Urban environment detection and comprehensive evaluation method based on remote sensing data
Technical Field
The invention relates to the technical field of urban environment detection, in particular to a method for urban environment detection and comprehensive evaluation based on remote sensing data.
Background
The remote sensing technology is a comprehensive technology for detecting and identifying various scenes on the ground by collecting, processing and finally imaging electromagnetic wave information radiated and reflected by a remote target by using various sensing instruments according to the theory of electromagnetic waves. The remote sensing can be applied to the field of urban environment detection, and the urban environment detection can monitor the quality of urban atmosphere, water body, soil, biology and the like, noise, electromagnetic waves, radioactivity and the like, and determine pollution sources, influence ranges, approaches and harm thereof; periodically observing urban pollution sources, grasping the dynamic change of pollution, and searching and analyzing the reasons.
The existing urban environment detection and comprehensive evaluation method is not comprehensive enough in detection surface during urban environment detection, adopts a targeted sensor detection mode to perform single detection evaluation on air quality or water body, and does not detect and predict corresponding time sequence changes of the environment.
In view of the above, an urban environment detection and comprehensive evaluation method based on remote sensing data is proposed by researching and improving the existing structure and deficiency.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a city environment detection and comprehensive evaluation method based on remote sensing data, which solves the problems in the prior art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the utility model provides a city environment detects and comprehensive evaluation method based on remote sensing data, includes remote sensing platform, data processing unit and environment judgement unit, remote sensing platform's output is connected with cloud ware, and the output of cloud ware is connected with environment detection center, data processing unit electric connection is in environment detection center's output, and data processing unit includes remote sensing data acquisition module, remote sensing image analysis processing module, remote sensing ground object discernment classification module, environment detection data extraction module and data classification storage module, remote sensing data acquisition module's output electric connection has remote sensing image analysis processing module, and remote sensing image analysis processing module's output electric connection has remote sensing ground object discernment classification module, remote sensing ground object discernment classification module's output electric connection has environment detection data extraction module, and environment judgement unit electric connection is in data processing unit's output, and environment judgement unit's output electric connection has unusual alarm module, environment judgement unit includes environment evaluation module and environment prediction module.
Further, the environment detection center comprises an atmospheric environment detection unit, a vegetation environment detection unit and a water body environment detection unit, the atmospheric environment detection unit, the vegetation environment detection unit and the water body environment detection unit are connected in parallel, and the atmospheric environment detection unit, the vegetation environment detection unit and the water body environment detection unit are respectively used for detecting the atmospheric environment, the vegetation environment and the water body environment in the urban environment.
Furthermore, the remote sensing data acquisition module is used for collecting and sorting remote sensing data in different periods according to a time sequence relation, then converting digital remote sensing data into a spatial resolution image, the remote sensing image analysis processing module is used for carrying out analysis processing on the remote sensing image, the analysis processing process comprises line radiation correction, gray level image conversion and smooth filtering processing, then closing operation in mathematical morphology is adopted to fill gaps of the outline, and the image outline is integrated, so that a clearer and complete remote sensing image is obtained.
Furthermore, the remote sensing ground object recognition and classification module is used for performing ground object classification detection on the images, extracting urban water body according to ground object reflection wave characteristics, extracting urban vegetation in a normalized differential vegetation index mode, and then performing semi-quantitative estimation on the condition of atmospheric pollutants by adopting a multispectral treatment system to realize detection of atmospheric environment, vegetation environment and water body environment.
Furthermore, the environment detection data extraction module is used for extracting urban water body data, urban vegetation data and urban atmospheric pollutant data on the basis of remote sensing ground object identification and classification, and the data classification storage module is used for classifying and storing the extracted data into a remote sensing database on an environment detection center.
Furthermore, the environment evaluation module comprises a current environment evaluation module, a comparison detection evaluation module and an evaluation result output module, and the output ends of the current environment evaluation module and the comparison detection evaluation module are electrically connected with the evaluation result output module.
Furthermore, the environment evaluation module is used for detecting and evaluating the current urban environment data, the comparison detection evaluation module is used for detecting and evaluating the change condition of the urban environment according to the time sequence relation, and the evaluation result output module is used for outputting an evaluation result and grading the urban environment condition according to the urban environment detection result.
Further, the environment prediction module comprises a data collection module, an environment model training module, an environment model verification module and an environment prediction output module, wherein the output end of the data collection module is electrically connected with the environment model training module, the output end of the environment model training module is electrically connected with the environment model verification module, and the output end of the environment model verification module is electrically connected with the environment prediction output module.
Further, the current environment evaluation module comprises an environment evaluation model construction module, an evaluation data substitution module, an evaluation result calculation module and a visual analysis module, wherein the output end of the environment evaluation model construction module is electrically connected with the evaluation data substitution module, the output end of the evaluation data substitution module is electrically connected with the evaluation result calculation module, and the output end of the evaluation result calculation module is electrically connected with the visual analysis module.
Further, the comparison detection evaluation module comprises a change feature extraction module, an image registration detection module, a time sequence distribution drawing module and a data structure analysis module, wherein the output end of the change feature extraction module is electrically connected with the image registration detection module, the output end of the image registration detection module is electrically connected with the time sequence distribution drawing module, and the output end of the time sequence distribution drawing module is electrically connected with the data structure analysis module.
The invention provides a city environment detection and comprehensive evaluation method based on remote sensing data, which has the following beneficial effects:
the urban environment detection and comprehensive evaluation method based on the remote sensing data can detect the atmospheric environment, vegetation environment and water environment of the urban environment, draw the environmental pollution condition time sequence distribution diagram of the urban according to the time sequence relationship while detecting the urban environment so as to reflect the change condition of the urban environment, and predict the environment according to the environment detection data so as to carry out pollution treatment on the environment in time.
1. The urban environment detection and comprehensive evaluation method based on the remote sensing data is provided with a data processing unit, a remote sensing data acquisition module collects and sorts the remote sensing data in different periods according to a time sequence relation, then digital remote sensing data are converted into a spatial resolution image, a remote sensing image analysis processing module analyzes and processes the remote sensing image, an analysis processing process comprises line radiation correction, gray level image conversion and smooth filtering processing, then a closed operation in mathematical morphology is adopted to fill gaps of an outline, and the outline of the image is integrated, so that a clearer and complete remote sensing image is obtained; the remote sensing ground object recognition and classification module performs ground object classification detection on the images, extracts urban water bodies according to ground object reflection wave characteristics, extracts urban vegetation in a mode of normalizing differential vegetation indexes, then performs semi-quantitative estimation on the conditions of atmospheric pollutants by adopting the multispectral processing system, and extracts urban water body data, urban vegetation data and urban atmospheric pollutant data on the basis of remote sensing ground object recognition and classification, wherein the data classification storage module stores the extracted data in a remote sensing database on an environment detection center in a classified manner.
2. The urban environment detection and comprehensive evaluation method based on the remote sensing data is provided with an environment detection center, an atmospheric environment detection unit, a vegetation environment detection unit and a water environment detection unit are used for respectively detecting the atmospheric environment, the vegetation environment and the water environment in the urban environment, an abnormal alarm module can be used for timely alarming when the environment judgment unit detects and predicts abnormal environment data or environmental pollution so as to timely maintain the urban environment, an environment evaluation module is used for detecting and evaluating the current urban environment data, a comparison detection evaluation module is used for detecting and evaluating the change condition of the urban environment according to a time sequence relation, and an evaluation result output module is used for outputting an evaluation result and grading the urban environment condition according to the urban environment detection result.
3. The city environment detection and comprehensive evaluation method based on the remote sensing data is provided with a current environment evaluation module, an environment evaluation model construction module can respectively construct environment evaluation models of atmospheric environment detection, vegetation environment detection and water environment detection, different weights are respectively given to different detection factors, an evaluation data substitution module can extract effective data in a remote sensing database of an environment detection center and substitute the effective data into the environment evaluation model, an evaluation result calculation module can output an evaluation result of the environment evaluation model, and a visual analysis module can display the environment evaluation result in a visual chart form.
4. The urban environment detection and comprehensive evaluation method based on the remote sensing data is provided with a comparison detection evaluation module, a change feature extraction module can extract time change features of the ground object environment from the remote sensing image according to the time change features, an image registration detection module can obtain corresponding image space coordinate transformation parameters through matched feature point pairs to determine an environment change land block, a time sequence distribution diagram drawing module can draw an urban environment pollution condition time sequence distribution diagram according to a time sequence relation so as to reflect urban environment change conditions, and a data structure analysis module can analyze the urban environment change data and express the data in a previous structured form so as to realize high logic of the data.
5. The city environment detection and comprehensive evaluation method based on the remote sensing data is provided with an environment prediction module, a data collection module can collect effective data in a remote sensing database of an environment detection center, an environment model training module can train according to historical remote sensing data, wherein a machine learning method of model training comprises, but is not limited to, KNN, decision trees, logistic regression, support vector machines, neural networks and deep neural networks, model training is continuously carried out after an optimal algorithm is selected, an environment model verification module can verify training results of the environment model training module according to actual environment development conditions until output result errors meet requirements, and further a prediction model is continuously perfected, so that a final environment prediction output module can output predicted environment data results according to current environment data, and environment development is predicted.
Drawings
FIG. 1 is a schematic diagram of a system flow of a city environment detection and comprehensive evaluation method based on remote sensing data;
FIG. 2 is a schematic diagram of a data processing unit structure of a city environment detection and comprehensive evaluation method based on remote sensing data according to the present invention;
FIG. 3 is a schematic diagram of an environment determination unit of the urban environment detection and comprehensive evaluation method based on remote sensing data;
FIG. 4 is a schematic view of an environmental assessment module structure of a city environmental detection and comprehensive assessment method based on remote sensing data according to the present invention;
fig. 5 is a schematic diagram of an environment prediction module structure of a city environment detection and comprehensive evaluation method based on remote sensing data.
In the figure: 1. a remote sensing platform; 2. a cloud server; 3. an environment detection center; 301. an atmospheric environment detection unit; 302. a vegetation environment detection unit; 303. a water environment detection unit; 4. a data processing unit; 401. the remote sensing data acquisition module; 402. the remote sensing image analysis processing module; 403. the remote sensing ground object identification and classification module; 404. an environment detection data extraction module; 405. a data classification storage module; 5. an environment determination unit; 6. an anomaly alarm module; 7. an environmental assessment module; 8. an environment prediction module; 801. a data collection module; 802. an environmental model training module; 803. an environmental model verification module; 804. an environment prediction output module; 9. a current environment assessment module; 901. an environmental assessment model construction module; 902. substituting the evaluation data into the module; 903. an evaluation result calculation module; 904. a visual analysis module; 10. a contrast detection evaluation module; 1001. a change feature extraction module; 1002. an image registration detection module; 1003. a time sequence distribution diagram drawing module; 1004. a data structured analysis module; 11. and the evaluation result output module.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings and examples. The following examples are illustrative of the invention but are not intended to limit the scope of the invention.
Referring to fig. 1 to 5, the present invention provides the following technical solutions: the urban environment detection and comprehensive evaluation method based on remote sensing data comprises a remote sensing platform 1, a data processing unit 4 and an environment judging unit 5, wherein the output end of the remote sensing platform 1 is connected with a cloud server 2, the output end of the cloud server 2 is connected with an environment detection center 3, the data processing unit 4 is electrically connected with the output end of the environment detection center 3, the data processing unit 4 comprises a remote sensing data acquisition module 401, a remote sensing image analysis processing module 402, a remote sensing ground object identification and classification module 403, an environment detection data extraction module 404 and a data classification storage module 405, the output end of the remote sensing data acquisition module 401 is electrically connected with the remote sensing image analysis processing module 402, the output end of the remote sensing image analysis processing module 402 is electrically connected with the remote sensing ground object identification and classification module 403, the output end of the remote sensing ground object identification and classification module 403 is electrically connected with the environment detection data extraction module 404, and the output end of the environment detection data extraction module 404 is electrically connected with the data classification storage module 405;
the specific operation is that the remote sensing data acquisition module 401 collects and sorts the remote sensing data of different periods according to the time sequence relationship, then converts the digital remote sensing data into a spatial resolution image, the remote sensing image analysis processing module 402 analyzes and processes the remote sensing image, the analysis processing process comprises line radiation correction, gray level image conversion and smooth filtering processing, then the gap of the outline is filled by adopting the closing operation in mathematical morphology, and the image outline is integrated, so that a clearer and complete remote sensing image is obtained; the remote sensing ground object recognition and classification module 403 performs ground object classification detection on the images, extracts urban water body according to the ground object reflection wave characteristics, extracts urban vegetation in a normalized differential vegetation index mode, then performs semi-quantitative estimation on the condition of atmospheric pollutants by adopting a multispectral processing system, and the environment detection data extraction module 404 extracts urban water body data, urban vegetation data and urban atmospheric pollutant data on the basis of remote sensing ground object recognition and classification, wherein the data comprises data such as ground surface temperature and humidity data, ph value, smoke concentration, vegetation coverage rate, water temperature and water level and the like, and the data classification storage module 405 stores the extracted data in a remote sensing database on the environment detection center 3 in a classified manner.
Referring to fig. 1, the environment detection center 3 includes an atmospheric environment detection unit 301, a vegetation environment detection unit 302, and a water environment detection unit 303, where the atmospheric environment detection unit 301, the vegetation environment detection unit 302, and the water environment detection unit 303 are connected in parallel, and the atmospheric environment detection unit 301, the vegetation environment detection unit 302, and the water environment detection unit 303 detect the atmospheric environment, the vegetation environment, and the water environment in the urban environment, respectively.
Referring to fig. 1, 3 and 4, the environment determining unit 5 is electrically connected to an output end of the data processing unit 4, and an abnormal alarm module 6 is electrically connected to an output end of the environment determining unit 5, the environment determining unit 5 includes an environment evaluating module 7 and an environment predicting module 8, the environment evaluating module 7 includes a current environment evaluating module 9, a comparison detecting evaluating module 10 and an evaluation result output module 11, and output ends of the current environment evaluating module 9 and the comparison detecting evaluating module 10 are electrically connected to the evaluation result output module 11;
the method specifically comprises the following steps that the abnormal alarm module 6 can alarm in time when the environment judging unit 5 detects and predicts abnormal environment data or environment pollution so as to maintain the urban environment in time, the environment evaluation module 7 detects and evaluates the current urban environment data, the comparison detection evaluation module 10 detects and evaluates the change condition of the urban environment according to a time sequence relation, and the evaluation result output module 11 outputs an evaluation result and ranks the urban environment condition according to the urban environment detection result.
Referring to fig. 5, the environment prediction module 8 includes a data collection module 801, an environment model training module 802, an environment model verification module 803 and an environment prediction output module 804, wherein an output end of the data collection module 801 is electrically connected with the environment model training module 802, an output end of the environment model training module 802 is electrically connected with the environment model verification module 803, and an output end of the environment model verification module 803 is electrically connected with the environment prediction output module 804;
the specific operation is that the data collection module 801 can collect valid data in a remote sensing database of the environment detection center 3, the environment model training module 802 can train according to historical remote sensing data, where a machine learning method of model training includes, but is not limited to KNN, decision tree, logistic regression, support vector machine, neural network, deep neural network, and after selecting an optimal algorithm, model training is continuously performed, the environment model verification module 803 can verify a training result of the environment model training module 802 according to an actual environment development condition until an output result error meets a requirement, and further, a prediction model is continuously perfected, so that the final environment prediction output module 804 can output a predicted environment data result according to current environment data, and predict environment development.
Referring to fig. 4, the current environment evaluation module 9 includes an environment evaluation model building module 901, an evaluation data substitution module 902, an evaluation result calculation module 903 and a visual analysis module 904, wherein the output end of the environment evaluation model building module 901 is electrically connected with the evaluation data substitution module 902, the output end of the evaluation data substitution module 902 is electrically connected with the evaluation result calculation module 903, and the output end of the evaluation result calculation module 903 is electrically connected with the visual analysis module 904;
the specific operation is that the environmental assessment model construction module 901 can respectively construct environmental assessment models of atmospheric environmental detection, vegetation environmental detection and water environmental detection, and respectively assign different weights to different detection factors, the evaluation data substitution module 902 can extract and substitute the effective data in the remote sensing database of the environmental detection center 3 into the environmental assessment model, the evaluation result calculation module 903 can output the evaluation result of the environmental assessment model, and the visual analysis module 904 can display the environmental evaluation result in the form of a visual chart.
Referring to fig. 4, the contrast detection evaluation module 10 includes a change feature extraction module 1001, an image registration detection module 1002, a timing distribution diagram drawing module 1003, and a data structure analysis module 1004, wherein an output end of the change feature extraction module 1001 is electrically connected with the image registration detection module 1002, an output end of the image registration detection module 1002 is electrically connected with the timing distribution diagram drawing module 1003, and an output end of the timing distribution diagram drawing module 1003 is electrically connected with the data structure analysis module 1004;
the specific operation is that the change feature extraction module 1001 can extract the time change feature of the ground object environment from the remote sensing image according to the time change feature, the image registration detection module 1002 can obtain the corresponding image space coordinate transformation parameter through the matched feature point pair, determine the environment change land block, the time sequence distribution diagram drawing module 1003 can draw the time sequence distribution diagram of the environmental pollution condition of the city according to the time sequence relationship so as to reflect the city environment change condition, the data structure analysis module 1004 can analyze and express the city environment change data in the form of the previous structure, and the high logic of the data is realized.
In summary, when the urban environment detection and comprehensive evaluation method based on remote sensing data is used, firstly, the remote sensing platform 1 uploads the urban remote sensing data to the cloud server 2, then the environment detection center 3 downloads the remote sensing data of the cloud server 2, so that the atmospheric environment detection unit 301, the vegetation environment detection unit 302 and the water environment detection unit 303 respectively detect the atmospheric environment, the vegetation environment and the water environment in the urban environment, and the data are processed through the data processing unit 4 during detection, in the process, the remote sensing data acquisition module 401 collects and sorts the remote sensing data in different periods according to a time sequence relation, then converts the digital remote sensing data into a spatial resolution image, the remote sensing image analysis processing module 402 analyzes and processes the remote sensing image, the analysis processing process comprises line radiation correction, gray level image conversion and smooth filtering processing, and then the gap of the outline is filled by adopting a closing operation in mathematical morphology, and the image outline is integrated, so that a relatively clear and complete remote sensing image is obtained. The remote sensing ground object recognition and classification module 403 performs ground object classification detection on the images, extracts urban water body according to ground object reflection wave characteristics, extracts urban vegetation in a mode of normalizing differential vegetation indexes, then performs semi-quantitative estimation on the condition of atmospheric pollutants by adopting a multispectral processing system, and the environment detection data extraction module 404 extracts urban water body data, urban vegetation data and urban atmospheric pollutant data on the basis of remote sensing ground object recognition and classification, wherein the data comprises data such as ground surface temperature and humidity data, ph value, smoke concentration, vegetation coverage rate, water temperature and water level and the like, and finally the data classification storage module 405 classifies and stores the extracted data into a remote sensing database on the environment detection center 3;
then the environment judging unit 5 carries out evaluation detection and prediction on the urban environment according to remote sensing data, in the process, the current environment evaluating module 9 carries out detection evaluation on the current environment condition, the environment evaluating model constructing module 901 can respectively construct environment evaluating models of atmospheric environment detection, vegetation environment detection and water environment detection during detection, different weights are respectively given to different detection factors, then the evaluating data substitution module 902 can extract the effective data in the remote sensing database of the environment detecting center 3 and substitute the effective data into the environment evaluating model, the evaluating result calculating module 903 can output the evaluating result of the environment evaluating model, and the visual analysis module 904 can display the environment evaluating result in the form of a visual chart;
then the comparison detection evaluation module 10 performs detection evaluation on the urban environment according to the time sequence relation, at this time, the change feature extraction module 1001 can extract the time change feature of the ground object environment from the remote sensing image according to the time change feature, then the image registration detection module 1002 can obtain corresponding image space coordinate transformation parameters through the matched feature point pairs, determine the environment change land block, then the time sequence distribution diagram drawing module 1003 can draw the time sequence distribution diagram of the urban environment pollution condition according to the time sequence relation so as to reflect the urban environment change condition, finally the data structuring analysis module 1004 can analyze and express the urban environment change data in the form of previous structuring so as to realize the high logic of the data, and the final evaluation result output module 11 outputs the evaluation result and ranks the urban environment condition according to the urban environment detection result;
the environment prediction module 8 predicts the urban environment development condition according to the historical data, the data collection module 801 can collect the effective data in the remote sensing database of the environment detection center 3, the environment model training module 802 can train according to the historical remote sensing data, the machine learning method of model training comprises, but is not limited to, KNN, decision tree, logistic regression, support vector machine, neural network and deep neural network, the model training is continuously performed after the optimal algorithm is selected, the environment model verification module 803 can verify the training result of the environment model training module 802 according to the actual environment development condition until the output result error meets the requirement, the prediction model is continuously perfected, the final environment prediction output module 804 can output the predicted environment data result according to the current environment data, the environment development is predicted, and the abnormal alarm module 6 can timely alarm when the abnormal environment data or the environment pollution is detected and predicted, so that the urban environment is timely maintained, and the whole urban environment detection and comprehensive evaluation method based on the remote sensing data is completed.
The embodiments of the invention have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.