Intelligent ecological environment management method and system based on remote sensing data and medium

Abstract

The invention provides an intelligent ecological environment management method, system and device based on remote sensing data and a medium, and the method comprises the steps: obtaining image data of an ecological system through a remote sensing image; preprocessing the image data, and performing analysis inversion and image slicing by adopting a remote sensing algorithm; monitoring the ecological condition according to the analysis inversion result; and analyzing and evaluating the ecological system pattern, the ecological system quality and the ecological problem stress according to the analysis inversion result, and displaying the image data, the monitoring result and the analysis and evaluation result according to the image slice, so as to solve the problem that the cognition of the ecological environment problem is deviated due to the local monitoring data, and the ecological environment problem is influenced. And enough detailed and accurate basis cannot be provided for a macroscopic ecological protection strategy and an environment management decision.

Description

Technical Field

[0001] The present invention relates to the field of ecological management technology, and in particular to a smart ecological environment management method, system, equipment and medium based on remote sensing data. Background Art

[0002] In today's era, with the accelerated advancement of industrialization and urbanization, the ecological environment is facing unprecedented pressure and challenges. Traditional ecological environment monitoring and management methods have gradually exposed many limitations when facing vast areas. For example, the distribution of ground monitoring stations is relatively sparse, making it difficult to fully, accurately and in real time reflect the overall status and dynamic changes of large-scale ecosystems. Such local monitoring data often leads to biased cognition of ecological and environmental problems, and cannot provide sufficiently detailed and accurate basis for macro-ecological protection strategies and environmental management decisions.

[0003] At the same time, remote sensing technology, as an advanced technical means to obtain information on the earth's surface from a long distance and contactlessly, is developing rapidly and being widely used in many fields. It has significant advantages such as wide coverage, fast information acquisition, and periodic repeated observations. It can monitor multiple elements of the ecosystem at different time and space scales, such as vegetation coverage, land use type, water body distribution, etc. With the continuous improvement of the resolution of remote sensing data and the increasing maturity of data processing algorithms, it has become possible and increasingly urgent to use remote sensing data for ecological and environmental management. Through remote sensing images, macroscopic and detailed observations of large-scale ecosystems can be carried out, thus overcoming the shortcomings of traditional monitoring methods and providing massive, multi-dimensional data support for smart ecological and environmental management, thereby achieving efficient analysis, accurate evaluation and visualization of ecosystem patterns, quality, and ecological problem threats, so as to meet the requirements of modern ecological and environmental management for comprehensiveness, accuracy and timeliness.

[0004] Therefore, it is urgent to propose an intelligent ecological environment management method, system, equipment and medium based on remote sensing data to solve the problem that local monitoring data often leads to deviations in the cognition of ecological and environmental issues and cannot provide sufficiently detailed and accurate basis for macro-ecological protection strategies and environmental management decisions. Summary of the invention

[0005] In order to overcome the problems existing in the relevant technologies, the present disclosure provides an intelligent ecological environment management method, system, equipment and medium based on remote sensing data to solve the technical problem that local monitoring data in the relevant technologies often leads to deviations in the cognition of ecological and environmental problems, and cannot provide sufficiently detailed and accurate basis for macro-ecological protection strategies and environmental management decisions.

[0006] One or more embodiments of this specification provide a smart ecological environment management method based on remote sensing data, including the following steps:

[0007] Obtaining ecosystem image data through remote sensing images;

[0008] Preprocessing the image data, analyzing and inverting the image using remote sensing algorithms, and image slicing;

[0009] Monitoring ecological conditions based on the analysis and inversion results;

[0010] Analyze and evaluate the ecosystem pattern, ecosystem quality and ecological stress based on the analysis and inversion results;

[0011] Based on the image slices, the image data, monitoring results, analysis and evaluation results are displayed.

[0012] Preferably, the monitoring of ecological conditions according to the analysis and inversion results comprises the following steps:

[0013] The ecological status includes ecosystem composition, ecological elements and ecological sensitivity;

[0014] The spatial distribution and area of ​​the ecological elements are extracted by remote sensing image information extraction means, wherein the ecological elements include forests, grasslands, water bodies, farmlands and deserts;

[0015] Based on the spatial distribution and area of ​​the extracted ecological elements, monitor the forest and grass distribution, the temporal and spatial changes of annual forest and grass vegetation coverage, water body distribution, farmland crop growth, desertification status and desertification degree.

[0016] Preferably, the monitoring of ecological conditions according to the analysis and inversion results further includes the following steps:

[0017] The ecological sensitivity includes soil erosion sensitivity and land desertification sensitivity;

[0018] Adopt the basic principle of universal soil erosion equation, select parameter factors, calculate and analyze the sensitivity level and spatial distribution of soil erosion in the basin, and monitor the sensitivity of soil erosion in the basin in that year;

[0019] Select factor indicators, calculate the sensitivity of land desertification in the basin, use the spatial analysis of geographic information system to multiply the sensitivity impact distribution maps of each single factor, obtain the regional land desertification sensitivity level distribution map, and monitor the sensitivity of land desertification.

[0020] Preferably, the analysis and assessment of the ecosystem pattern according to the analysis and inversion results specifically includes the following steps:

[0021] Analyze and evaluate the index value and spatial distribution of desertified land area ratio and the index value and spatial distribution of water wetland area ratio in the current year;

[0022] The landscape pattern analysis model was applied to analyze the landscape fragmentation index and landscape connectivity of the overall region and different functional zones in the year, and to quantify the connection between different patch types and landscape types in the landscape, and between patches of the same and different types.

[0023] Preferably, the analysis and assessment of ecosystem quality according to the analysis and inversion results specifically includes the following steps:

[0024] Combined with the forest and grassland coverage extraction results of the previous year, the forest and grassland coverage improvement rate index value is calculated to analyze the forest and grassland ecological quality of the year, and the vegetation index reflecting the photosynthetic effective radiation absorption of vegetation is used to invert the growth of farmland crops and reflect the ecological quality of farmland;

[0025] The inversion model was applied to obtain the spatial distribution characteristics of chlorophyll a and suspended sediment, and a spatial distribution map was drawn to analyze the water quality of the basin that year;

[0026] The inversion model was applied to obtain the spatial distribution characteristics of chemical oxygen demand, total nitrogen and total phosphorus, and a spatial distribution map was drawn to analyze the water quality of the Wulansuhai water body that year.

[0027] Preferably, the analysis and assessment of ecological stress based on the analysis and inversion results specifically includes the following steps:

[0028] Classify the vegetation growth and obtain the vegetation growth grade distribution map for the year;

[0029] By using the inversion model, the spatial distribution characteristics of grassland degradation and land desertification were obtained, and the spatial distribution maps were drawn respectively;

[0030] The salinization sensitivity model was applied to perform spatial operations and obtain the salinization sensitivity level distribution map.

[0031] Preferably, the display of the image data, monitoring results, analysis and evaluation results specifically includes the following steps:

[0032] After multi-year data fusion, the collected data, monitoring results, analysis and evaluation results are displayed through videos, graphics, reports and voice.

[0033] One or more embodiments of this specification provide a smart ecological environment management system based on remote sensing data, including a data acquisition module, a data processing module, a monitoring module, an analysis module, and a display module;

[0034] The data acquisition module is used to acquire image data of the ecosystem through remote sensing images;

[0035] The data processing module is used to pre-process the image data, perform analysis and inversion using remote sensing algorithms, and perform image slicing;

[0036] The monitoring module is used to monitor the ecological status according to the analysis and inversion results;

[0037] The analysis module is used to analyze and evaluate the ecosystem pattern, ecosystem quality and ecological problem stress according to the analysis and inversion results;

[0038] The display module is used to display the image data, monitoring results, analysis and evaluation results based on the image slices.

[0039] One or more embodiments of the present specification provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the above-mentioned intelligent ecological environment management method based on remote sensing data is implemented.

[0040] One or more embodiments of the present specification provide a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned smart ecological environment management method based on remote sensing data are implemented.

[0041] The invention discloses a smart ecological environment management method, system, equipment and medium based on remote sensing data, which has the advantages of obtaining image data of the ecosystem through remote sensing images, covering a large area of ​​ecological areas, breaking through the spatial limitations of traditional ground monitoring sites, and obtaining relevant information of the ecosystem in a wide range in a short time. The image data is pre-processed to effectively remove noise, correct geometric distortion and other problems, improve data quality, and make the subsequent analysis and inversion results based on remote sensing algorithms more accurate and reliable. According to the analysis and inversion results, the ecological status is monitored, and the dynamic changes of various indicators of the ecosystem can be grasped in real time. According to the analysis and inversion results, the analysis and evaluation of the ecosystem pattern, ecosystem quality and ecological problem coercion can be carried out, and the ecosystem can be comprehensively analyzed from multiple dimensions. It can clearly understand the spatial distribution pattern of the ecosystem, the quality status of each component, and the various ecological problems and their coercion levels faced, providing a comprehensive and detailed basis for formulating scientific and reasonable ecological environment protection and restoration strategies, and displaying image data, monitoring results, analysis and evaluation results according to image slices, and presenting complex ecological environment data in the form of intuitive and easy-to-understand images, charts, etc. It is convenient for managers, scientific researchers and relevant decision-makers to quickly understand the current status, changing trends and existing problems of the ecological environment, promote the effective dissemination and exchange of information, help improve the scientificity and rationality of ecological environment management decisions, and realize the integrated intelligent ecological environment management process from data acquisition, processing, analysis and evaluation to display. By making full use of the advantages of remote sensing data and the coordination of various steps, it is possible to monitor, manage and support decision-making of the ecological environment more efficiently and accurately, improve the intelligence level and comprehensive efficiency of the entire ecological environment management work, and promote the development of ecological environment management in a more scientific and intelligent direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 A flowchart of a smart ecological environment management method based on remote sensing data provided by one or more embodiments of this specification;

[0044] Figure 2An ecological status display diagram provided for one or more embodiments of this specification; (a) is an ecosystem composition remote sensing monitoring diagram, (b) is a forest and grassland element monitoring diagram, (c) is a water element monitoring diagram, (d) is a farmland element monitoring diagram, (e) is a desert element monitoring diagram, (f) is an ecological sensitivity monitoring diagram, (g) is an ecosystem pattern evaluation diagram, (h) is a forest, grassland and farmland ecological quality evaluation diagram, (i) is a water body ecological quality evaluation diagram, (j) is a lake ecosystem quality evaluation diagram, and (k) is an ecological problem threat evaluation diagram;

[0045] Figure 3 A schematic diagram of the structure of a smart ecological environment management system based on remote sensing data provided by one or more embodiments of this specification;

[0046] Figure 4 A schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the protection scope of the present invention.

[0048] The present invention is described in detail below in conjunction with specific implementation methods and the accompanying drawings.

[0049] Method Embodiment

[0050] According to an embodiment of the present invention, a smart ecological environment management method based on remote sensing data is provided. Figure 1 As shown, it is a flow chart of the smart ecological environment management method based on remote sensing data provided in this embodiment. The smart ecological environment management method based on remote sensing data according to the embodiment of the present invention includes:

[0051] S110. Through remote sensing images, we obtain image data of the ecosystem and data from the pilot project for ecological protection and restoration of mountains, rivers, forests, farmlands, lakes and grasslands in the Ulungur Lake Basin. In the form of satellite remote sensing images and table data, we comprehensively display the ecological status of the Ulungur Lake Basin.

[0052] S120, preprocess the image data, use remote sensing algorithms for analysis and inversion, and slice the image. The data preprocessing process includes geometric precision correction, registration, image mosaicking and cropping, image enhancement, cloud removal and shadow processing, and spectral normalization. According to the update requirements and the remote sensing indexes involved in the system, the remote sensing image is analyzed and operated by the remote sensing algorithm. The source file of the image is in GeoTIFF format. In order to better load and display, the image updated by the system needs to be sliced, and the slice generation algorithm is written to ensure that each image has no pixel loss during the slicing process.

[0053] S130. Monitor the ecological status based on the analysis and inversion results.

[0054] S140. Analyze and evaluate ecosystem pattern, ecosystem quality and ecological threats based on the analysis and inversion results.

[0055] S150. Display image data, monitoring results, analysis and evaluation results based on image slices.

[0056] The method provided in this embodiment obtains the image data of the ecosystem through remote sensing images, which can cover a large area of ​​ecological areas, break through the spatial limitations of traditional ground monitoring sites, and obtain relevant information of the ecosystem in a wide range in a short time. The image data is pre-processed to effectively remove noise, correct geometric distortion and other problems, improve data quality, and make the subsequent analysis and inversion results based on remote sensing algorithms more accurate and reliable. The ecological status is monitored according to the analysis and inversion results, and the dynamic changes of various indicators of the ecosystem can be grasped in real time. The analysis and evaluation of the ecosystem pattern, ecosystem quality and ecological problem coercion are carried out according to the analysis and inversion results, and the ecosystem can be comprehensively analyzed from multiple dimensions. It can clearly understand the spatial distribution pattern of the ecosystem, the quality status of each component, and the various ecological problems and their coercion levels faced, providing a comprehensive and detailed basis for formulating scientific and reasonable ecological environment protection and restoration strategies. The image data, monitoring results, analysis and evaluation results are displayed according to image slices, and complex ecological environment data can be presented in the form of intuitive and easy-to-understand images, charts, etc. It is convenient for managers, scientific researchers and relevant decision-makers to quickly understand the current status, changing trends and existing problems of the ecological environment, promote the effective dissemination and exchange of information, help improve the scientificity and rationality of ecological environment management decisions, and realize the integrated intelligent ecological environment management process from data acquisition, processing, analysis and evaluation to display. By making full use of the advantages of remote sensing data and the coordination of various steps, it is possible to monitor, manage and support decision-making of the ecological environment more efficiently and accurately, improve the intelligence level and comprehensive efficiency of the entire ecological environment management work, and promote the development of ecological environment management in a more scientific and intelligent direction.

[0057] In one embodiment, monitoring of ecological conditions based on the analysis and inversion results includes the following steps:

[0058] Ecological status includes ecosystem composition, ecological elements and ecological sensitivity.

[0059] Remote sensing image information extraction is used to extract the spatial distribution and area of ​​ecological elements, including forests, grasslands, water bodies, farmlands and deserts.

[0060] Based on the spatial distribution and area of ​​the extracted ecological elements, monitor the forest and grass distribution, the spatiotemporal changes in annual forest and grass vegetation coverage, the water body distribution, the growth of farmland crops, the desertification status and the degree of desertification.

[0061] Specifically,

[0062] Forest and Grassland Element Monitoring

[0063] The forest and grassland (forest and grassland coverage) monitoring area is mainly located in the Alaben grassland in the east of Bayannur City and the intersection of the Alaben grassland and the Ula Mountains in Wulansuhai. Remote sensing images are used to monitor the large-scale forest and grassland distribution and forest and grassland vegetation coverage.

[0064] Forest and Grass Distribution Monitoring

[0065] By using medium-resolution remote sensing images from 2021 and 2022, the vegetation index is called to perform band operations to extract forest and grassland vegetation, obtain the distribution of forests and grasslands, and realize the distribution monitoring of forests and grasslands.

[0066] Forest and grass vegetation coverage monitoring

[0067] Using medium-resolution remote sensing images from 2021 and 2022, and using a pixel binary model based on the normalized vegetation index, the forest and grass vegetation coverage in 2021 and 2022 is inverted to monitor the spatiotemporal changes in vegetation coverage in the basin in 2021 and 2022.

[0068] Water distribution monitoring

[0069] The monitoring area of ​​water bodies (water area, water resource distribution) is mainly the Hetao Plain water system ecological protection network, monitoring the water area and water resource distribution of the elements. Two new medium-resolution remote sensing images in 2021 and 2022 are added. The water body index is calculated by band operation to extract water bodies, monitor the distribution and area of ​​water areas, locate the distribution of water resources, and provide basic water resource information for the management of the agricultural water conservancy ecosystem in the Hetao Plain.

[0070] The area of ​​lake (wetland) monitoring mainly covers the Wuliangsuhai Ecological Protection Zone. There are various types of landforms in the Wuliangsuhai wetland, mainly swamps, lakes, mudflats, and salt marshes. Using medium-resolution remote sensing images in 2021 and 2022, we will extract and monitor information on the spatial distribution and area of ​​wetlands, and further provide a basis for wetland ecological construction and ecological environmental protection.

[0071] Farmland element monitoring

[0072] Using medium-resolution remote sensing images from 2021 and 2022, computer-assisted classification methods are used to identify the distribution and area of ​​farmland in that year; the vegetation index that can reflect the effective radiation absorption of vegetation photosynthesis is used to reflect the growth of farmland crops.

[0073] Desert element monitoring

[0074] The main area for desert element monitoring is the Ulan Buh Desert Comprehensive Management Area, where information extraction and monitoring of desertification are carried out.

[0075] Monitoring of spatial distribution of desertified land

[0076] Using medium-resolution remote sensing images from 2021 and 2022, we extracted the spatial distribution of desertified land, calculated the proportion of desertified land area and the proportion of severely desertified desert area in that year, and provided desertification status data for the comprehensive desert control project.

[0077] Desertification Index Monitoring

[0078] By using medium-resolution remote sensing images from 2021 and 2022, and inverting soil moisture content and vertical drought index, we can further analyze the spatial distribution of different levels of desertification in that year.

[0079] The method provided in this embodiment, by extracting the spatial distribution and area of ​​ecological elements by means of remote sensing image information extraction, can accurately identify and distinguish the spatial distribution range and area size of different ecological elements such as forests, grasses, water bodies, farmlands and deserts, and clearly outline the composition of the ecosystem. It provides a high-resolution and refined data basis for in-depth understanding of the structure and composition of the ecosystem, helps to fully grasp the distribution pattern and current status of regional ecological resources, and based on detailed monitoring information of various ecological elements, can further comprehensively analyze regional ecological sensitivity, provide key decision-making support for rational planning of land use, optimization of industrial layout and formulation of ecological protection red lines, effectively reduce the negative impact of human activities on the ecological environment, and promote regional ecological balance and sustainable development.

[0080] In one embodiment, monitoring of ecological conditions based on the analysis and inversion results further includes the following steps:

[0081] Ecological sensitivity includes soil erosion sensitivity and land desertification sensitivity.

[0082] Using the basic principles of the universal soil erosion equation, parameter factors are selected to calculate and analyze the soil erosion sensitivity level and spatial distribution of the basin, and monitor the soil erosion sensitivity within the basin that year.

[0083] Select factor indicators, calculate the sensitivity of land desertification in the basin, use the spatial analysis of geographic information system to multiply the sensitivity impact distribution maps of each single factor, obtain the regional land desertification sensitivity level distribution map, and monitor the sensitivity of land desertification.

[0084] The method provided in this embodiment selects parameter factors for calculation and analysis based on the principle of the general soil and water loss equation, can accurately quantify the soil and water loss sensitivity level and its spatial distribution in the basin, and clearly show the differences in the degree of soil and water loss risk in different areas of the basin, providing extremely accurate data support for the targeted formulation of soil and water conservation measures and planning of basin ecological management. By scientifically selecting factor indicators to calculate the sensitivity of land desertification in the basin, and using the powerful spatial analysis function of the geographic information system to perform multi-factor comprehensive calculations, not only can the distribution of regional land desertification sensitivity levels be accurately obtained, the detailed spatial pattern and changing trend of land desertification risks can be fully revealed, and it can also be presented in the form of an intuitive grade distribution map, which is convenient for relevant departments and personnel to quickly understand and identify high-risk areas for land desertification.

[0085] In one embodiment, the analysis and assessment of the ecosystem pattern is performed based on the analysis and inversion results, specifically including the following steps:

[0086] Analyze and evaluate the index value and spatial distribution of desertified land area ratio and the water wetland area ratio and spatial distribution of the year.

[0087] The landscape pattern analysis model was applied to analyze the landscape fragmentation index and landscape connectivity of the overall region and different functional zones in the year, and to quantify the connection between different patch types and landscape types, and between patches of the same and different types.

[0088] In one embodiment, the analysis and assessment of ecosystem quality is performed based on the analysis and inversion results, specifically including the following steps:

[0089] Combined with the forest and grassland coverage extraction results of the previous year, the forest and grassland coverage improvement rate index value is calculated, and the forest and grassland ecological quality of the year is analyzed. The vegetation index reflecting the effective radiation absorption of vegetation photosynthesis is used to invert the growth of farmland crops and reflect the ecological quality of farmland.

[0090] By applying the inversion model applicable to the water body of the Wulansuhai Basin, the spatial distribution characteristics of chlorophyll a and suspended sediment were obtained, and a spatial distribution map was drawn to analyze the water quality status of the basin that year.

[0091] By applying the inversion model applicable to the Wulansuhai Lake, the spatial distribution characteristics of chemical oxygen demand, total nitrogen and total phosphorus were obtained, and a spatial distribution map was drawn to analyze the water quality of the Wulansuhai Lake that year.

[0092] The method provided in this embodiment can accurately quantify the annual changes in forest and grassland ecological quality by comparing the forest and grassland coverage of the current year with that of the previous year and calculating the coverage improvement rate index value. The vegetation index is used to invert the growth of farmland crops, and the farmland ecological quality information can be intuitively obtained. The spatial distribution characteristics of chlorophyll a and suspended sediment are obtained by using the inversion model and a distribution map is drawn. The spatial heterogeneity of water quality in the basin can be intuitively displayed, and the water pollution hotspots and clean water source areas can be clearly located. The spatial distribution characteristics of chemical oxygen demand, total nitrogen and total phosphorus are obtained with the help of the inversion model, and the water quality distribution map of Wuliangsuhai Lake is drawn, realizing comprehensive and refined monitoring of the water quality of the lake. This is of great significance for timely discovering problems such as eutrophication of the lake and the spread of pollution. Integrating the ecological quality analysis and evaluation results of forests, farmlands, watersheds and lakes can build a comprehensive regional ecosystem quality evaluation system. This rich and detailed information provides a comprehensive data basis for ecological and environmental management departments to formulate comprehensive ecological protection policies, land use plans and regional development strategies, promotes scientific, precise and forward-looking ecosystem management decisions, and effectively improves the overall quality and sustainable development capabilities of regional ecosystems.

[0093] In one embodiment, the analysis and assessment of ecological stress is performed based on the analysis and inversion results, specifically including the following steps:

[0094] Ecological stress reflects the interference of human activities on the normal structure and function of the basin ecosystem. In the Wulansuhai Basin, it is manifested as vegetation growth assessment, grassland degradation assessment, and land desertification and salinization assessment.

[0095] Vegetation growth: Classify the vegetation growth and obtain the vegetation growth grade distribution map for the year.

[0096] Grassland degradation: Grassland degradation refers to the phenomenon or process in which grassland biological resources, land resources, water resources and ecological environment deteriorate due to natural conditions and human activities, leading to a decline in productivity. The inversion model is used to obtain the spatial distribution characteristics of grassland degradation and draw a spatial distribution map.

[0097] Land desertification: Land desertification refers to the phenomenon that the topsoil loses fine particles (silt and clay) and gradually becomes sandy due to soil erosion, or the land productivity decreases or even loses due to the invasion of quicksand (silt). The inversion model applicable to the desertified land of Wulansuhai is applied to obtain the spatial distribution characteristics of land desertification and draw a spatial distribution map.

[0098] Salinization: Salinization sensitivity mainly depends on factors such as evaporation / precipitation, groundwater mineralization, groundwater depth, and soil texture. The salinization sensitivity model is used to perform spatial calculations to obtain a salinization sensitivity level distribution map.

[0099] The method provided in this embodiment can show the difference of vegetation growth conditions in the region in an intuitive and clear way by classifying vegetation growth and obtaining the vegetation growth grade distribution map of the year. The inversion model is used to obtain the spatial distribution characteristics of grassland degradation and land desertification and draw the corresponding distribution map, realizing the accurate monitoring of grassland and land desertification conditions. The salinization sensitivity model is used for spatial calculation and the salinization sensitivity grade distribution map is obtained, which can comprehensively evaluate the sensitivity of salinization in the region and its spatial distribution. The monitoring and evaluation results of vegetation growth, grassland degradation, land desertification and salinization sensitivity can enable relevant personnel to clearly grasp the ecological environment situation in the region as a whole. These detailed distribution maps and evaluation information provide a comprehensive and reliable basis for the formulation of comprehensive ecological and environmental protection policies, resource development and utilization plans, and ecological restoration plans, promote the scientific and refined decision-making of ecological and environmental management, and promote the development of regional ecological environment in a healthy and sustainable direction.

[0100] In one embodiment, the image data, monitoring results, analysis and evaluation results are displayed, such as Figure 2 As shown, the ecological status display diagram provided in this embodiment specifically includes the following steps:

[0101] After integrating the collected data, monitoring results, analysis and evaluation results over multiple years, they are displayed through videos, graphics, reports and voice.

[0102] Figure 2 (a) is the remote sensing monitoring map of the ecosystem. The process changes of the ecosystem can be characterized by the changes in ecological elements. The forest and grassland element monitoring, water element monitoring, farmland element monitoring, desert element monitoring, and mining element monitoring indicators are used to quantitatively evaluate the changes in the pattern of the watershed ecosystem before and after the implementation of the project, so as to reflect the changes in the ecosystem process and the effectiveness of ecological restoration.

[0103] Figure 2(b) is the forest and grassland element monitoring map. The forest and grassland element can reflect the status and changes of forest and grassland resources in a large area and is an important part of the project in the implementation of monitoring. New remote sensing monitoring and analysis in 2021 and 2022 will be added to realize the monitoring of forest and grassland distribution and vegetation coverage in the forest and grassland element monitoring.

[0104] Figure 2 (c) is a water element monitoring map. Water elements can reflect the status of water resources and area changes in a large area, provide theoretical support data for the rational development and protection of project engineering, and are also an important part of water area monitoring during the implementation of the project. The water elements in 2021 and 2022 are presented in the form of analysis charts, including water distribution, lake water index, and farmland water index changes.

[0105] Figure 2 (d) is the farmland element monitoring map. The farmland element monitoring mainly monitors the distribution of farmland and the growth of crops. It displays the regional distribution of farmland area, crop growth, and regional conditions of crop growth in 2021 and 2022 through analytical charts, providing a reference for the government to understand the latest situation of farmland and make scientific decisions.

[0106] Figure 2 (e) is a desert element monitoring map, which displays the sand area, regional distribution of sand area, soil moisture area, and vertical drought index distribution area in 2021 and 2022 in the form of graphs and tables. It directly reflects the current status, degree and dynamic evolution of desertification, and provides data reference for desertification prevention and control work.

[0107] Figure 2(f) is the ecological sensitivity monitoring map. Ecologically sensitive and vulnerable areas include ecologically sensitive areas and ecologically fragile areas. Ecologically sensitive areas refer to areas that are particularly sensitive to human production and living activities or have potential natural disaster impacts, and are extremely susceptible to improper human development activities and produce negative ecological effects. Ecologically sensitive areas include all contents belonging to the ecological category, such as biology, habitat, water resources, atmosphere, soil, geology, landforms, and environmental pollution. Its types include: river systems, waterfront areas, mountains and hills, special or rare plant communities, wildlife habitats, and important ecosystems such as swamps and wetlands. Ecologically fragile areas, also known as ecological transition areas, refer to the boundary transition area between two different types of ecosystems. Ecologically fragile areas have the basic characteristics of weak system anti-interference ability, sensitivity to global climate change, strong temporal and spatial volatility, significant edge effects, and high environmental heterogeneity. Therefore, it is necessary to strengthen the monitoring of their changes to provide a theoretical basis for the process of ecological restoration. The monitoring data in this module only inverts the index data of soil and water loss sensitivity distribution and land desertification sensitivity distribution from 2018 to 2020, and cannot reflect the changing trends of indicators calculated for middle and upper category elements in 2021 and 2022. This module needs to add data for 2021 and 2022 to better show the changes in various sensitivity indicators in the process of ecological restoration.

[0108] Figure 2 (g) is an ecosystem pattern assessment map, which uses remote sensing image inversion results to show the evaluation of desertified land and water wetlands. The ecosystem pattern assessment display for 2021 and 2022 has been added, mainly including the area ratio of desertified areas, the area ratio of water wetlands, the proportion of landscape area occupied by patches, the grassland landscape fragmentation index and changes, and the sand landscape concentration index and changes.

[0109] Figure 2 (h) is a forest, grassland and farmland ecological quality evaluation map. The forest, grassland and farmland ecological quality evaluation indicators mainly include forest and grassland coverage improvement rate, crop growth and other indicators. Using graphs, tables and other display methods, new forest, grassland and farmland ecological quality evaluation indicators for 2021 and 2022 are added to present the forest and grassland coverage improvement rate in the basin, regional comparison of forest and grassland coverage improvement rate in the basin, crop growth, and regional comparison of crop growth. It directly reflects the effect of ecological restoration and provides data support for the next step of work.

[0110] Figure 2(i) is a water ecological quality evaluation chart. The quality of water ecosystems is a sensitive factor and indicator of regional ecological and environmental changes, and has an important impact on regional water resources management, planning, and policy formulation. The water ecosystem quality indicators mainly include water chlorophyll A, water suspended sediment and other indicators. The water ecosystem quality evaluation for 2021 and 2022 is newly added, and the chlorophyll A content of water bodies, regional comparison of chlorophyll A content of water bodies, suspended sediment content of water bodies, and regional comparison of suspended sediment content of water bodies are displayed in the form of charts.

[0111] Figure 2 (j) is a lake ecosystem quality evaluation chart. The lake ecosystem quality mainly reflects the water quality of the lake through the chemical oxygen demand, total nitrogen and total phosphorus in the water body, which is the main basis for water quality management policies. The lake ecosystem quality indicators mainly include water environment chemical oxygen demand, water environment total nitrogen, water environment total phosphorus and other indicators. New lake ecosystem quality indicators for 2021 and 2022 and the evaluation of the indicators are added.

[0112] Figure 2 (k) is an evaluation chart of ecological stress, which provides a theoretical basis for scientific protection and effective restoration, and provides objective data support for monitoring the effectiveness of restoration projects. The ecological stress indicators mainly include vegetation degradation situation-vegetation growth, vegetation degradation situation-grassland degradation, desertification difference index, soil salinity index and other indicators. The evaluation and display of relevant indicators in 2021 and 2022 are newly added, mainly including vegetation growth, grassland degradation, desertification, and soil salinization, so as to better display the changes of various indicators in the process of ecological restoration.

[0113] The method provided in this embodiment integrates the collected data, monitoring results, analysis and evaluation results of multiple years and then displays them. It can present the changing trend of the ecological environment over a long time span, help to deeply analyze the evolution law of the ecosystem, and comprehensively display various related results in a unified manner. It can present the collected data, monitoring results, analysis and evaluation results from different dimensions, avoiding the inconvenience caused by information dispersion.

[0114] System Example

[0115] According to an embodiment of the present invention, a smart ecological environment management system based on remote sensing data is provided. Figure 3 As shown, it is a structural diagram of the smart ecological environment management system based on remote sensing data provided in this embodiment. According to the smart ecological environment management system based on remote sensing data in this embodiment of the present invention, it includes a data acquisition module 31, a data processing module 32, a monitoring module 33, an analysis module 34 and a display module 35.

[0116] The data acquisition module 31 is used to acquire image data of the ecosystem through remote sensing images.

[0117] The data processing module 32 is used to pre-process the image data, perform analysis and inversion using remote sensing algorithms, and perform image slicing.

[0118] The monitoring module 33 is used to monitor the ecological status according to the analysis and inversion results.

[0119] The analysis module 34 is used to analyze and evaluate the ecosystem pattern, ecosystem quality and ecological problem stress based on the analysis and inversion results.

[0120] The display module 35 is used to display the image data, monitoring results, analysis and evaluation results based on the image slices.

[0121] In the system provided by this embodiment, the data acquisition module 31 acquires the image data of the ecosystem through remote sensing images, which can cover a large area of ​​ecological areas, breaking through the spatial limitations of traditional ground monitoring sites, and can obtain relevant information of the ecosystem in a wide range in a short time. The data processing module 32 pre-processes the image data, which can effectively remove noise, correct geometric distortion and other problems, improve data quality, and make the subsequent analysis and inversion results based on remote sensing algorithms more accurate and reliable. The monitoring module 33 monitors the ecological status according to the analysis and inversion results, and can grasp the dynamic changes of various indicators of the ecosystem in real time. The analysis module 34 analyzes and evaluates the ecosystem pattern, ecosystem quality and ecological problem threats based on the analysis and inversion results, and can analyze the ecosystem from multiple dimensions. A comprehensive analysis can be carried out to clearly understand the spatial distribution pattern of the ecosystem, the quality status of each component, and the various ecological problems and their degree of coercion faced, providing a comprehensive and detailed basis for the formulation of scientific and reasonable ecological environmental protection and restoration strategies. The display module 35 displays image data, monitoring results, analysis and evaluation results according to image slices, and can present complex ecological environmental data in the form of intuitive and easy-to-understand images, charts, etc., which is convenient for managers, scientific researchers and relevant decision-makers to quickly understand the current status, changing trends and existing problems of the ecological environment, promote the effective dissemination and exchange of information, and help improve the scientificity and rationality of ecological environmental management decisions, and realize the integrated intelligent ecological environmental management process from data acquisition, processing, analysis and evaluation to display. By making full use of the advantages of remote sensing data and the coordination of various steps, it is possible to monitor, manage and support decision-making of the ecological environment more efficiently and accurately, improve the intelligence level and comprehensive efficiency of the entire ecological environmental management work, and promote the development of ecological environmental management in a more scientific and intelligent direction.

[0122] The embodiment of the present invention is a system embodiment corresponding to the above-mentioned method embodiment. The specific operations of the processing steps of each module can be understood by referring to the description of the method embodiment, which will not be repeated here.

[0123] like Figure 4 As shown, the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the smart ecological environment management method in the above-mentioned embodiment is implemented, or when the computer program is executed by a processor, the smart ecological environment management method based on remote sensing data in the above-mentioned embodiment is implemented.

[0124] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0125] Each embodiment in this specification 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 or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A smart ecological environment management method based on remote sensing data, characterized in that: The following steps are involved: Obtaining ecosystem image data through remote sensing images; Preprocessing the image data, analyzing and inverting the image using remote sensing algorithms, and image slicing; Monitoring ecological conditions based on the analysis and inversion results; Analyze and evaluate the ecosystem pattern, ecosystem quality and ecological stress based on the analysis and inversion results; Based on the image slices, the image data, monitoring results, analysis and evaluation results are displayed.

2. The smart ecological environment management method according to claim 1, characterized in that: The monitoring of ecological conditions according to the analysis and inversion results comprises the following steps: The ecological status includes ecosystem composition, ecological elements and ecological sensitivity; The spatial distribution and area of ​​the ecological elements are extracted by remote sensing image information extraction means, wherein the ecological elements include forests, grasslands, water bodies, farmlands and deserts; Based on the spatial distribution and area of ​​the extracted ecological elements, monitor the forest and grass distribution, the temporal and spatial changes of annual forest and grass vegetation coverage, water body distribution, farmland crop growth, desertification status and desertification degree.

3. The smart ecological environment management method according to claim 2, characterized in that: The monitoring of ecological conditions according to the analysis and inversion results also includes the following steps: The ecological sensitivity includes soil erosion sensitivity and land desertification sensitivity; Adopt the basic principle of universal soil erosion equation, select parameter factors, calculate and analyze the sensitivity level and spatial distribution of soil erosion in the basin, and monitor the sensitivity of soil erosion in the basin in that year; Select factor indicators, calculate the sensitivity of land desertification in the watershed, use the spatial analysis of geographic information system to multiply the sensitivity impact distribution maps of each single factor, obtain the regional land desertification sensitivity level distribution map, and monitor the sensitivity of land desertification.

4. The smart ecological environment management method according to claim 1, characterized in that: The analysis and evaluation of the ecosystem pattern according to the analysis and inversion results specifically includes the following steps: Analyze and evaluate the index value and spatial distribution of desertified land area ratio and the index value and spatial distribution of water wetland area ratio in the current year; The landscape pattern analysis model was applied to analyze the landscape fragmentation index and landscape connectivity of the overall region and different functional zones in the year, and to quantify the connection between different patch types and landscape types in the landscape, and between patches of the same and different types.

5. The smart ecological environment management method according to claim 1, characterized in that: The analysis and evaluation of ecosystem quality according to the analysis and inversion results specifically includes the following steps: Combined with the forest and grassland coverage extraction results of the previous year, the forest and grassland coverage improvement rate index value is calculated to analyze the forest and grassland ecological quality of the year, and the vegetation index reflecting the photosynthetic effective radiation absorption of vegetation is used to invert the growth of farmland crops and reflect the ecological quality of farmland; The inversion model was applied to obtain the spatial distribution characteristics of chlorophyll a and suspended sediment, and a spatial distribution map was drawn to analyze the water quality of the basin that year; The inversion model was applied to obtain the spatial distribution characteristics of chemical oxygen demand, total nitrogen and total phosphorus, and a spatial distribution map was drawn to analyze the water quality of Wulansuhai Lake that year.

6. The smart ecological environment management method according to claim 1, characterized in that: The analysis and assessment of ecological stress based on the analysis and inversion results specifically includes the following steps: Classify the vegetation growth and obtain the vegetation growth grade distribution map for the year; By using the inversion model, the spatial distribution characteristics of grassland degradation and land desertification were obtained, and the spatial distribution maps were drawn respectively; The salinization sensitivity model was applied to perform spatial operations and obtain the salinization sensitivity level distribution map.

7. The smart ecological environment management method according to claims 1-6, characterized in that: The display of the image data, monitoring results, analysis and evaluation results specifically includes the following steps: After multi-year data fusion, the collected data, monitoring results, analysis and evaluation results are displayed through videos, graphics, reports and voice.

8. A smart ecological environment management system based on remote sensing data, characterized in that: It includes data acquisition module, data processing module, monitoring module, analysis module and display module; The data acquisition module is used to acquire image data of the ecosystem through remote sensing images; The data processing module is used to pre-process the image data, perform analysis and inversion using remote sensing algorithms, and perform image slicing; The monitoring module is used to monitor the ecological status according to the analysis and inversion results; The analysis module is used to analyze and evaluate the ecosystem pattern, ecosystem quality and ecological problem stress according to the analysis and inversion results; The display module is used to display the image data, monitoring results, analysis and evaluation results based on the image slices.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the intelligent ecological environment management method based on remote sensing data as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the intelligent ecological environment management method based on remote sensing data as described in any one of claims 1 to 7 are implemented.

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