Since the Industrial Revolution, social productivity has increased rapidly and human activities have been frequent. In addition, the growing population has a stronger demand for and transformation of land, and the relationship between man and land has become increasingly tense. In addition, the irrational development and utilization of land resources has caused a series of ecological and environmental problems such as soil erosion, vegetation degradation, water shortage, regional climate change, and sharp decline in biodiversity. How to optimize the land use pattern, maintain regional land ecological security, alleviate the contradiction between land supply and demand, and make the human-land relationship harmonious and co-existing has become a research hotspot at home and abroad.
Ecosystem services are the benefits that humans obtain directly or indirectly from ecosystems, and play a vital role in addressing urban challenges and implementing sustainable development. With the rapid development of global urbanization, frequent human activities have led to rapid changes in land use, resulting in changes in ecosystem structure and function, affecting the supply of ecosystem services. Therefore, the integration of ecosystem service assessment and future urban land planning has become an important research topic in recent years.
The scenario analysis method is currently one of the most mature methods for the study of future ecosystem service trade-offs and synergies. By establishing different land use scenarios to analyze the changes among ecosystem services and the internal interaction effects, decision-making suggestions can be made for future land use planning scenarios. The PLUS model has two modules, one is the rule mining framework based on the land expansion analysis strategy, and the other is the CA model based on multi-type random patch seeds. In addition, the model also has a built-in Markov chain in order to make predictions on the amount of land use . The PLUS model can use a patch-level land use simulation model to accurately simulate the nonlinear relationship changes behind land use, and achieve a more accurate impact of land use on potential ecosystem services under different policy scenarios in the future.
In the case of intensified succession of land scenarios in the future, it is necessary to accurately simulate the development potential of future land use, to conduct multiple scenario planning in line with policy guidelines, and to reasonably and accurately simulate the various functions and trade-offs of ecosystem services. Sustained ecosystem services trade-offs urgent need for development concepts. The application of geospatial analysis techniques will ensure the realization of this goal, and the use of PLUS models will help decision makers evaluate and plan land use policies in advance by setting development driving parameters under the required scenario conditions. The InVEST model has been widely used to assess ecosystem services.
Explain the multi-scenario forecasting of ecosystem services from the aspects of data, methods and practice. The content covers the acquisition, selection and unification of multi-source data; ArcGIS spatial data processing, spatial analysis and mapping; the principle of PLUS model and InVEST model, parameter extraction and model operation and result analysis; land use changes in time and space and the impact on ecosystem services analyze;
Can learn:
1) Based on historical land use data, future land use prediction under multi-scenario mode;
2) Use the InVEST model to quantify and evaluate ecosystem service functions;
3) Prediction and analysis of temporal and spatial changes of spatial data;
4) Attribution analysis of spatial heterogeneity of ecosystem services. In specific practical cases, you will learn to use the above principles and technical methods to improve the application ability of spatial information technology.
【Tutor Accompanying】:
1. Establish an exchange group for mentors to help students, to answer questions and share experiences for a long time, to assist learning and application.
2. Online question-and-answer exchanges will be held from time to time after the course ends to assist learning and consolidate work practice problem-solving exchanges
[Method]: webcast + student group assistance + face-to-face practical work communication with tutors
[Teaching Features]:
1. Explain the principles in simple terms;
2. Explanation of skills and methods, providing all case data and codes;
3. Combined with the project case to explain the implementation method, and connect to the actual work application;
4. Follow up with computer operations, independently complete case operation exercises, and track and analyze problems throughout the process;
5. At the end of the course, the exclusive student aid group assists in consolidating learning and practical work application exchanges, and holds online Q&A from time to time;
[Outline]:
Chapter 1 Theoretical Basis and Software Introduction
1. Concept definition and theoretical basis
Land use
Multi-scenario simulation
Ecosystem services
2. Introduction to geographic data
Geodatabase:
File Geodatabase: A collection of multiple types of GIS datasets saved in a file system folder;
Personal Geodatabase: The raw data format for ArcGIS geodatabases stored and managed in Microsoft Access data files
Raster data: It consists of a matrix of cells (or pixels) organized by rows and columns (or grid), each of which contains an information value. Rasters can be digital aerial photographs, satellite imagery, digital pictures, or even scanned maps.
Vector data: It is a non-topological simple format that stores the geometric position and attribute information of geographic elements. Geographic elements are represented by points, lines, or areas (regions).
Form data:
3. Introduction and practice of ArcGIS spatial data processing and analysis
ArcGIS Platform Introduction
ArcGIS common coordinate system
ArcGIS spatial data processing and conversion
ArcGIS spatial analysis
ArcGIS mapping skills
4. Introduction and installation of PLUS model and InVEST model
PLUS version introduction, installation;
PLUS software interface, common function introduction;
InVEST version introduction, installation;
InVEST software interface, common function introduction;
Those pits that have been stepped on in the past - common mistakes and usage attention; path problems, etc.
Chapter 2 Data Acquisition and Preparation
1. Land use data
Introduction and acquisition method of land use dataset
Land use data set selection
Land use data preprocessing: image stitching, cropping, reprojection, etc.
2. Driving factor data
Climate and environmental data
Socioeconomic data
3. Different types of data preparation methods and practices
Raster data processing:
Raster image stitching, cropping, reprojection and resampling;
Basic geographic information data processing and spatial analysis:
Introduction and Analysis of Euclidean Distance Algorithm
Introduction and Analysis of Density Analysis Algorithm
Topographic factor extraction
The principle and method of extracting terrain factors such as slope, aspect, terrain relief, and hill shadow
Soil factor data extraction
Editing and exporting of attribute tables
properties of the join table
Reclassify: Various methods to reclassify or change input cell values to substitute values
Lookup Table: Creates a new raster by looking up the value of another field in the input raster data table
Meteorological factor data processing:
Site data download and extraction
Interpolation analysis: interpolation analysis of meteorological station data by inverse distance weighting (IDW), natural neighborhood method, trend surface method and spline function method;
NetCDF data processing: Create a raster layer from a NetCDF file
Raster data conversion method
Chapter 3 Simulation of Land Use Pattern
1. Principle of PLUS model
Rule Mining Framework Based on Land Expansion Analysis Strategy
CA model based on multi-type random patch seeds
2. PLUS model construction and accuracy verification
Land use expansion analysis
Simulation parameter setting
(1) Restricted area
(2) Field effect
(3) Conversion cost
(4) Domain weight
(5) Land use demand
Use a Markov model to predict completion.
In the formula: St and St+1 are the land use in period t and t+1, Pij is the transition probability matrix, and n is the land use type.
Model accuracy verification
Overall accuracy (overall accuracy)
Kappa coefficient
3. Simulation of land use pattern in Hengduan Mountains under different scenarios
Land use simulation under natural development scenarios
Land use simulation under ecological protection scenarios
Land use simulation under economic development priority scenarios
Chapter 4 Ecosystem Service Assessment
1. InVEST model principle and modules
2. Water production service
Data requirements and preparation:
3. Soil conservation
Data requirements and preparation:
4. Carbon storage
Data requirements and preparation:
5. Habitat quality
Data requirements and preparation:
Chapter Five Spatiotemporal Changes and Driving Mechanism Analysis
1. Analysis of spatial and temporal changes in land use
Analysis of changes in land use structure
Analysis of land use dynamics
Land use transfer matrix analysis
Standard deviation ellipse analysis of land use
2. Spatial autocorrelation (Global Moran's I) (Spatial Statistics) analysis principle and practice
3. Working principle and practice of high/low clustering (Getis-Ord General G) analysis
Use the Getis-Ord General G statistic to measure the degree of clustering of high or low values.
4. Analysis of spatial stratification heterogeneity
Principle of geographic detector
Installation and introduction of geographic detector module
Factor detection
Interactive detection
5. Local regression analysis
Introduction to Geographically Weighted Regression Models
Basic principles of model building
(1) Determination of space weight coefficient
(2) Bandwidth selection criteria
Analysis of parameters and evaluation indicators
Spatial pattern analysis of regression coefficient
Chapter 6 Thesis Writing Skills and Case Analysis
1. Structure of scientific papers
Introduce the main points of writing the abstract, introduction, methods, results, discussion, conclusion
2. Specifications for diagrams in scientific papers
3. Analysis of paper submission skills
4. Case analysis of SCI papers
5. Model application can be expanded
Original link: [Paper writing] Multi-scenario simulation prediction based on "PLUS model +" ecosystem services
Related:
Ecosystem NPP and carbon source and carbon sink simulation practice technology application
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