View the original text>>> Practical application based on "Python+" multi-technology fusion in the estimation of evapotranspiration and total primary productivity of vegetation
Familiar with evapotranspiration ET and its components (vegetation transpiration Ec, soil evaporation Es, canopy interception Ei), the concept of vegetation gross primary productivity GPP and the basic principles of carbon-water coupling; master the use of Python and ArcGIS tools for course-related operations; proficiency Master the internationally popular Penman-Monteith model, and be able to apply this model to calculate canopy conductance and evapotranspiration components on various vegetation types; master visualization methods and mapping methods for single-station and regional results.
Table of contents
1. Evapotranspiration and photosynthesis impedance
4. Data download and processing
【Brief description】:
1. Evapotranspiration and photosynthesis impedance
Evapotranspiration and photosynthetic impedance are important concepts in plant physiology. Evapotranspiration is closely related to plant water balance, growth and metabolism; while photosynthesis resistance reflects the diffusion resistance formed by plants to maintain photosynthesis under the condition of limiting water evapotranspiration. Studying the principles of evapotranspiration and photosynthesis impedance is helpful to understand the photosynthesis efficiency, growth rate and ecological adaptability of plants, and provide scientific basis and decision support for agricultural production, forestry management and environmental protection.
2. Python instructions
2.1. Installation of Jupyter Notebook editor + Anaconda manager
Python is an easy-to-learn, powerful programming language with rich standard library and extensive third-party library support, suitable for many fields such as big data processing, artificial intelligence, and web development.
2.2 Installation and configuration of virtual environment
Virtual environments allow the creation of multiple independent Python environments on the same machine, each of which can have its own version of Python and third-party libraries installed. Different projects can use different Python versions and dependent libraries, avoiding version conflicts and dependency conflicts.
2.3 Common library learning
This section includes the basic syntax of Python and the use of common scientific computing (Numpy), data processing (Pandas) and data visualization (Matplotlib) library functions.
2.4 Data processing
Common data problems in Python include data duplication, data exception, text type, data missing, data invalid, etc., corresponding to operations such as outlier processing, text conversion, and blank value filling.
3. ArcGIS practice
3.1 Basic Operation
The basic operations of ArcGIS include creating and opening map documents, loading data, saving documents, layer operations, data frame coordinate system definition, feature attribute query, etc.
3.2 Data format conversion
In ArcGIS, the mutual conversion of different data formats can be realized, such as the mutual conversion between EXCEL data and Shapefile data, TXT data and Shapefile data, etc.
3.3 Extract raster values
Value extraction to points can be achieved in ArcGIS or batch processing of raster datasets can be achieved using ArcPy.
3.4 Data pruning
The clipping function in ArcGIS is used to clip the layer or raster dataset according to the specified boundary range. Clipping allows you to remove data that is not of interest or to limit it to a specific area for better analysis and visualization.
3.5 Cartography
Cartography mainly includes the main elements of map layout design, map rendering methods, etc.
4. Data download and processing
4.1 Site data download and processing
FLUXNET2015 is a global-scale observational dataset of carbon, water, and energy fluxes, bringing together data from more than 200 observing sites. The dataset provides in situ observations of multiple observed variables such as carbon, water, and energy fluxes, stored and shared in a standardized format.
Ø Data download
Open the website https://fluxnet.org/data/fluxnet2015-dataset/ , click Download FLUXNET2015 Dataset, and log in with the user name and account password. You can choose a site according to your needs and fill in the application requirements to complete the download.
Ø Data processing
According to research needs, the downloaded data is processed, including variable selection, outlier processing, and blank value filling.
4.2 Regional data download and processing
GLASS is a global land surface remote sensing dataset that provides high-resolution vegetation leaf area index (LAI) data with a spatial resolution of 250m/500m/0.05° and a temporal resolution of 8 days.
Ø Data download
Open the website http://www.glass.umd.edu/index.html , select the LAI dataset with the corresponding resolution according to the research needs, and use DownThemAll! to download the data in batches.
Ø Data processing
The downloaded data is in hdf format. According to research requirements, the downloaded data is processed, including data format conversion, definition projection, corresponding raster value extraction, data summary, etc.
5. Application case
nCase 1: Calculation of evapotranspiration, soil evaporation, and vegetation transpiration at the site scale
On the station scale, the effective energy of the canopy and the effective energy of the soil are calculated by using the leaf area index and net radiation, and the soil evaporation is obtained according to the accumulated precipitation and the equilibrium evaporation rate of the soil surface for a certain period of time, and then the vegetation transpiration and canopy conductance are calculated. Spend. The specific operation is as follows:
1. Station value extraction and interpolation of leaf area index
Ÿ Data format conversion
Ÿ Definition of projection
Ÿ Station value extraction
Ÿ Data interpolation
2. Calculation of soil evaporation
Ÿ Canopy effective energy and soil effective energy calculation
Ÿ Soil evaporation fraction calculation
Ÿ Soil balance evaporation calculation
3. Calculation of vegetation transpiration
Ÿ Calculation of psychrometer constant
Ÿ Calculation of the slope of the relationship curve between saturated water vapor pressure and temperature
Ÿ Calculation of aerodynamic conductance
4. Canopy conductance calculation
Ÿ numerical calculation
Ÿ result visualization
Case 2: Regional Data Download, Processing and Display of Evapotranspiration and Vegetation Gross Primary Productivity
Download, process, display and count the data of regional surface evapotranspiration and its components (soil evaporation, vegetation transpiration, canopy interception evaporation), and vegetation total primary productivity data.
[Other related recommendations]:
Advanced application and batch simulation of APSIM model based on R language
Ecosystem NPP and carbon source and carbon sink simulation practice technology application