalized vegetation index, normalized water index and normalized building index corresponding to the preprocessed remote sensing image data specifically includes: based on the preprocessed remote sensing image data, obtaining the pixel value of the near-infrared band, the pixel value of the infrared band, the pixel value of the green band and the pixel value of the mid-infrared band corresponding to each pixel; based on the pixel value of the near-infrared band and the pixel value of the infrared band, determining the normalized vegetation index corresponding to each pixel; based on the pixel value of the green band and the pixel value of the near-infrared band, determining the normalized water index corresponding to each pixel; based on the pixel value of the mid-infrared band and the pixel value of the near-infrared band, determining the normalized building index corresponding to each pixel.

[0011] In one example, the method of merging the first watershed unit set with the second watershed unit set to obtain the third watershed unit set specifically includes: if in the third watershed unit set, there is a monitoring section corresponding to multiple third watershed units, then the multiple third watershed units are merged into one.

[0012] In one example, the method of taking the intermediate monitoring section in the intermediate monitoring section set as the pouring point and extracting the second watershed unit set specifically includes: superimposing the intermediate monitoring section set with the first watershed unit set to determine the number of monitoring sections in each first watershed unit; within the first watershed unit, taking the intermediate monitoring section as the pouring point using the flow direction data; and extracting the second watershed unit set based on the flow direction data and the pouring point using the watershed tool of ArcGIS.

[0013] In one example, the extracting of the second watershed unit set based on flow direction data and pouring points through the watershed tool of ArcGIS specifically includes: determining that the second watershed unit set does not include all tributaries of the target river; moving the intermediate monitoring section within a preset adjacent range, and re-extracting the second watershed unit set until the second watershed unit set includes all tributaries of the target river.

[0014] The present application also provides a natural condition assessment device based on a watershed unit, comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute: obtaining river data corresponding to a target river, the river data including river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; based on the river system data, using a fixed length method or a river surface width multiple method, determining an initial monitoring section set for the target river; based on the watershed vector data, cutting out a target digital elevation model within the target river. data; transform the target digital elevation model data into a horizontal coordinate system through projection, and perform hydrological analysis to extract a first watershed unit set; in the initial monitoring section set, eliminate redundant monitoring sections to obtain an intermediate monitoring section set; use the intermediate monitoring sections in the intermediate monitoring section set as pouring points to extract a second watershed unit set; merge the first watershed unit set with the second watershed unit set to obtain a third watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gaps, and the number of detection sections in each third watershed unit is lower than a preset threshold; based on the third watershed unit set and visible light satellite remote sensing images, evaluate the natural state of the target river.

[0015] The present application also provides a non-volatile computer storage medium storing computer executable instructions, characterized in that the computer executable instructions are configured to: obtain river data corresponding to a target river, the river data including river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; based on the river system data, determine the initial monitoring section set of the target river using a fixed length method or a river surface width multiple method; based on the watershed vector data, cut out the target digital elevation model data within the target river; transform the target digital elevation model data into a horizontal coordinate system through projection, and perform Hydrological analysis is performed to extract a first watershed unit set; in the initial monitoring section set, redundant monitoring sections are eliminated to obtain an intermediate monitoring section set; the intermediate monitoring sections in the intermediate monitoring section set are used as pouring points to extract a second watershed unit set; the first watershed unit set is merged with the second watershed unit set to obtain a third watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gaps, and the number of detection sections in each third watershed unit is lower than a preset threshold; based on the third watershed unit set and visible light satellite remote sensing images, the natural state of the target river is evaluated.

[0016] The method proposed in this application can bring the following beneficial effects: the introduction of watershed units expands the river health evaluation from the river section scale to the watershed scale, and the river health status is evaluated from the scale of the watershed unit, which can make full use of remote sensing image data resources and can be applied to rivers in watersheds of different scales, with high scale adaptability. The evaluation of the natural condition of the river with the watershed unit as the monitoring range can comprehensively consider multiple factors such as water quality, biodiversity, and land use in the watershed, and has a better evaluation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A schematic diagram of a flow chart of a natural condition evaluation method based on a watershed unit in an embodiment of the present application;

[0019] Figure 2 A schematic diagram of a watershed in which the second watershed unit set cannot be completely extracted in an embodiment of the present application;

[0020] Figure 3 A schematic diagram of a watershed completely extracted to the second watershed unit set in an embodiment of the present application;

[0021] Figure 4 A schematic diagram of a watershed in which a single monitoring section corresponds to multiple watershed units in an embodiment of the present application;

[0022] Figure 5 This is a schematic diagram of a watershed after a plurality of watershed units are merged in an embodiment of the present application;

[0023] Figure 6 A schematic diagram of a watershed of a third watershed unit set in an embodiment of the present application;

[0024] Figure 7 This is a schematic diagram of the structure of a natural condition assessment device based on a watershed unit in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0026] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0027] Figure 1 A flow chart of a natural condition evaluation method based on a watershed unit provided for one or more embodiments of this specification. The method can be applied to different types of rivers, and the process can be executed by a computing device in the corresponding field. Certain input parameters or intermediate results in the process allow manual intervention and adjustment to help improve accuracy.

[0028] The analysis method involved in the embodiments of the present application can be implemented by a terminal device or a server, and the present application does not impose any special restrictions on this. For the convenience of understanding and description, the following embodiments are described in detail by taking a server as an example.

[0029] It should be noted that the server can be a single device or a system composed of multiple devices, that is, a distributed server, and this application does not make any specific limitations on this.

[0030] like Figure 1 As shown, the embodiment of the present application provides a natural condition evaluation method based on a watershed unit, comprising:

[0031] S101: Acquire river data corresponding to a target river, wherein the river data includes river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image.

[0032] First, obtain the river data corresponding to the target river. The target river here refers to the river whose natural condition is to be evaluated. The river data includes river system data, basin vector data, digital elevation model (DEM), and visible light satellite remote sensing image. Among them, river system data and basin vector data are used to determine the monitoring section and monitoring range; digital elevation model is used to divide river basin units, requiring a resolution better than 30m and a coverage range exceeding the river basin. Visible light satellite remote sensing images are used to extract vegetation index, water body index, and land classification to construct river natural condition indicators. It is required to use data from March to October when vegetation growth is most luxuriant, with a resolution better than 30m and a coverage range exceeding the river basin.

[0033] It should be noted that the above river data can be pre-stored in a storage device of a computer device. When the natural condition of a target river needs to be evaluated, the computer device can select the river data from the storage device. Of course, the computer device can also obtain the river data from other external devices. For example, the river data is stored in the cloud. When the natural condition of a target river needs to be evaluated, the computer device can obtain the river data from the cloud. This embodiment does not limit the method for obtaining river data, and the method for obtaining river data is a prior art.

[0034] S102: Based on the river system data, use a fixed length method or a river water surface width multiple method to determine an initial monitoring section set of the target river.

[0035] Monitoring sections can be preset in the river system through river system data according to the river segmentation and monitoring section setting methods in the "Guidelines for River and Lake Health Assessment (Trial)", such as the fixed length method or the river water surface width multiple method. When setting the monitoring section, full consideration should be given to the hydrological division points of the river basin, such as the upper, middle and lower reaches of the river; the variation points of hydrological and hydraulic conditions, such as dams, large tributary confluence sections, and large tributary bifurcation points; and the land use difference division points adjacent to the river bank, such as urban river sections and rural river sections. It should be noted that the above-mentioned monitoring section setting method belongs to the prior art.

[0036] S103: based on the watershed vector data, clipping out the target digital elevation model data within the target river; transforming the target digital elevation model data into a horizontal coordinate system through projection, and performing hydrological analysis to extract a first watershed unit set.

[0037] The digital elevation model data within the watershed is cropped using the watershed vector data, and then transformed into a plane coordinate system through projection. The digital elevation model data in the plane coordinate system can be input into ArcGIS for hydrological analysis to extract watershed units. For the sake of distinction, the watershed units obtained through hydrological analysis are referred to as first watershed units. When conducting hydrological analysis, the process includes obtaining DEM data without depressions, flow direction analysis, calculating accumulated water flow, extracting river networks, extracting watersheds, and the like. The above processes are all prior arts. When all first watershed units are extracted, the set consisting of all first watershed units is called the first watershed unit set.

[0038] S104: Eliminate redundant monitoring sections from the initial monitoring section set to obtain an intermediate monitoring section set.

[0039] The river system data, initial monitoring section data, and first basin unit data are superimposed and displayed together. Since there are multiple monitoring sections in a first basin determined by the fixed length method or the river water surface width multiple method, it is necessary to remove redundant monitoring sections, but the hydrological distinction points, hydraulic variation points, and land use distinction points of the river should be retained. When removing redundant monitoring sections, they can be removed manually, and after the removal is completed, the intermediate monitoring section set is obtained.

[0040] S105: Taking the intermediate monitoring section in the intermediate monitoring section set as the pouring point, extracting the second watershed unit set.

[0041] The intermediate monitoring sections obtained after the initial screening are superimposed on the first watershed unit. There will still be multiple intermediate monitoring sections in each first watershed unit. In this case, the flow direction data can be used in the first watershed unit to take the intermediate monitoring section points as pouring points, extract the second watershed unit, and thus obtain the second watershed unit set.

[0042] In one embodiment, when extracting the second unit set, it is necessary to superimpose the intermediate monitoring section set with the first watershed unit set to determine the number of monitoring sections in each first watershed unit, and then, within the first watershed unit, use the flow direction data to use the intermediate monitoring section as the pouring point; and use the ArcGIS watershed tool to extract the second watershed unit set based on the flow direction data and the pouring point.

[0043] Furthermore, this process may not be able to extract the second watershed units of all the intermediate monitoring sections completely after one data processing. Figure 2 As shown in , for the intermediate monitoring section where the second watershed unit cannot be extracted, the position of the intermediate monitoring section can be moved within a certain range, and the above extraction process can be repeated until the extracted second watershed unit can contain all tributaries of the target river. Figure 3 shown.

[0044] S106: The first watershed unit set is merged with the second watershed unit set to obtain a third watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gap, and the number of detected sections in each third watershed unit is lower than a preset threshold.

[0045] After obtaining the first set of basin units through hydrological analysis and the second set of basin units through pouring points, the basin unit data extracted from the hydrological analysis and pouring points are merged. There will be a result that one monitoring section corresponds to multiple basin units. At this time, multiple basin units need to be merged into one. Figure 4-Figure 5 In addition, topological errors between watershed units need to be eliminated through topological checking until the entire watershed of the target river is divided into Figure 6 There are several third watershed units shown, and there is no overlap or gap between each watershed unit. All tributaries flowing through this watershed eventually merge into the same main stream. There is a monitoring section in each third watershed unit.

[0046] S107: Evaluate the natural state of the target river based on the third watershed unit set and visible light satellite remote sensing images.

[0047] After the target river basin is divided into different third basin units, the natural state of the target river can be evaluated through the third basin units and visible light satellite remote sensing images. Here, the scale of the basin unit replaces the scale of the monitored river section and monitoring point in the existing technology to evaluate the health of the river. It can comprehensively consider multiple factors such as water quality, biodiversity, and land use in the basin, which is comprehensive; it can systematically study the interactions and connections between ecological elements such as water bodies, soil, and vegetation, which is systematic; the river health assessment method based on the basin as a unit can be applied to basins of different scales and has scale adaptability; evaluation based on the basin as a unit helps maintain the integrity of the ecosystem and water cycle process, thereby more accurately evaluating the natural state of the river.

[0048] In one embodiment, when evaluating the natural condition of a target river, the visible light satellite remote sensing image must first be processed. The processing here includes preprocessing processes such as radiation correction, geometric correction, image stitching, denoising, and image cutting. After preprocessing, the preprocessed remote sensing image in the target river basin is obtained. Then, the normalized vegetation index, normalized water index, and normalized building index corresponding to the preprocessed remote sensing image data are calculated. The part of the normalized water index that is higher than the preset threshold is taken as the water body, and the water body vector is extracted from the preprocessed remote sensing image; then, based on the normalized vegetation index and the water body vector, the vegetation coverage rate corresponding to each pixel is determined; each pixel is classified for land use; based on the vegetation coverage rate and the land use classification, the natural condition of the target river is evaluated.

[0049] Specifically, the auxiliary features include the normalized difference vegetation index (NDVI), the normalized water index (NDWI), and the normalized building index (NDBI). The calculation formulas are as follows:

[0050]

[0051] Among them, NIR is the pixel value of the near-infrared band; Red is the pixel value of the infrared band; Green is the pixel value of the green band; MIR is the pixel value of the mid-infrared band.

[0052] When extracting water body vectors, after obtaining the NDWI index results, the water body is extracted by setting the corresponding threshold. Usually, the threshold is set to 0.2, that is, the part with NDWI value greater than 0.2 is considered to be a water body. Use the "Classification>post Classification>Classification to vector" tool in ENVI to convert the raster results into vector data. In the converted vector data, the water body part is basically completely extracted, but there may still be some small spots or mis-extraction phenomena. Some post-processing operations can be taken, such as removing small spots, setting the minimum upper map area, etc., to improve the extraction results.

[0053] Vegetation coverage in river natural condition evaluation refers to the vegetation in the riverbank. When calculating vegetation coverage, the present invention should use the above water body vector data and vegetation index DNVI data for masking to eliminate the influence of water surface on vegetation coverage. Generally, an NDVI value greater than 0 indicates vegetation coverage, and a larger value indicates a higher vegetation coverage. A threshold can be set according to specific needs to determine the range of vegetation coverage. The calculation formula is:

[0054]

[0055] Among them, FVC is the vegetation coverage rate, NDVI is min and NDVI max They respectively represent the minimum and maximum NDVI within the target river’s watershed. These values ​​can be obtained by counting the NDVI values ​​in remote sensing images.

[0056] When classifying land use, according to the land use types classified in the existing standards, cultivated land, garden land, forest land, grassland, construction land, transportation land, water area, industrial and mining storage land, and other land are selected as targets, and the object-oriented land use classification method is used to classify the land use of remote sensing images in the basin.

[0057] When evaluating the natural conditions of the target river, the vegetation coverage rate and the intensity of human activities are used for evaluation. Specifically, the vegetation coverage rate can be scored by using the processing results of the above vegetation coverage rate and assigning a percentage score to each pixel in the remote sensing image according to the following scoring rule table:

[0058] Vegetation coverage (%) illustrate Points 0-10 Sparse vegetation 0-25 10-40 Medium density coverage 25-50 40-75 High density coverage 50-75 >75 And high density coverage 75-100

[0059] 2) Human activity intensity scoring

[0060] Another evaluation index of the natural condition of the shoreline in the "Guidelines for River and Lake Health Assessment (Trial)" is riverbank stability. Starting from the "basin" criterion layer, the present invention uses the above land use status results to construct a human activity intensity index to replace riverbank stability. First, a simple value is assigned according to the impact of human activities on the river, thereby obtaining the vector result corresponding to the remote sensing image.

[0061]

[0062] After the assignment, use the "Extensions>Raster Vector Converter>Vector to Raster" tool in ENVI to convert the vector results into raster data, and then calculate the human activity intensity in the remote sensing image through the maximum-minimum normalization formula. The normalization formula for human activity intensity is as follows:

[0063]

[0064] Among them, HAI Normalizatiob is the normalized value of human activity intensity, HAI is the human activity intensity value, min and HAI max They respectively represent the minimum and maximum values ​​of HAI within the watershed of the target river. These values ​​can be obtained by counting the HAI values ​​in remote sensing images.

[0065] According to the following scoring rules, the intensity of human activities is scored in percentage for each pixel in the basin.

[0066]

[0067] In one embodiment, in ArcGIS, the "zonal statistics" tool in the Spatial Analyst toolbox can be used to perform regional statistics. The vector data of the watershed unit obtained is used as the input boundary, and the mean score of vegetation coverage and human activity intensity in each watershed unit can be counted respectively. The natural condition score in the watershed unit is calculated by the following formula:

[0068] BH=FVCr*FVCw+HAIr*HAIw

[0069] Among them, BH represents the score of natural conditions in the watershed unit, FVCr represents the score of vegetation coverage in the watershed unit, FVCw represents the weight of vegetation coverage, HAIr represents the score of human activity intensity in the watershed unit, and HAIw represents the weight of human activity intensity.

[0070] like Figure 7 As shown, the embodiment of the present application also provides a natural condition evaluation device based on a watershed unit, including:

[0071] at least one processor; and,

[0072] a memory communicatively connected to the at least one processor; wherein,

[0073] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0074] Obtain river data corresponding to the target river, the river data including river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; based on the river system data, use a fixed length method or a river surface width multiple method to determine the initial monitoring section set of the target river; based on the watershed vector data, cut out the target digital elevation model data within the target river; transform the target digital elevation model data into a horizontal coordinate system through projection, and perform hydrological analysis to extract the first watershed unit set; in the initial monitoring section set The redundant monitoring sections are eliminated to obtain an intermediate monitoring section set; the intermediate monitoring sections in the intermediate monitoring section set are used as pouring points to extract the second watershed unit set; the third watershed unit set is obtained by merging the first watershed unit set with the second watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gap, and the number of detection sections in each third watershed unit is lower than a preset threshold; based on the third watershed unit set and visible light satellite remote sensing images, the natural state of the target river is evaluated.

[0075] The embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0076] Obtain river data corresponding to the target river, the river data including river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; based on the river system data, use a fixed length method or a river surface width multiple method to determine the initial monitoring section set of the target river; based on the watershed vector data, cut out the target digital elevation model data within the target river; transform the target digital elevation model data into a horizontal coordinate system through projection, and perform hydrological analysis to extract the first watershed unit set; in the initial monitoring section set The redundant monitoring sections are eliminated to obtain an intermediate monitoring section set; the intermediate monitoring sections in the intermediate monitoring section set are used as pouring points to extract the second watershed unit set; the third watershed unit set is obtained by merging the first watershed unit set with the second watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gap, and the number of detection sections in each third watershed unit is lower than a preset threshold; based on the third watershed unit set and visible light satellite remote sensing images, the natural state of the target river is evaluated.

[0077] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0078] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0079] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0080] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0083] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0084] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0085] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory media such as modulated data signals and carrier waves.

[0086] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0087] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A natural condition evaluation method based on watershed units, characterized in that: include: Acquire river data corresponding to the target river, wherein the river data includes river system data, watershed vector data, digital elevation model, and visible light satellite remote sensing image; Based on the river system data, a fixed length method or a river surface width multiple method is used to determine an initial monitoring section set of the target river; Based on the watershed vector data, clipping target digital elevation model data within the target river; The target digital elevation model data is transformed into a horizontal coordinate system through projection, and a hydrological analysis is performed to extract a first watershed unit set; In the initial monitoring section set, redundant monitoring sections are eliminated to obtain an intermediate monitoring section set; Taking the middle monitoring section in the middle monitoring section set as the pouring point, extracting the second watershed unit set; By merging the first watershed unit set with the second watershed unit set to obtain a third watershed unit set, wherein each third watershed unit in the third watershed unit set has no overlap and no gap, and the number of detection sections in each third watershed unit is lower than a preset threshold; Based on the third watershed unit set and visible light satellite remote sensing images, evaluating the natural state of the target river; The method of using the intermediate monitoring section in the intermediate monitoring section set as a pouring point to extract the second watershed unit set specifically includes: Overlaying the intermediate monitoring section set with the first watershed unit set to determine the number of monitoring sections in each first watershed unit; In the first watershed unit, the middle monitoring section is used as a pouring point using flow direction data; Extract the second watershed unit set based on flow direction data and pour points using the watershed tool of ArcGIS; The method of extracting the second watershed unit set based on flow direction data and pour points by using the watershed tool of ArcGIS specifically includes: Determining that the second set of watershed units does not include all tributaries of the target river; The intermediate monitoring section is moved within a preset adjacent range, and the second watershed unit set is re-extracted until the second watershed unit set includes all tributaries of the target river.

2. The method according to claim 1, characterized in that The evaluating the natural state of the target river based on the third watershed unit set specifically includes: Preprocessing the visible light satellite remote sensing image to obtain preprocessed remote sensing image data; Calculating the normalized vegetation index, normalized water index and normalized building index corresponding to the preprocessed remote sensing image data; The part of the normalized water index higher than the preset threshold is regarded as the water body, and the water body vector is extracted from the preprocessed remote sensing image; Based on the normalized vegetation index and the water body vector, determining the vegetation coverage rate corresponding to each pixel in the preprocessed remote sensing image; Performing land use classification on each pixel in the preprocessed remote sensing image; Based on the vegetation coverage and the land use classification, the natural state of the target river is evaluated.

3. The method according to claim 2, characterized in that The evaluating the natural state of the target river based on the vegetation coverage rate and the land use classification specifically includes: Based on the vegetation coverage rate, determining the vegetation coverage rate score of each pixel in the preprocessed remote sensing image; Based on the land use classification, determining the human activity intensity score corresponding to each pixel in the preprocessed remote sensing image; Based on the vegetation coverage score and the human activity intensity score, determine the average vegetation coverage score and the average human activity intensity score corresponding to each third watershed unit; Based on the average vegetation coverage rate, the average human activity intensity and the preset weights respectively corresponding to each third watershed unit, the natural condition score within the third watershed unit is determined.

4. The method according to claim 3, characterized in that The step of determining the intensity of human activities corresponding to each pixel in the preprocessed remote sensing image based on the land use classification specifically includes: Determine the human activity intensity scores corresponding to different land use types; Based on the land use type corresponding to each pixel, the corresponding human activity intensity score is assigned to the pixel; Convert the assigned remote sensing image from vector results to raster data; The human activity intensity within each pixel is calculated using the normalized formula.

5. The method according to claim 2, characterized in that: The calculating of the normalized vegetation index, the normalized water index and the normalized building index respectively corresponding to the pre-processed remote sensing image data specifically includes: Based on the preprocessed remote sensing image data, the pixel value of the near infrared band, the pixel value of the infrared band, the pixel value of the green band and the pixel value of the mid-infrared band corresponding to each pixel are obtained; Determine the normalized vegetation index corresponding to each pixel based on the pixel value of the near infrared band and the pixel value of the infrared band; Based on the pixel value of the green band and the pixel value of the near-infrared band, determine the normalized water index corresponding to each pixel; Based on the pixel value of the mid-infrared band and the pixel value of the near-infrared band, a normalized building index corresponding to each pixel is determined.

6. The method according to claim 1, characterized in that The step of merging the first watershed unit set with the second watershed unit set to obtain a third watershed unit set specifically includes: If, in the third river basin unit set, there is one monitoring section corresponding to multiple third river basin units, the multiple third river basin units are merged into one.

7. A natural condition evaluation device based on a watershed unit, characterized in that: include: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the method according to any one of claims 1 to 6.

8. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to execute the steps of the method according to any one of claims 1 to 6.

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