基于MODIS数据的城西湿地地表温度演化特征与机制分析

摘要由人类活动所致的土地利用/土地覆盖（LULC）方式的改变是区域及全球气候变化驱动力的关键组分，而城市化则是地表组成及其结构大规模变化的主要驱动力之一。本文以长三角南翼核心城市杭州市为研究区，基于MODIS LST和NDVI产品数据，辅以LANSAT 8 TIRS数据，在城市区域地表温度时空特征分析的基础上，围绕杭州城西湿地、典型样区和典型地物，展开相应地表温度时空特征及形成机制分析。结果表明：（1）城市热力景观主要以中温区和次高温区为主，而且从城市中心到郊区热力景观呈现由高到低的现象。（2）热环境空间自相关分析表明，杭州市各季节均以高-高集聚或低-低集聚为主。（3）城西湿地LST和NDIV的时间序列分析表明：城西湿地LST和NDVI值夏季高，且各月LST值和NDVI值由高到低呈现为：五常湿地/和睦湿地＞西溪湿地＞南湖。（4）剖面分析表明各个季节LST和NDVI变化规律基本同步。（5）归一化植被指数NDVI与LST呈负相关性，归一化建筑指数NDBI与LST呈正相关；由此可见，植被对城市地表温度具有一定的降温效应；建设用地则有着相反的作用。51468

Abstract Land use and land cover change caused by human activity is essential to the regional and global climate change. As one of the most important driving factor, urbanization tremendously changed the composition and structure of earth surface. In this paper, Hangzhou, a core city located at southern Yangtze River Delta in China was selected as the study area. Based on MODIS LST and NDVI data products, supplemented by LANSAT 8 TIRS data, the spatial and temporal distributions and formation mechanism of surface temperature in Western Hangzhou Wetland, typical regions, and typical samples, were analyzed. The results showed that: (1) Among these five types of thermal landscape, the middle temperature region and sub-high temperature region are the most prevalent, and the thermal landscape distributions have moved from the suburb to the downtown. (2) Thermal environment spatial autocorrelation analysis showed that the high-high concentration and low-low concentration were adjacent at all seasons in Hangzhou City. (3) LST and NDIV time series analysis in Western Hangzhou Wetland showed that, the value of the two are high in summer, and average value from high to low in every months appeared as: Wuchang Wetlands/Hemu wetlands, Xixi Wetlands, and South Lake. (4) Profile analysis showed that the value of LST was synchronous with that of NDVI in each season in Hangzhou City. (5) The value of LST was negatively related with NDVI, and positively related with NDBI.

毕业论文关键词：热岛效应; 地表温度反演; 时空分布; 归一化植被指数

Keyword: Heat island effect; Land surface temperature retrieval; Spatial and temporal distributions; NDVI

1 引言 5

2 研究区概况 6

3 数据与方法 7

3.1 数据获取 7

3.2 数据处理及研究方法 7

3.2.1 整体技术方案 7

3.2.2 数据预处理 8

3.2.3 热力景观分析 8

3.2.4 空间自相关分析 9

3.2.5 剖面分析 10

3.2.6 时间序列分析 10

3.2.7 地表温度反演 10

3.2.8 遥感指数提取 10

4 结果与分析 11

4.1 区域热力景观分析 11 基于MODIS数据的城西湿地地表温度演化特征与机制分析:http://www.751com.cn/zidonghua/lunwen_55099.html