本文選題：草地 + 分類�。� 參考：《電子科技大學(xué)》2017年碩士論文

【摘要】：干旱一直是對中國影響最主要的氣象災(zāi)害之一,它對人類生存、生活的環(huán)境和經(jīng)濟、社會的發(fā)展,都有著嚴(yán)重的負(fù)面影響。內(nèi)蒙古草原面積遼闊,草地干旱是內(nèi)蒙古主要的自然災(zāi)害之一,因此開展內(nèi)蒙古草地干旱災(zāi)害監(jiān)測,建立有效的草原干旱監(jiān)測模型,具有一定的理論意義和現(xiàn)實價值。本文基于風(fēng)云三號氣象衛(wèi)星(FY-3)衛(wèi)星的中分辨率光譜成像儀(Medium Resolution Spectral Imager,MERSI)數(shù)據(jù)和可見光紅外輻射計(Visible and Infra-Red Radiometer,VIRR)數(shù)據(jù),開展內(nèi)蒙古地區(qū)草地干旱監(jiān)測研究。主要研究工作如下:(1)內(nèi)蒙古地區(qū)草地分布提取。經(jīng)過對比三種分類方法的精度及適應(yīng)性,選取隨機森林分類方法提取內(nèi)蒙古地區(qū)草地分布。首先篩選出圖像質(zhì)量好的MERSI數(shù)據(jù),分別采用隨機森林、最大似然法、決策樹法進行分類,利用美國陸地衛(wèi)星8號星(Landsat8)影像數(shù)據(jù)對結(jié)果進行精度驗證;分別對三種分類方法作精度分析對比后,選取隨機森林法對草地進行分類提取,做出本論文研究所需的草地分布圖。(2)草地干旱監(jiān)測指數(shù)研究。利用MERSI數(shù)據(jù)產(chǎn)品生成歸一化植被指數(shù)(Normalized Difference Vegetation Index,NDVI)和地表溫度(Land Surface Temperatrue,LST)旬產(chǎn)品后,分別對基于溫度植被指數(shù)(Temperature Vegetation Dryness Index,TVDI)、植被供水指數(shù)、熱慣量指數(shù)模型進行反演以及計算,生成旬際的干旱指數(shù)產(chǎn)品結(jié)果圖,并結(jié)合草地分布圖,生成草地干旱圖;并對比三種指數(shù)的反演結(jié)果精度。實驗結(jié)果表明基于TVDI的草地干旱監(jiān)測精度最高。(3)基于TVDI的草地干旱分級。結(jié)合內(nèi)蒙古草原旱情情況,建立了適合內(nèi)蒙古草原的干旱指數(shù)分級標(biāo)準(zhǔn),生成干旱等級示意圖;并結(jié)合氣象資料對內(nèi)蒙古草原的空間、旬月年際的變化進行分析。以上工作表明利用FY-3A/MERSI衛(wèi)星資料監(jiān)測內(nèi)蒙古草原干旱具有可行性。
[Abstract]:Drought has always been one of the most important meteorological disasters affecting China, which has a serious negative impact on human survival, living environment, economy and social development.Inner Mongolia has a vast grassland area, grassland drought is one of the main natural disasters in Inner Mongolia, so it is of theoretical significance and practical value to carry out the monitoring of grassland drought disasters in Inner Mongolia and to establish an effective grassland drought monitoring model.Based on the medium Resolution Spectral imager MERSI data of FY-3 and visible and Infra-Red Radiometeror VIRR data, the grassland drought monitoring in Inner Mongolia is carried out.The main research work is as follows: 1) extraction of grassland distribution in Inner Mongolia.By comparing the accuracy and adaptability of the three classification methods, the random forest classification method was selected to extract the grassland distribution in Inner Mongolia.Firstly, the MERSI data with good image quality are selected and classified by random forest, maximum likelihood method and decision tree method, and the accuracy of the results is verified by the image data of American Landsat 8 satellite.After analyzing and comparing the accuracy of the three classification methods, the random forest method was selected to classify and extract the grassland, and the grassland distribution map. 2) the grassland drought monitoring index was studied in this paper.The normalized Difference Vegetation index (NDVI) and Land Surface temperature index (LST) were generated by using MERSI data products. The models of temperature vegetation index, vegetation water supply index and thermal inertia index were retrieved and calculated respectively based on the temperature vegetation index (TVI), the vegetation Vegetation Dryness index (VDI), the vegetation water supply index (VSI) and the caloric inertia index (TCI).The drought index product result map of ten days is generated, and the grassland drought map is generated by combining the grassland distribution map, and the accuracy of the inversion results of the three indices is compared.The results show that the precision of grassland drought monitoring based on TVDI is the highest.According to the drought situation of Inner Mongolia grassland, the drought index classification standard suitable for Inner Mongolia steppe was established, and the map of drought grade was generated, and the spatial and interannual variation of Inner Mongolia grassland was analyzed with meteorological data.The above work shows that it is feasible to use FY-3A/MERSI satellite data to monitor grassland drought in Inner Mongolia.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S812.1

【參考文獻】

相關(guān)期刊論文 前10條

1 劉舒;姜琦剛;馬s，

本文編號：1763574