China regional transpiration product data set (Evapotranspiration, ET)

Introduction

Vegetation transpiration is the process in which plants absorb water from the soil through their roots, transport it to their leaves, and then evaporate on the surface of the leaves, releasing the water into the air. This is an important water cycle process that plays an important role in maintaining the balance and stability of the ecosystem. Preface – Artificial Intelligence Tutorial

During the process of vegetation transpiration, plants absorb water from the soil through their roots and transport it to their leaves through intercellular spaces and vessels. On the surface of the leaves, water evaporates into water vapor, which is then released into the atmosphere. This process not only helps plants maintain water balance, but also affects the atmospheric environment and climate change.

Vegetation transpiration plays an important role in the balance and stability of ecosystems. It helps plants maintain proper moisture levels, promoting plant growth and reproduction. At the same time, it can also affect the atmospheric environment and climate change. Water vapor released by vegetation transpiration can affect atmospheric humidity and cloud formation, thereby affecting rainfall and temperature.

In short, vegetation transpiration is a very important ecosystem process that plays an important role in maintaining the balance and stability of the ecosystem and influencing atmospheric environment and climate change.

The Chinese region's evaporation product (Evapotranspiration, ET) is provided by the Aerospace Grand Laboratory. It is a smoothed ET product calculated by the Smoother algorithm based on NASA MODIS data (MOD16A2.061), which solves problems such as image cloud coverage and pixel outliers. The processed image results covering the China area were mosaic, and a monthly composite product with a resolution of 500 meters was generated.

Dataset ID: 

MDO/MODIS_MONTH_ET_CHINA

Time range: 2001-2021

Scope: Nationwide

Source:  Aerospace Vision

Copy code snippet: 

var images = pie.ImageCollection("EMDO/MODIS_MONTH_ET_CHINA")

name type Spatial resolution (m) Value range Invalid value Scale Factor Description
mean Int16 500 0~5 32767 0.1 The smoothed monthly synthetic ET average product calculated by the Smoother algorithm
min Int16 500 0~5 32767 0.1 The smoothed monthly synthetic ET minimum value product calculated by the Smoother algorithm
max Int16 500 0~5 32767 0.1 The smoothed monthly synthetic ET maximum value product calculated by the Smoother algorithm
total Int16 500 0~5 32767 0.1 The smoothed monthly synthetic ET product calculated by the Smoother algorithm

date

string

Image date

 

Code:

 /**
 * @File    :   中国地区月度蒸腾产品(MOD-ET)
 * @Desc    :   加载中国地区月度蒸腾产品(MOD-ET)
 */

//引用数据,选择第一景,选择波段并乘以比例因子
var img = pie.ImageCollection('EMDO/MODIS_MONTH_ET_CHINA')
             .getAt(4)
             .select("max")
             .multiply(0.1)
print(img)

// 设置图层显示参数并加载
var visParam = {
    min: 0,
    max: 5,
    palette:'69cd9,7512e8,2091ea,4befce,2edfdd,9efd9f,ebcc76,ff6032,ffc0,c68d',
};
Map.addLayer(img,visParam,"img")
Map.centerObject(img,2)

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Origin blog.csdn.net/qq_31988139/article/details/132812143