长江流域资源与环境 >> 2013, Vol. 22 >> Issue (06): 721-.

• 自然资源 • 上一篇    下一篇

不同土地利用类型的地表特征参量的遥感反演研究——以猫跳河流域为例

原菲菲 | 徐增让 |詹卫华 | 鲁春霞 | 曹文德   

  1. (1.中国矿业大学(北京)地球科学与测绘工程学院|北京100083|2.中国科学院地理科学与资源研究所|北京100101|3.水利部综合事业局| 北京 100053
  • 出版日期:2013-06-20

LAND SURFACE COEFFICIENT EXTRACTION OF DIFFERENT LAND USE TYPE DERIVED FROM REMOTE SENSING INVERTION MODELING IN THE MAOTIAO RIVER WATERSHED

YUAN Feifei1| XU Zengrang2| ZHAN Weihua3, LU Chunxia2| CAO Wende1| RU Weina1   

  1. (1.College of Geoscience and Surveying Engineering|China University of Mining &|Technology(Beijing), Beijing 100083, China; |2.Institute of Geographic Sciences and Natural Resources Research|Chinese Academy of Sciences| Beijing 100101| China|3.Office of the National Water Park,the Ministry of Water Resource of China, Beijing 100053, China
  • Online:2013-06-20

摘要:

利用2007年5月Lansat5 TM数据,运用单通道算法,基于全国遥感监测土地利用/覆盖分类体系,对贵州省猫跳河流域的地表特征参量进行了反演,得到不同土地利用类型下的典型地表特征参数值。在3种主要的土地利用类型中,林地的植被指数最高、地表温度最低,农田的植被指数最低而地表温度最高,草地介乎林地和农田之间。城镇建设用地主要表现为热岛效应,而水域则主要表现为地表温度(LST)和归一化植被指数(NDVI)的双低特征。进一步对二级土地利用类型的分析表明,由于结构、功能的不同,土地利用二级类在地表特征参量方面也表现出了有规律地变化。有助于深入认识不同土地利用类型的物理特征,可以丰富主要土地利用类型的影像分类的先验知识,有望将不同土地利用方式的生态环境效应研究推进一步

Abstract:

Landsat thematic mapper(TM) has a thermal band(TM6),and this band can be used for retrieving land surface temperature(LST).In this paper,typical surface features parameter values were retrieved base on Landsat 5 TM remote sensing data of May,2007 in the Maotiao River watershed.The NDVI(normalized difference vegetation index) can be calculated using TM3 and TM4 band data,the land surface emissivity(LSE) of TM6 can be obtained by using NDVITEM (NDVI Thresholds Method),and the LST(land surface temperature) can be retrieved by single channel algorithm.The classification of land use types uses the China land use/cover of remote sensing monitoring classification system(geographical resources of Chinese academy of sciences,1999).According to this system,the researched area can be divided into 5 class including the forest land,grassland,cultivated land,water area and urban and rural construction land,and 13 subclass by which NDVI and LST can be respectively statisticed.The results indicated that in the three main types of the land use,the forest land had the highest NDVI and the lowest LST,farmland had the lowest NDVI and the highest LST,and the features parameter of grassland was between forest land and farmland.Heat island effect was clear in urban construction land,and both LST and NDVI were low in waterbody.The analysis of land use types shows that the surface characteristic parameters in the subclass land use/coverage scale represented regularly change even in the same kind of land use type for the different structure and function.In the subclass of forest land,forested land had the highest NDVI and the lowest LST.The NDVI of shrub land,sparse woodlot and other woodlands diminished gradually while the temperature increasesd gradually.In the subclass of grassland,high cover grass had the highest NDVI and lowest LST and the NDVI of low cover grass was the lowest,while the temperature was the highest.The features parameter of moderate cover grass was between high and low cover grass.In the subclass of farmland,the NDVI of paddy fields was greater than the dry land,while the temperature of the former was less than the latter.In the subclass of urban and rural construction land,NDVI and temperature had no apparent reverse relation.In order to deeply understand the significant degree of mean differerce of LST and NDVI in any two land use types of subclass,a series of posthoc multiple comparison tests using GamesHowell method were conducted associated with each possible pairing of land use types of subclass in SPSS.Most pairings exhibited significantly different mean values of NDVI and LST,while 3 pairings including forested land and high cover grass,sparse woodlot and moderate cover grass,construction land and urban use land were not significantly different in both NDVI and LST.Overall,a significant inverse relationship between LST and NDVI was observed for the entire watershed.Comparisons of mean NDVI and LST associated with individual pairings suggest that the majority of land use types of subclass can be differentiated on the basis of both LST and NDVI,and it is meaningful to analysis with the scale of subclass.This research helps to deepen the understanding of physical characteristics of different land use types and enrich the experienced knowledge of image classification of the main land use types

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