本文選題：地表溫度 + 植被指數(shù)　； 參考：《太原理工大學(xué)》2017年碩士論文

【摘要】：農(nóng)業(yè)干旱是由于水分供應(yīng)不平衡造成土壤缺水,影響農(nóng)作物的生長發(fā)育,直接導(dǎo)致糧食減產(chǎn),嚴(yán)重時影響糧食安全和社會穩(wěn)定。干旱季節(jié)容易誘發(fā)各種其他自然災(zāi)害,如森林火災(zāi)、蝗災(zāi)、農(nóng)作物減產(chǎn)、水資源短缺、土地沙漠化、地下水位下降等。準(zhǔn)確監(jiān)測農(nóng)業(yè)干旱,長期以來都是學(xué)者們關(guān)注的重點,研究并掌握其發(fā)展特征是國家預(yù)防農(nóng)業(yè)干旱及其他災(zāi)情發(fā)生的重中之重。本文在傳統(tǒng)農(nóng)業(yè)干旱監(jiān)測及遙感干旱監(jiān)測模型基礎(chǔ)上,對地表溫度(Land Surface Temperature,LST)進行數(shù)字高程模型(Digital Elevation Model,DEM)和緯度校正得到修正后的LST,結(jié)合歸一化植被指數(shù)(Normalized Difference Vegetation Index,NDVI)初步構(gòu)建溫度植被干旱指數(shù)(Temperature Vegetation Dryness Index,TVDI)模型;在此基礎(chǔ)上進行擬合干邊改進,形成具有區(qū)域特色的山西省農(nóng)業(yè)干旱TVDI遙感監(jiān)測模型。將其應(yīng)用于研究區(qū),得到1984-2016年山西省農(nóng)業(yè)干旱監(jiān)測結(jié)果,探討并分析研究區(qū)33年間的干旱特征和演變特征,以及農(nóng)業(yè)干旱動態(tài)變化與氣候變化之間的響應(yīng)。通過研究,得到以下主要結(jié)論:1.與改進前的模型相比,改進后的TVDI模型不僅修正了地區(qū)之間由于緯度差異帶來的干旱監(jiān)測誤差,而且對提高高海拔地區(qū)的農(nóng)業(yè)干旱監(jiān)測精度效果顯著。2.山西省農(nóng)業(yè)干旱總體上呈減緩趨勢,歷年均有干旱發(fā)生,旱情由西到北呈現(xiàn)無旱到輕旱再到中旱的垂直分帶現(xiàn)象;全省農(nóng)業(yè)干旱普遍態(tài)勢表現(xiàn)為2-4月北部重旱,其余地區(qū)輕旱或無旱,5-9旱情減緩,10月-次年1月區(qū)域內(nèi)大部地區(qū)為輕旱或中旱;全省季際旱情除春季旱情呈現(xiàn)加重趨勢外,其余三季均呈現(xiàn)出減緩趨勢。3.1984-2016年間,山西省農(nóng)業(yè)干旱的空間空間分布特征為:中旱或重旱區(qū)由西北部蔓延至西部,再到東部和中部,最后到西北地區(qū);輕旱區(qū)由中部蔓延至中部和東部,最后到除中旱或重旱區(qū)的大多數(shù)區(qū)域。無旱區(qū)以運城大部為主,夏季面積達到最大。秋季旱情與DEM高程分布呈現(xiàn)出顯著相關(guān)。4.分析TVDI與溫度、降水的關(guān)系發(fā)現(xiàn):年均TVDI與溫度相關(guān)性不顯著,正、負相關(guān)關(guān)系面積比例均衡,分別占全省總面積的57.3%和43.7%,相關(guān)系數(shù)絕對值東部高于西部;全省大部年均TVDI與降水呈現(xiàn)顯著負相關(guān)關(guān)系,研究區(qū)內(nèi)79%以上區(qū)域呈現(xiàn)負相關(guān),60%以上范圍相關(guān)系數(shù)絕對值達到0.5以上,且以呂梁山為界,東部相關(guān)性高于西部。
[Abstract]:Agricultural drought is caused by water supply imbalance resulting in soil water shortage, affecting the growth and development of crops, directly leading to grain production, seriously affecting food security and social stability. Drought season can easily induce other natural disasters, such as forest fire, locust disaster, crop yield reduction, water resources shortage, land desertification, groundwater level decline and so on. Accurate monitoring of agricultural drought has been the focus of scholars for a long time. It is the most important for the state to prevent agricultural drought and other disasters to study and grasp its development characteristics. Based on the traditional agricultural drought monitoring and remote sensing drought monitoring models, The Land Surface temperature Model Dem (Digital elevation Model Dem) and the modified LSTs after latitude correction are used to construct the Temperature vegetation dryness Index (TDI) model combining with the Normalized difference vegetation Index (NDVI). The TVDI remote sensing monitoring model of agricultural drought in Shanxi Province with regional characteristics was formed. The results of agricultural drought monitoring in Shanxi Province from 1984 to 2016 were applied to the study area. The drought characteristics and evolution characteristics in 33 years and the response between agricultural drought dynamics and climate change in the study area were discussed and analyzed. The main conclusions are as follows: 1. Compared with the improved model, the improved TVDI model not only corrects the drought monitoring error caused by the latitude difference among different regions, but also improves the precision of agricultural drought monitoring in the high altitude area. Generally speaking, agricultural drought in Shanxi Province has slowed down, and drought has occurred over the years, and the drought situation from west to north shows a vertical zonation of no drought to light drought and then to moderate drought, and the general situation of agricultural drought in Shanxi Province is severe drought in the northern part of the province from February to April. The drought in the rest of the region slowed down from 5 to 9, and in most of the regions from October to January of the following year, there was a moderate or moderate drought, and the interseasonal drought in the whole province showed a slowing trend except the increasing trend of drought in spring. 3. During the period 1984-2016, the interseasonal drought in the whole province showed a slowing trend. The spatial distribution characteristics of agricultural drought in Shanxi Province are as follows: moderate or heavy drought areas spread from the northwest to the west, then to the east and the middle, and finally to the northwest, and the light arid areas from the central to the central and eastern, Finally to most areas except moderate or heavily arid areas. The dry-free area is dominated by Yuncheng, with the largest area in summer. There was a significant correlation between drought and Dem height distribution in autumn. By analyzing the relationship between TVDI and temperature and precipitation, it is found that the average annual correlation between TVDI and temperature is not significant, and the proportion of positive and negative correlation area is balanced, accounting for 57.3% and 43.7% of the total area of the province, respectively. The absolute value of correlation coefficient in the east is higher than that in the west. There is a significant negative correlation between TVDI and precipitation in most of the provinces. The absolute value of range correlation coefficient is above 0.5 in more than 79% of the regions in the study area, and the correlation is higher in the east than in the west.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S423

【參考文獻】

相關(guān)期刊論文 前10條

1 張文鴿;劉豪;殷會娟;;基于改進TVDI指數(shù)的河南省干旱監(jiān)測[J];人民黃河;2016年11期

2 王國杰;齊道日娜;王磊;譚;薛峰;;基于風(fēng)云三號氣象衛(wèi)星微波亮溫資料反演東北地區(qū)土壤濕度及其對比分析[J];大氣科學(xué);2016年04期

3 杜靈通;候靜;胡悅;王新云;王磊;;基于遙感溫度植被干旱指數(shù)的寧夏2000-2010年旱情變化特征[J];農(nóng)業(yè)工程學(xué)報;2015年14期

4 王鶯;王勁松;姚玉璧;趙福年;;基于溫度植被干旱指數(shù)的廣東省旱情動態(tài)監(jiān)測[J];草業(yè)學(xué)報;2014年02期

5 鮑艷松;嚴(yán)婧;閔錦忠;王冬梅;李紫甜;李鑫川;;基于溫度植被干旱指數(shù)的江蘇淮北地區(qū)農(nóng)業(yè)旱情監(jiān)測[J];農(nóng)業(yè)工程學(xué)報;2014年07期

6 沙莎;郭鈮;李耀輝;韓濤;趙艷霞;;我國溫度植被旱情指數(shù)TVDI的應(yīng)用現(xiàn)狀及問題簡述[J];干旱氣象;2014年01期

7 龍曉敏;王龍;楊蕊;田琳;;基于溫度植被干旱指數(shù)的云南干旱遙感監(jiān)測[J];中國農(nóng)村水利水電;2012年11期

8 趙杰鵬;張顯峰;廖春華;包慧漪;;基于TVDI的大范圍干旱區(qū)土壤水分遙感反演模型研究[J];遙感技術(shù)與應(yīng)用;2011年06期

9 杜靈通;田慶久;;寧夏回族自治區(qū)NDVI的時空變化特征研究[J];水土保持通報;2011年05期

10 楊樹聰;沈彥俊;郭英;近藤昭彥;;基于表觀熱慣量的土壤水分監(jiān)測[J];中國生態(tài)農(nóng)業(yè)學(xué)報;2011年05期

相關(guān)碩士學(xué)位論文 前1條

1 冀美蓉;基于MODIS遙感數(shù)據(jù)的山西省土壤水分反演研究[D];山西農(nóng)業(yè)大學(xué);2013年

，

本文編號：2084341