Chapter One
Theoretical basis and analysis of research hotspots
1. Introduction to ecosystem services and ecosystem service values
2. Research methods of ecosystem service value
3. Research hotspots on ecosystem service value
Visual Analysis of Citespace Literature
VOSviewer document visual analysis
Chapter two
Spatial data source and preprocessing
1. Introduction to Spatial Data
2. ArcGIS Pro data collection and analysis
Data loading and database construction
Space coordinate system establishment and selection
Spatial data collection and storage
map symbol design
Map layout design and research area map making
3. Acquisition and preprocessing of environmental element data
Introduction to data types and acquisition methods
Introduction to Remote Sensing Cloud Computing Platform
PIE ENGINE Grammar Introduction
Training based on PIE ENGINE data acquisition
Data processing training based on PIE ENGINE
third chapter
Estimation and Analysis of Ecological Service Value Based on Value Equivalent Factor Method
1. Ecological service value estimation based on value equivalent factor method
Spatial data source and processing
Ecosystem Type Classification
Ecosystem service function type
Estimation method of ecosystem service function value
Spatial Statistical Analysis Based on ARCGIS
2. Analysis of temporal and spatial changes of ecosystem service value
The impact of land use on the value of ecosystem services
Characteristic analysis of land use transfer
Chapter Four
Ecosystem carbon storage function and value assessment based on InVEST model
1. Ecosystem service function evaluation model based on InVEST carbon module
Introduction to InVEST Models
InVEST Carbon Module Introduction
Model parameter interpretation and data preparation
Model running and result analysis
2. InVEST Blue Carbon Ecosystem Service Value Estimation
chapter Five
Evaluating the social value of ecosystem services based on the SolVES model
SolVES 4.0 Model Environment Configuration
1. Introduction to SolVES 4.0 model functions
2. QGIS 3.8.2 installation and configuration
3. PostgreSQL 11.7 installation configuration
4. PostGIS 2.5.3 installation configuration
5. Maxent 3.4.1 installation configuration
load sample data
Note: SolVES 4.0 was developed and tested on a system running Microsoft Windows 10 Enterprise Edition with a 64-bit processor. The software listed above is required to run Solution 4.0. Additionally, the Java Runtime must be available on the system running Solution 4.0 in order to access and run Maxent 3.4.1.
SolVES 4.0 model run
1. Create a new project
2. Data Analysis Tools
Principles of Survey Data Analysis
Survey data analysis parameter selection and setting
3. Transfer Value Tool
Transfer Value Calculation Principle
Transfer value instrument parameter selection
4. Analysis of model running results
Users generate composite reports that map social value and related environmental indicators based on the results of current projects or previously completed projects.
The map layout contains selected value index maps, including study area boundaries and selected backgrounds. The map title includes project name, survey group, and social value type.
Continuous data is displayed in the form of a line graph. Categorical data are displayed as scatterplots. The x-axis labels of the scatterplot have integer values for the specified categories.
AUC values, mean nearest neighbor statistics, and maximum index scores are included in the map layout for all results generated by the Analyze Survey Data tool.
5. SolVES model performance test
Maxent model principle
Maxent model parameters and operation
MaxEnt result analysis:
Based on the AUC data generated by the MaxEnt model, the performance of the model operation is tested for reliability and fitness, and the area under the Maxent curve and the variable contribution are interpreted and adjusted.
Transfer Value Results Analysis:
When the study area has a similar biophysical and social context to the main study area, but survey data are not available, a value transfer mapping model can be used, accessed through the transfer value tool, relying on Maxent's Solve the statistical models generated in the analysis.
SolVES 4.0 model data preparation and storage
1. Table data type and format and loading
The "id" field and the "geom" field (in the case of vector data) are managed by PostgreSQL and should not be included when preparing user-supplied data for loading into the solver database.
2. Spatial data loading
3. Acquisition of social survey data
Understand the characteristics and satisfaction of the interviewees
Respondents were asked to assign social values and mark corresponding social value points.
Collect social background and demographic characteristics data of respondents
4. Source and processing of spatial data
Geospatial data includes Shapefiles and raster datasets of the study area:
The STUDY_AREA class Shapefile needs to study the boundary elements of the area;
SURVEY_POINTS data is based on questionnaire digitization;
The raster dataset is the extraction of environmental elements in the study area;
For SURVERY_POINTS data and STUDY_AREA data, use the kernel density analysis tool of ArcGIS to operate on the two data, and output the overall spatial distribution map of social value.
4. SolVES model processing data
Perform average nearest neighbor analysis on the SURVERY_POINTS data to obtain the average nearest neighbor ratio (R-ratio) and standard deviation (Z-score), highlighting the importance of each value in the region;
Using the SolVES model to statistically integrate the hypothetical scores assigned to each social value by the respondents collected from the questionnaire, a spatially explicit map with a 10-point value index (VI) is generated to determine each social value The importance of type.
Group the respondents, import the corresponding socio-demographic characteristics data and spatial data into the model, use the value index output by normalized calculation as the weight, and output the spatial distribution map of each social value in the entire research area, and these A graph of the relationships that exist between value distributions and environmental variables.
Chapter Six
Correlation Analysis of Environmental Variables and Social Value
1. Multicollinearity test of environmental variables
R environment configuration and basic syntax
correlation analysis
variance inflation factor analysis
2. Statistical Analysis
Statistical Analysis of Landscape Types Using ArcGIS Zonal Statistical Tool
3. Spatial distribution of main social value types
4. Analysis of the impact of environmental variables on social value
Conduct a correlation analysis on the selected landscape types under the social value points marked by the interviewees, get the public's favorite landscape type, and analyze the influencing factors of the landscape type and social value;
5. Analysis of the contribution rate of environmental variables
The contribution of each environmental variable can be obtained according to the contribution rate of the environmental variables obtained from the operation of MaxEnt
6. Spatial autocorrelation analysis
The relationship between the distance variable and VI was judged according to Moran's I, p value and z score.
7. Analysis of the effectiveness of social value transfer of ecosystem services
Transfer Error Analysis
Variance analysis
Chapter VII
SCI Thesis Writing and Expanding Case Analysis
Analysis of paper writing skills and submission strategies
Biodiversity value assessment of national parks from the perspective of social-ecological coupling analysis
Case training:
(1) Habitat quality assessment based on the InVEST model
(1) Social value assessment based on SoLVES
(2) Coupling degree analysis
(4) Hot spot analysis
l Estimation of Urban Ecosystem Services Value: A Case Study ofChengdu, Southwestern China
l Evaluating Trade-Off and Synergies of Ecosystem Services Values of a Representative Resources-Based Urban Ecosystem
Link to the original text: The application, paper writing, and extended analysis of the social value assessment of ecosystem service functions based on the multi-technical integration of the equivalent factor method, InVEST, and SolVES models