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Ningxia University (2021)

Research on Dynamic Monitoring of Vegetation Productivity in Desert Steppe at Village Scale


Titre : Research on Dynamic Monitoring of Vegetation Productivity in Desert Steppe at Village Scale

Auteur : 张矞勋

Grade : Master 2021

Université : Ningxia University

Résumé partiel
The desert steppe area in the farming-pastoral zone in northern China is not only an important part of the grassland,it plays an important role in my country’s ecological barrier,and it is also an important animal husbandry production base.The fragile environment and lack of resources are the key to restricting the coordinated development of ecology and production in this region.Timely and accurately grasping the vegetation growth status and changing trends in the desert grassland area is conducive to promoting the sustainable use of resources in the agricultural and pastoral system and grassland security.The application of the domestic high-resolution series of remote sensing satellites provides a reliable technical route for this.Based on the remote sensing satellites of BJ-2 and GF-6,with Wanjigou Village in Yanchi County of Ningxia as the object,this study carried out the construction and verification of the vegetation parameter estimation model with high time resolution at the village scale,and tried to use it in the pasture.Dynamic and precise management of the productivity of the scale farming and pastoral system.The main research results and conclusions are as follows :(1)Construction and verification of remote sensing estimation model for vegetation parameters at village scale with high temporal resolution.Through the collection of the BJ-2 with high spatial resolution in 2019 and 15 high time resolution GF-6 satellite remote sensing image data in 2020,combined with ground measurement of land vegetation canopies of different types of use Layer spectrum and vegetation growth parameter data,analyze the canopy spectrum characteristics of vegetation in different growth stages in the growing season.After screening,seven different types of vegetation indices were selected,and models were constructed with the aid of three methods.According to the results of comparative analysis,the Leaf area index(LAI)and biological indicators for grassland,Caragana korshinskii shrub and farmland crops in desert grasslands were established respectively.Estimation model of parameters such as volume and coverag

Mots clés : Desert steppe ;Remote sensing monitoring ;Monitoring model ;Neural network algorithm ;Grassland productivity ;

Présentation (CNKI)

Page publiée le 2 mars 2022