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1地表不透水面信息遥感的主要方法分析显示文摘全球范围内的城市扩张已使得大量的不透水面取代了以植被为主的地表自然景观,并给生态环境带来了明显的负面影响。不透水面作为一个影响生态环境的关键因子已引起了全社会的广泛关注。如何及时快速地掌握不透水面的空间分布信息,准确无误地量化不透水面的动态变化信息,是城市规划、环境保护亟待解决的现实问题。而遥感以其快速、大范围、多尺度、可重复的对地观测优势为解决这一问题提供了很好的解决方案。不透水面遥感研究经过近十几年的发展已有了长足的进步,多种针对不透水面信息反演的遥感创新技术与方法被相继提出。本文重点分析了这些针对遥感不透水面提出的创新技术,详细地指出了它们的优势和不足,并在此基础上总结了中国遥感工作者在不透水面遥感方面的研究工作。当前许多不透水面信息的反演精度都可以达到85%以上,但是不透水面与裸土和阴影信息的混淆仍是困扰不透水面信息精准反演的主要问题。由于大部分不透水面材料具有和砂土石同源的特点,因此在现有影像光谱分辨率不足的情况下,单靠光谱是很难进一步提高不透水面信息的反演精度,而借助LiDAR等其他辅助数据,将有望帮助解决这一瓶颈问题。徐涵秋 王美雅 2016遥感学报2016,20,5:111
2Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data显示文摘This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.YUE Wenze 2009Chinese Geographical Science2009,19,3:7
3Examining the Relationship Between Spatial Configurations of Urban Impervious Surfaces and Land Surface Temperature显示文摘The urban heat island(UHI) effect has significant effects on the quality of life and public health. Numerous studies have addressed the relationship between UHI and the increase in urban impervious surface area(ISA), but few of them have considered the impact of the spatial configuration of ISA on UHI. Land surface temperature(LST) may be affected not only by urban land cover, but also by neighboring land cover. The aim of this research was to investigate the effects of the abundance and spatial association of ISAs on LST. Taking Harbin City, China as an example, the impact of ISA spatial association on LST measurements was examined. The abundance of ISAs and the LST measurements were derived from Landsat Thematic Mapper(TM) imagery of 2000 and 2010, and the spatial association patterns of ISAs were calculated using the local Moran’s I index. The impacts of ISA abundance and spatial association on LST were examined using correlation analysis. The results suggested that LST has significant positive associations with both ISA abundance and the Moran’s I index of ISAs, indicating that both the abundance and spatial clustering of ISAs contribute to elevated values of LST. It was also found that LST is positively associated with clustering of high-ISA-percentage areas(i.e.,>50%) and negatively associated with clustering of low-ISA-percentage areas(i.e.,<25%). The results suggest that, in addition to the abundance of ISAs,their spatial association has a significant effect on UHIs.WU Xiangli LI Binxia LI Miao GUO Meixin ZANG Shuying ZHANG Shouzhi 2019Chinese Geographical Science2019,29,4:3
4Topographical and hydrological effects on meso-scale vegetation in desert steppe, Mongolia显示文摘This study investigated the seasonal variations of the normalized difference vegetation index(NDVI) and its relationships with climatic variables and topography in a small-scale(20 km×20 km) area(i.e., Tsogt-Ovoo village) within the desert steppe zone of Mongolia using in-situ observed climate data and satellite remote sensing data. We found that the topography is very important for vegetation growth in the desert steppe although the summer precipitation is the constraining factor. The unexpectedly high NDVI(up to 0.56), as well as the high aboveground biomass, in the valley bottom was primarily resulted from the topography-modulated redistribution of overland flow after relatively heavy precipitation events during the growing season. This makes the valley bottoms in desert steppes not only reliable feeding resources for livestock but also heavens for wild lives. But, the detected large standard deviation of annual maximum NDVI(NDVI_(max)) from 2000 to 2013 in the valley bottom in response to rather variable precipitation implies that the valley bottoms under desert steppe climates are more vulnerable to climatic change.Batdelger GANTSETSEG Masahide ISHIZUKA Yasunori KUROSAKI Masao MIKAMI 2017Journal of Arid Land2017,9,1:2
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