NL2032387B1 - A regional ecosystem vulnerability remote sensing assessment system - Google Patents
A regional ecosystem vulnerability remote sensing assessment system Download PDFInfo
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- NL2032387B1 NL2032387B1 NL2032387A NL2032387A NL2032387B1 NL 2032387 B1 NL2032387 B1 NL 2032387B1 NL 2032387 A NL2032387 A NL 2032387A NL 2032387 A NL2032387 A NL 2032387A NL 2032387 B1 NL2032387 B1 NL 2032387B1
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- 238000005070 sampling Methods 0.000 claims abstract description 31
- 238000012360 testing method Methods 0.000 claims abstract description 30
- 238000011084 recovery Methods 0.000 claims abstract description 29
- 238000005192 partition Methods 0.000 claims abstract description 26
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 16
- 239000002689 soil Substances 0.000 claims description 15
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 6
- 229910052698 phosphorus Inorganic materials 0.000 claims description 6
- 239000011574 phosphorus Substances 0.000 claims description 6
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 5
- 229910052717 sulfur Inorganic materials 0.000 claims description 5
- 239000011593 sulfur Substances 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 4
- 239000002253 acid Substances 0.000 claims description 3
- 239000012670 alkaline solution Substances 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 241000282414 Homo sapiens Species 0.000 description 5
- 238000011160 research Methods 0.000 description 5
- 239000000243 solution Substances 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 230000006355 external stress Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 230000004083 survival effect Effects 0.000 description 2
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 1
- 229910019142 PO4 Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011157 data evaluation Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- NBIIXXVUZAFLBC-UHFFFAOYSA-K phosphate Chemical compound [O-]P([O-])([O-])=O NBIIXXVUZAFLBC-UHFFFAOYSA-K 0.000 description 1
- 239000010452 phosphate Substances 0.000 description 1
- 238000000746 purification Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000010792 warming Methods 0.000 description 1
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- 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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
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Abstract
The present invention provides a regional ecosystem vulnerability remote sensing assessment system, including a regional partition module, a data sampling module, an external pressure test module, a data recovery module and 5 a timing module, the regional partition module transmits partition data to a data sampling module, and the data The sampling module transmits the sampling data to the external pressure test module, the external pressure test module transmits the data to the data recovery module, and both the data recovery module and the external pressure test module transmit the data to the timely module. By setting 10 up a data sampling module, an external pressure test module, a data recovery module and a timing module, it is convenient to simulate the impact of external pressure on the regional ecological environment, and to record and grade these impacts, so as to increase the work efficiency of collecting ecological environment vulnerability data and reduce the workload of staff.
Description
A regional ecosystem vulnerability remote sensing assessment system
The invention relates to the field of regional ecosystems, in particular to a method and system for remote sensing assessment of the vulnerability of regional ecosystems.
Ecosystem is one of the most basic components that constitute the terrestrial ecosystem, and it is an important guarantee for maintaining sustainable social and economic development. Since the 20th century, climate warming has been increasing, and the global climate and environment have undergone great changes. The loss of species diversity, the frequent occurrence of extreme weather events, the intensification of desertification, and the melting of polar glaciers are all strong feedback on ecosystem changes. A major threat to the survival of human beings and the sustainable development of society and economy. However, under the dual coercion of human activities and climate change, population, resource and environmental issues have increasingly become issues that need to be solved urgently affecting human survival. The rapid expansion of the population and the unreasonable development and utilization of resources have caused the ecosystem's own resilience and self-purification ability to decline continuously, and the human living environment has become more and more fragile. The research on "fragile ecological environment" and "ecosystem fragility" has attracted extensive attention of scholars at home and abroad.Research in the field of ecosystem vulnerability has been recognized as important research hot issues. by the International Biology Programme (IBP) (1960s), the Man and Biosphere Programme (MAB) (1970s), and the Geosphere,
Biosphere Programme (GBP) (1980s). As an important analytical tool in the field of global ecological environment change and ecosystem sustainability science, ecosystem vulnerability research has been put on the research agenda by many international scientific institutions (IHDP, IPCC, IGBP, etc.), and it has become the focus of attention in the field of global ecological environment change.
When assessing the vulnerability of the ecological environment, it is necessary to collect a large number of data in the area, among which the evaluation of environmental sensitivity and resilience requires a long time and area to collect data, which increases the overall workload of collecting data.
Aiming at the deficiencies of the prior art, the present invention provides a remote sensing assessment method and system for regional ecosystem vulnerability, which solves the problem that collecting ecological environment vulnerability data consumes a long time and increases people's workload.
To achieve the above purpose, the present invention is achieved through the following technical solutions:Regional Ecosystem Vulnerability Remote Sensing
Assessment System, including regional partition module, data sampling module, external pressure test module, data recovery module and timing module, the area partitioning module transmits the partition data to the data sampling module, the data sampling module transmits the sampling data to the external pressure test module, the external pressure test module transmits the data to the data recovery module, and the data recovery module is connected to the data recovery module.
The external stress test module transmits data to the timely module;
The area partition module is used to perform a partition operation on the area;
The data sampling module is used for sampling the data in one of the regions in the partition;
The external pressure test module is used to perform a corresponding pressure interference test on the sampled data;
The data recovery data is used to change the changed data into a normal value;
The timing module is used to collect time parameters consumed in the external pressure testing module and the data recovery module.
Preferably, the data sampling module adopts the CR algorithm to perform random sampling.
Preferably, the data sampling module respectively picks up four groups of data of water quality, soil, vegetation and air quality in the area.
Preferably, the external pressure test module applies external interference to four sets of data of water quality, soil, vegetation and air quality, respectively, adding phosphorus-containing substances to the water in the water area, adding acid or alkaline solution to the soil, and reducing the density of vegetation in the area, adding sulfur-containing gas to the air.
Preferably, the timing module adopts a database time model, wherein the response time and the waiting time are calculated in the database time model.
Preferably, the data recovery module adopts the SQL Server database recovery model.
The remote sensing assessment method of regional ecosystem vulnerability includes the following steps:
S1. Perform data partition processing on the area;
S2. Sampling the data in one of the regions in the partition in S1, and randomly select four groups of data for the water quality, soil, vegetation and air quality in the region;
S3. Apply external pressure to the four sets of data of S2;
S4, Record the response time of the changed data in S3 through the timing module, and discipline the time for the recovery of the changed data;
S5. The discipline data in S4 is output to the expert knowledge base for storage, and the time data is graded for evaluation.
The present invention provides a remote sensing assessment method and system for regional ecosystem vulnerability. It has the following beneficial effects:
By setting up a data sampling module, an external pressure test module, a data recovery module and a timing module, it is convenient to simulate the impact of external pressure on the regional ecological environment, and to record and grade these impacts, so as to increase the work efficiency of collecting ecological environment vulnerability data and reduce the workload of staff.
Fig. 1 is the flow chart of the present invention;
Fig. 2 is an internal diagram of a data sampling module in the present invention.
The technical solutions in the embodiment of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiment of the present invention. Obviously, the described embodiment are only a part of the embodiment of the present invention, rather than all the embodiment. Based on the embodiment of the present invention, all other embodiment obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
As shown in Figures 1-2, an embodiment of the present invention provides a regional ecosystem vulnerability remote sensing assessment system, including a regional partition module, a data sampling module, an external pressure test module, a data recovery module, and a timing module , and the regional partition module transmits partition data. To the data sampling module, the data sampling module transmits the sampling data to the external pressure test module, the external pressure test module transmits the data to the data recovery module, and both the data recovery module and the external pressure test module transmit the data to the timely module;
The area partition module is used to partition the area;
The data sampling module is used to sample the data in one of the areas in the partition. The data sampling module uses the CR algorithm to perform random sampling. The phosphorus content is sampled, the PH in the soil is sampled, the vegetation density in the area is sampled, and the sulfur content in the air quality is sampled, which is convenient for the external pressure processing of these four sets of data.
The external pressure test module is used to perform the corresponding pressure interference test on the sampled data. The external pressure test module applies external interference to the four groups of data of water quality, soil, vegetation and air quality respectively. Add phosphorus-containing substances to the water in the area, add acid or alkaline solution to the soil, reduce the density of vegetation in the area, add sulfur-containing gas to the air, and add phosphate solution to the water area in the area, so as to change the phosphorus content in the water area. , making the water eutrophic,then add the carbonate solution to the soil to change the pH value of the soil. The staff uses the vegetation in the area to cut into the vegetation in the area to reduce the density of vegetation.
The timing module is used to collect the time parameters consumed in the external stress test module and the data recovery module. The timing module adopts the database time model, in which the response time and waiting time are calculated in the database time model, where the response time is when the outside world affects the data. The time used for data change is convenient for evaluating the sensitivity of the ecological environment, and then the waiting time is the time from changing data to restoring the original data, which is convenient for evaluating the recovery capability of the ecological environment. The less time spent indicates that the ecological environment in the area is less vulnerable. 5 The remote sensing assessment method of regional ecosystem vulnerability includes the following steps:
S1. Perform data partition processing on the area, and divide the area into multiple areas, so as to facilitate the subsequent data evaluation of the multiple areas.
S2. Sampling the data in one of the regions in the partition in S1, randomly select four groups of data for water quality, soil, vegetation and air quality in the region, and select four groups of environmental data with weights in the ecological environment.
S3. Apply external pressure to the four sets of data in S2 to change the phosphorus content in the water, the pH value in the soil, the density of the vegetation and the sulfur content in the air, so as to discipline the response time of data changes and restore the data. time for discipline.
S4. Record the response time of the change data in S3 through the timing module, and discipline the time of the change data recovery, so as to facilitate the evaluation of the recovery ability of the ecological environment.
S5. The discipline data in S4 is output to the expert knowledge base for storage, and the time data is graded and evaluated. The grades are graded according to the principle that the less time used, the better, and the data is collected in some areas through worker intervention. , to increase the efficiency of collection and evaluation.
Although embodiment of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, and substitutions can be made in these embodiment without departing from the principle and spirit of the invention and modifications, the scope of the present invention is defined by the appended claims and their equivalents.
Claims (7)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NL2032387A NL2032387B1 (en) | 2022-07-06 | 2022-07-06 | A regional ecosystem vulnerability remote sensing assessment system |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NL2032387A NL2032387B1 (en) | 2022-07-06 | 2022-07-06 | A regional ecosystem vulnerability remote sensing assessment system |
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| Publication Number | Publication Date |
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| NL2032387B1 true NL2032387B1 (en) | 2024-01-23 |
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| NL2032387A NL2032387B1 (en) | 2022-07-06 | 2022-07-06 | A regional ecosystem vulnerability remote sensing assessment system |
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| NL (1) | NL2032387B1 (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112903606A (en) * | 2021-02-09 | 2021-06-04 | 深圳大学 | Mangrove forest ecological restoration force assessment method based on unmanned aerial vehicle hyperspectrum |
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112903606A (en) * | 2021-02-09 | 2021-06-04 | 深圳大学 | Mangrove forest ecological restoration force assessment method based on unmanned aerial vehicle hyperspectrum |
Non-Patent Citations (2)
| Title |
|---|
| GALAPPATHTHI K ET AL: "TOPICAL REVIEW @BULLET OPEN ACCESS A review of measuring ecosystem resilience to disturbance You may also like A review of measuring ecosystem resilience to disturbance", ENVIRON. RES. LETT, 14 May 2021 (2021-05-14), pages 53008, XP093032973, Retrieved from the Internet <URL:https://iopscience.iop.org/article/10.1088/1748-9326/abdf09/pdf> [retrieved on 20230320] * |
| MÜLLER F ET AL: "Assessing resilience in long-term ecological data sets", ECOLOGICAL INDICATORS, ELSEVIER, AMSTERDAM, NL, vol. 65, 6 December 2015 (2015-12-06), pages 10 - 43, XP029447223, ISSN: 1470-160X, DOI: 10.1016/J.ECOLIND.2015.10.066 * |
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