CN110597932A - Environment comprehensive evaluation prediction method based on remote sensing image - Google Patents
Environment comprehensive evaluation prediction method based on remote sensing image Download PDFInfo
- Publication number
- CN110597932A CN110597932A CN201910601918.4A CN201910601918A CN110597932A CN 110597932 A CN110597932 A CN 110597932A CN 201910601918 A CN201910601918 A CN 201910601918A CN 110597932 A CN110597932 A CN 110597932A
- Authority
- CN
- China
- Prior art keywords
- environment
- simulation
- prediction model
- remote sensing
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Remote Sensing (AREA)
- Geometry (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- Computer Graphics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an environment comprehensive evaluation and prediction method based on remote sensing images, which comprises the steps of collecting satellite remote sensing images and environment data of a target area through a data information system and establishing a basic database; then obtaining parameters required for establishing an environment simulation prediction model according to a basic database; establishing an environment simulation prediction model based on the basic database and the parameters; simulating the time-space distribution of the pollutant concentration through an environment simulation prediction model; recently, big data analysis is carried out on the simulation result, ArcGIS and a webpage platform are imported, and real-time dynamic visual display of the simulation result is achieved. The invention can vividly and intuitively show the pollutant concentration distribution and the dynamic change condition thereof at different moments and different spatial positions; an image and visual expression platform is provided for emergency disposal, and emergency decision can be effectively assisted.
Description
Technical Field
The invention relates to the field of environmental prediction and evaluation, in particular to an environmental comprehensive evaluation and prediction method based on a remote sensing image.
Background
At present, the methods for comprehensively evaluating and predicting the environment (atmosphere, soil and underground water) mainly comprise a professional judgment method, an analog analysis method, a mathematical model method and a physical model method.
Among them, the professional judgment method can qualitatively judge the environmental influence of the atmosphere, the soil and the underground water. The method is generally used when the environmental influence problem is special, the environmental influence characteristics are difficult to accurately identify or the environmental influence can not be predicted by a common method.
The analogy analysis method belongs to qualitative or semi-quantitative prediction, and can be adopted when the evaluation time is short, enough data cannot be obtained, and the environmental influence cannot be predicted by using a mathematical model method or a physical model method.
Mathematical model methods general conditions mathematical model methods are simpler and more quantitative.
The physical model method can graphically reflect the pollution characteristics of a relatively complex ground environment and the physical process of pollutant migration, but a proper test site and conditions and necessary basic data are required, and the model is manufactured by more manpower, material resources and time.
Disclosure of Invention
The invention aims to provide an environment comprehensive evaluation and prediction method based on remote sensing images aiming at the defects in the prior art, which adopts a method of combining physical and mathematical models to graphically and visually analyze the pollution condition of the comprehensive environment of atmosphere, soil and underground water so as to solve the problems in the prior art.
The technical problem solved by the invention can be realized by adopting the following technical scheme:
an environment comprehensive evaluation prediction method based on remote sensing images comprises the following steps:
1) acquiring a satellite remote sensing image and environmental data of a target area through a data information system, and establishing a basic database;
2) acquiring parameters required for establishing an environment simulation prediction model according to a basic database;
3) establishing an environment simulation prediction model based on the basic database and the parameters;
4) simulating the spatial-temporal distribution of pollutant concentration through an environment simulation prediction model;
5) and carrying out big data analysis on the simulation result and importing the simulation result into ArcGIS and a webpage platform to realize real-time dynamic visual display of the simulation result.
Further, the parameters required by the environment simulation prediction model in the step 2) include the spatial dimension of the model, the time scale described or used by the model, the load, source and sink of pollution, the range of simulation prediction, the variable and dynamic structure in the pollution flow and mixed transportation and model.
Further, the environment simulation prediction model established in the step 3) is used for completely simulating the process of diffusion of environmental pollutants from a source to air, soil and underground water and movement and migration of pollutants;
the environment simulation and prediction model comprises a pollution source module, an air diffusion module, a soil diffusion module and a groundwater diffusion module; the formula for the simulation is as follows:
the formula for the simulation is as follows:
wherein α is a contaminant; d is the integrated longitudinal dispersion coefficient; v is the rate of diffusion of the contaminants; λ is the attenuation coefficient; θ is the voidage; r is the barrier coefficient.
Further, the simulation process of the environment simulation prediction model in the step 4) is as follows:
4.1) the spatio-temporal distribution of contaminant concentrations includes contaminant concentrations at different times and at different locations;
4.2) identifying the concentration value of the pollutant by adopting the depth of the color, and dynamically displaying the diffusion and migration process of the pollutant at each moment;
4.3) reading point location data marked with time and concentration information in the analog computation output data file according to the time sequence to generate a pollution surface;
4.4) preparing a polluted surface into a map Element by using an ArcGIS platform;
4.5) adding Element sets to the map drawing and continuously refreshing the map.
Further, the input format and the output format of the environment simulation prediction model are adjusted in the step 5), so that the requirements of the environment simulation prediction model on connection with ArcGIS and a webpage platform are met, and real-time dynamic visual display of a simulation result is realized.
Compared with the prior art, the invention has the beneficial effects that:
and the pollutant concentration distribution and the dynamic change condition thereof at different moments and different spatial positions are vividly and intuitively displayed. An image and visual expression platform is provided for emergency disposal, and emergency decision can be effectively assisted.
Drawings
FIG. 1 is a schematic diagram of an environmental simulation prediction model according to the present invention.
Fig. 2 is a block diagram of a system for predicting and evaluating environmental pollution according to the present invention.
FIG. 3 is a flow chart of the application of the environmental comprehensive assessment prediction technique according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
The invention relates to a method for comprehensively evaluating and predicting environments (atmosphere, soil and underground water) based on remote sensing images, which comprises the following steps:
step 1: building a basic database;
in order to effectively judge the pollution level and the pollution time in time, basic data related to pollutants needs to be collected, which mainly comprises:
(1) the spatial dimension of the model;
(2) the time scale described (or used) by the model;
(3) the load, source and sink of pollution;
(4) simulating a predicted range;
(5) pollution flowing and mixed transportation;
(6) variables in the model and the kinetic structure.
Step 2: environmental simulation prediction model
The environment simulation prediction model can simulate the complete process of environmental pollutant from the source to the diffusion of air, soil and underground water and the movement and the migration of the pollutant. The program adopts modular structure combination, the model comprises a plurality of calculation modules (a pollution source module, an air diffusion module, a soil diffusion module and an underground water diffusion module), each module has different functions, and the modules can be used independently and jointly, are flexible, are convenient for processing the environmental pollution diffusion problem of multiple targets, and are particularly suitable for the pollutant leakage and water disaster prediction of large areas such as petroleum and natural gas. One or more modules can be selected for processing according to actual conditions. The environmental simulation predictive model may be used in the analytical design phase as well as in the decision management phase, as compared to other models. When the pollution transmission with complex conditions is simulated, the model disperses the drainage basin into a plurality of sub-drainage basins, and the sub-drainage basins are simulated one by one according to the surface properties of the sub-drainage basins, so that the problem of simulating the pollution drainage basin with multiple characteristics can be conveniently solved, and the foundation is laid for the application of the model in large regionalization. The method comprises the following specific steps:
(1) analyzing the long-term change trend time-space distribution characteristics of long-term meteorological data, precipitation and the like in the simulation area; and selecting meteorological data and precipitation data of four areas in the polluted area for analysis, and performing seasonal analysis and spatial variation analysis on the basis.
(2) Basic data preparation
The basic data preparation work includes: extracting the information of the underlying surface of the research area, generalizing the sub-drainage basin and integrating the model.
(3) Environment comprehensive simulation model establishment
On the basis of fully researching the pollution rule and the underlying surface characteristics in the pollution area, a comprehensive pollutant simulation model is established by adopting a method combining weather, hydrology and pollution dynamics. The model comprises four parts of atmospheric pollution, surface runoff generation, surface confluence and groundwater runoff transmission.
The earth surface runoff generating and converging subsystem is mainly used for simulating pollution sources and pollution diffusion of earth surface soil layers. The underground water transmission subsystem mainly simulates the specific process of pollution source and soil pollution, and calculates to a downstream or overflow point, thereby simulating the complete pollutant diffusion process.
The formula for the simulation is as follows:
wherein α is a contaminant; d is the integrated longitudinal dispersion coefficient; v is the rate of diffusion of the contaminants; λ is the attenuation coefficient; θ is the voidage; r is the barrier coefficient.
Step 3, simulation result display and visualization
The input and output formats of the comprehensive environment assessment and prediction model are adjusted, the requirements of the model on connection with ArcGIS and a webpage are met, and the visualization of an environment simulation result is realized by combining the secondary development of big data. And carrying out big data analysis on the simulation result data and importing the simulation result data into an ArcGIS or webpage platform, thereby realizing multidimensional visualization of pollution diffusion and vividly and intuitively displaying the pollutant concentration distribution and the dynamic change condition thereof at different moments and different spatial positions. An image and visual expression platform is provided for emergency disposal, and emergency decision can be effectively assisted.
The invention integrates a satellite remote sensing image and a model generated by three-dimensional modeling of pollutant diffusion into a platform, and then collects various data required by the model through the specific division of an environment simulation prediction model and sub-modules thereof, as shown in figure 1, the environment simulation prediction model and the sub-modules thereof are divided into: the device comprises a pollution source diffusion module, an air diffusion module, a soil diffusion module and a groundwater diffusion module. And finally, realizing three-dimensional dynamic simulation and three-dimensional visualization through a GIS platform and a webpage.
As shown in fig. 2, in order to embed the model generated by three-dimensional modeling of pollutant diffusion into the GIS integrated platform, a path for storing and managing a multi-user spatial database is opened, and data such as weather, soil, and land utilization required by the basic database are provided to the model system and the GIS integrated platform through a data processing interface. The comprehensive GIS platform has the basic functions of a GIS, and also has common functions of data organization, management and processing, data information query, simulation technology, disaster prediction, 4D simulation and the like.
Fig. 2 also shows the system structure of the environmental pollution prediction and evaluation in one embodiment, including various specific basic databases, environmental comprehensive prediction models, GIS information, and web page displays. The meteorological database collects meteorological hydrological data, and the soil foundation database and the land utilization database provide real-time and accurate data for the environmental simulation prediction model.
And the simulation prediction result is combined with GIS and big data analysis to carry out specific comprehensive prediction on the geological disasters of the water area.
FIG. 3 is a flow chart of the application of the environment comprehensive evaluation prediction technology. And transmitting the data and the simulation result collected by the data information system to information processing platforms such as a GIS and the like. If the data simulation calculation result needs early warning and forecasting, the result is forecasted to a mobile phone APP, a webpage and the like through the MAS early warning system.
The comprehensive environmental evaluation and prediction method provided by the invention establishes a reliable, rapid and sufficient-accuracy environmental simulation prediction and early warning system based on GIS comprehensive integration, provides reference for emergency handling of accidents by related departments, reduces economic and social losses caused by environmental accidents such as water pollution to the minimum extent, avoids national economic losses to the maximum extent, reduces unnecessary municipal investment, and realizes maximization of environmental and economic benefits.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (5)
1. A comprehensive environment evaluation and prediction method based on remote sensing images is characterized by comprising the following steps:
1) acquiring a satellite remote sensing image and environmental data of a target area through a data information system, and establishing a basic database;
2) acquiring parameters required for establishing an environment simulation prediction model according to a basic database;
3) establishing an environment simulation prediction model based on the basic database and the parameters;
4) simulating the spatial-temporal distribution of pollutant concentration through an environment simulation prediction model;
5) and carrying out big data analysis on the simulation result and importing the simulation result into ArcGIS and a webpage platform to realize real-time dynamic visual display of the simulation result.
2. The method for comprehensive environmental assessment and prediction based on remote sensing images as claimed in claim 1, wherein the parameters required by the environmental simulation prediction model in step 2) include spatial dimensions of the model, time scale described or used by the model, pollution load, source and sink, simulation prediction range, pollution flow and mixed transportation and variables and dynamic structures in the model.
3. The comprehensive environment assessment and prediction method based on remote sensing images as claimed in claim 1, wherein the environment simulation prediction model established in step 3) is used for completely simulating the process of environmental pollutant diffusion from source to air, soil, underground water and pollutant movement migration;
the environment simulation and prediction model comprises a pollution source module, an air diffusion module, a soil diffusion module and a groundwater diffusion module;
the formula for the simulation is as follows:
wherein α is a contaminant; d is the integrated longitudinal dispersion coefficient; v is the rate of diffusion of the contaminants; λ is the attenuation coefficient; θ is the voidage; r is the barrier coefficient.
4. The method for comprehensively evaluating and predicting the environment based on the remote sensing image according to claim 1 or 3, wherein the simulation process of the environment simulation prediction model in the step 4) is as follows:
4.1) the spatio-temporal distribution of contaminant concentrations includes contaminant concentrations at different times and at different locations;
4.2) identifying the concentration value of the pollutant by adopting the depth of the color, and dynamically displaying the diffusion and migration process of the pollutant at each moment;
4.3) reading point location data marked with time and concentration information in the analog computation output data file according to the time sequence to generate a pollution surface;
4.4) preparing a polluted surface into a map Element by using an ArcGIS platform;
4.5) adding Element sets to the map drawing and continuously refreshing the map.
5. The remote sensing image-based environment comprehensive evaluation and prediction method according to claim 1, wherein in the step 5), the input and output formats of the environment simulation prediction model are adjusted to meet the requirement of the environment simulation prediction model for connection with ArcGIS and a webpage platform, so that real-time dynamic visual display of a simulation result is realized.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910601918.4A CN110597932B (en) | 2019-07-05 | 2019-07-05 | Environment comprehensive evaluation prediction method based on remote sensing image |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910601918.4A CN110597932B (en) | 2019-07-05 | 2019-07-05 | Environment comprehensive evaluation prediction method based on remote sensing image |
Publications (2)
Publication Number | Publication Date |
---|---|
CN110597932A true CN110597932A (en) | 2019-12-20 |
CN110597932B CN110597932B (en) | 2022-03-11 |
Family
ID=68852665
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910601918.4A Active CN110597932B (en) | 2019-07-05 | 2019-07-05 | Environment comprehensive evaluation prediction method based on remote sensing image |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110597932B (en) |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111221806A (en) * | 2020-01-20 | 2020-06-02 | 南京大学(溧水)生态环境研究院 | Construction method of material circulation process simulation database |
CN112507048A (en) * | 2020-11-11 | 2021-03-16 | 中国地质调查局水文地质环境地质调查中心 | Polluted site water and soil environment multi-element one-stop management system |
CN112710623A (en) * | 2020-12-16 | 2021-04-27 | 重庆商勤科技有限公司 | Method and equipment for remotely sensing and monitoring diffusion range and concentration of toxic and harmful gas |
CN112884310A (en) * | 2021-02-04 | 2021-06-01 | 中山大学 | Computer-aided assessment method, system and device for pollutant diffusion rule |
CN113269382A (en) * | 2020-12-29 | 2021-08-17 | 生态环境部卫星环境应用中心 | Regional atmospheric environment quality assessment method based on satellite remote sensing |
CN117314705A (en) * | 2023-10-11 | 2023-12-29 | 青海省生态环境监测中心 | Environment comprehensive evaluation prediction method based on remote sensing image |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100131199A1 (en) * | 2008-11-21 | 2010-05-27 | Gary Severson | GPS navigation code system |
US20100223276A1 (en) * | 2007-03-27 | 2010-09-02 | Faleh Jassem Al-Shameri | Automated Generation of Metadata for Mining Image and Text Data |
CN101840431A (en) * | 2010-04-30 | 2010-09-22 | 中国科学院地理科学与资源研究所 | Calculating cost coding method of spatial analysis method in distributed environment |
CN102184487A (en) * | 2011-05-17 | 2011-09-14 | 华东师范大学 | Pollution source management system based on geographic information system (GIS) technology and one-dimensional water quality model and operation method thereof |
CN102708245A (en) * | 2012-05-09 | 2012-10-03 | 浙江大学 | Sudden water pollution accident analog simulation and visualization service system |
CN104516950A (en) * | 2014-12-10 | 2015-04-15 | 百度在线网络技术(北京)有限公司 | Inquiring method and device of interest points |
CN104636629A (en) * | 2015-03-05 | 2015-05-20 | 香港中文大学深圳研究院 | Method and device for analyzing emergent water quality pollution event |
CN105550799A (en) * | 2015-12-07 | 2016-05-04 | 南通大学 | Drainage basin transboundary region water environment risk reduction technology system |
CN106990128A (en) * | 2017-04-05 | 2017-07-28 | 北京矿冶研究总院 | Plaque image and pollution characteristic coupling method in regional tailing pond environmental risk assessment |
CN107145848A (en) * | 2017-04-27 | 2017-09-08 | 中国科学院遥感与数字地球研究所 | A kind of wind erosion of soil monitoring method and system based on remotely-sensed data |
CN108038351A (en) * | 2017-12-06 | 2018-05-15 | 武汉大学 | A kind of chlorophyll computational methods based on remote sensing image and water ecological model |
CN109815419A (en) * | 2019-02-22 | 2019-05-28 | 北京三快在线科技有限公司 | Point of interest indexing means, device, medium and electronic equipment based on geographical location |
-
2019
- 2019-07-05 CN CN201910601918.4A patent/CN110597932B/en active Active
Patent Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100223276A1 (en) * | 2007-03-27 | 2010-09-02 | Faleh Jassem Al-Shameri | Automated Generation of Metadata for Mining Image and Text Data |
US20100131199A1 (en) * | 2008-11-21 | 2010-05-27 | Gary Severson | GPS navigation code system |
CN101840431A (en) * | 2010-04-30 | 2010-09-22 | 中国科学院地理科学与资源研究所 | Calculating cost coding method of spatial analysis method in distributed environment |
CN102184487A (en) * | 2011-05-17 | 2011-09-14 | 华东师范大学 | Pollution source management system based on geographic information system (GIS) technology and one-dimensional water quality model and operation method thereof |
CN102708245A (en) * | 2012-05-09 | 2012-10-03 | 浙江大学 | Sudden water pollution accident analog simulation and visualization service system |
CN104516950A (en) * | 2014-12-10 | 2015-04-15 | 百度在线网络技术(北京)有限公司 | Inquiring method and device of interest points |
CN104636629A (en) * | 2015-03-05 | 2015-05-20 | 香港中文大学深圳研究院 | Method and device for analyzing emergent water quality pollution event |
CN105550799A (en) * | 2015-12-07 | 2016-05-04 | 南通大学 | Drainage basin transboundary region water environment risk reduction technology system |
CN106990128A (en) * | 2017-04-05 | 2017-07-28 | 北京矿冶研究总院 | Plaque image and pollution characteristic coupling method in regional tailing pond environmental risk assessment |
CN107145848A (en) * | 2017-04-27 | 2017-09-08 | 中国科学院遥感与数字地球研究所 | A kind of wind erosion of soil monitoring method and system based on remotely-sensed data |
CN108038351A (en) * | 2017-12-06 | 2018-05-15 | 武汉大学 | A kind of chlorophyll computational methods based on remote sensing image and water ecological model |
CN109815419A (en) * | 2019-02-22 | 2019-05-28 | 北京三快在线科技有限公司 | Point of interest indexing means, device, medium and electronic equipment based on geographical location |
Non-Patent Citations (5)
Title |
---|
LIBAO ZHANG: "Global and Local Saliency Analysis for the Extraction of Residential Areas in High-Spatial-Resolution Remote Sensing Image", 《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 》 * |
刘婷婷等: "流域水环境监测管理***设计与应用――以云南松华坝流域为例", 《国土资源信息化》 * |
石亚男等: "绿洲生态环境动态调控模型及***概念设计应用", 《地球信息科学》 * |
赵少华: "中国城镇生态环境遥感监测现状及发展趋势", 《生态环境学报》 * |
郑丰: "环境应急信息管理平台", 《污染防治技术》 * |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111221806A (en) * | 2020-01-20 | 2020-06-02 | 南京大学(溧水)生态环境研究院 | Construction method of material circulation process simulation database |
CN111221806B (en) * | 2020-01-20 | 2024-04-16 | 南京大学(溧水)生态环境研究院 | Construction method of substance circulation process simulation database |
CN112507048A (en) * | 2020-11-11 | 2021-03-16 | 中国地质调查局水文地质环境地质调查中心 | Polluted site water and soil environment multi-element one-stop management system |
CN112710623A (en) * | 2020-12-16 | 2021-04-27 | 重庆商勤科技有限公司 | Method and equipment for remotely sensing and monitoring diffusion range and concentration of toxic and harmful gas |
CN113269382A (en) * | 2020-12-29 | 2021-08-17 | 生态环境部卫星环境应用中心 | Regional atmospheric environment quality assessment method based on satellite remote sensing |
CN113269382B (en) * | 2020-12-29 | 2022-09-20 | 生态环境部卫星环境应用中心 | Regional atmospheric environment quality assessment method based on satellite remote sensing |
CN112884310A (en) * | 2021-02-04 | 2021-06-01 | 中山大学 | Computer-aided assessment method, system and device for pollutant diffusion rule |
CN117314705A (en) * | 2023-10-11 | 2023-12-29 | 青海省生态环境监测中心 | Environment comprehensive evaluation prediction method based on remote sensing image |
CN117314705B (en) * | 2023-10-11 | 2024-04-16 | 青海省生态环境监测中心 | Environment comprehensive evaluation prediction method based on remote sensing image |
Also Published As
Publication number | Publication date |
---|---|
CN110597932B (en) | 2022-03-11 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN110597932B (en) | Environment comprehensive evaluation prediction method based on remote sensing image | |
Chen | Visualization of real-time monitoring datagraphic of urban environmental quality | |
CN109242291A (en) | River and lake basin water environment wisdom management method | |
CN112507048B (en) | Polluted site water and soil environment multi-element one-stop management system | |
Martin et al. | Development of a GIS-based spill management information system | |
CN114443982A (en) | Large-area soil heavy metal detection and space-time distribution characteristic analysis method and system | |
CN112819340A (en) | Urban flood disaster dynamic evaluation method based on multi-source data | |
CN116362113B (en) | Accident disaster evolution simulation method and system based on digital twinning | |
Vitali et al. | A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station | |
Zhao et al. | Groundwater contamination risk assessment based on intrinsic vulnerability, pollution source assessment, and groundwater function zoning | |
Yasarer et al. | Characterizing ponds in a watershed simulation and evaluating their influence on streamflow in a Mississippi watershed | |
CN113887974A (en) | Urban resource environment bearing capacity comprehensive evaluation method based on multi-source time-space data integration | |
Prueksakorn et al. | Applications of WRF/CALPUFF modeling system and multi-monitoring methods to investigate the effect of seasonal variations on odor dispersion: a case study of Changwon City, South Korea | |
Xu et al. | Permeability control and flood risk assessment of urban underlying surface: a case study of Runcheng south area, Kunming | |
Ren et al. | Analysis of the spatial characteristics of inhalable particulate matter concentrations under the influence of a three-dimensional landscape pattern in Xi'an, China | |
CN114154300B (en) | Urban thermal environment and air pollutant concentration real-time sensing map building method | |
Ramsankaran et al. | Physically-based distributed soil erosion and sediment yield model (DREAM) for simulating individual storm events | |
Elhassan et al. | Water quality modelling in the San Antonio River Basin driven by radar rainfall data | |
KR101594148B1 (en) | Visulalization and analysis system of input/output data using efdc model | |
Wang et al. | The architecture and application of an automatic operational model system for basin scale water environment management and design making supporting | |
Saleh et al. | An integrated weather–hydrologic–coastal–stormwater framework to model urban‐coastal interactions: City of Hoboken application | |
Zollweg | Effective use of geographic information systems for rainfall-runoff modeling | |
Chen | RETRACTED ARTICLE: Plant planning and urban construction of sponge city based on GIS system | |
Zhu | Application of SWMM model and image recognition in virtual simulation of urban architectural landscape | |
Dotson | Watershed modeling with HEC-HMS (hydrologic engineering centers-hydrologic modeling system) using spatially distributed rainfall |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |