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中国地表覆盖异质性参数提取与分析 被引量:5

Extraction and Analysis of Land Cover Heterogeneity over China
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摘要 地表异质性广泛存在于陆地表面各个尺度,是地表参数遥感反演不确定性的主要来源之一。基于高分辨率地表分类参考图,提取出低分辨率混合像元的端元数量和边界长度指标来描述地表异质性。然后以中国地区为例,使用全国30 m空间分辨率Global Land 30地表分类数据集提取出1 km尺度像元的描述混合结构和破碎程度的异质性指标。并基于提取出的异质性指标分析了中国区域在1 km尺度上非均质地表地物类型的组合特征、斑块特征和不同生态群系内部异质性特征。发现山地和生态交错区是主要的高异质性区域,稀树草原生物群系内部异质性最大(平均边界长度为7 426 m),其次依次为森林(4 323 m)、耕地/草地(3 160 m)和灌丛(1 779 m)。 Spatial heterogeneity exists in land surface at every scale, and it is one of key factors to bring uncertainty to land parameter retrieval from remote-sensed data. This paper proposed a methodology to use the boundary length among different land cover types to characterize and quantify land surface heterogeneity based on high-resolution land cover images. Then the heterogeneity feature at 1 kilometer scale in China was extracted from “GlobalLand30” land cover datasets with the spatial resolution of 30 m. The mixed structure, degree of fragmentation and intra-heterogeneity of eight main vegetation biomes from MODIS land cover product over heterogeneous surface in china were analyzed. Mountain area and ecotone are more heterogeneous than other regions. Savanna biome (average boundary length is 7 426 meters) is the most heterogeneous zone followed by forest, grass/crop and shrub biome with average boundary length of 4 323, 3 160, 1 779 meters, respectively.
出处 《地球科学进展》 CAS CSCD 北大核心 2016年第10期1067-1077,共11页 Advances in Earth Science
基金 国家自然科学基金项目"非均质混合像元遥感反射波谱模型构建及叶面积指数反演方法研究"(编号:41271366) 国家重点基础研究发展计划项目"复杂地表遥感信息动态分析与建模"(编号:2013CB733401)资助~~
关键词 空间异质性 地表参数反演 地表分类图 辐射传输 Spatial heterogeneity Parameter inversion Land cover dataset Radiative transfer.
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  • 1杨凯,陈军,关泽群,孙家柄,陆惠文,詹庆明.用多时域遥感影象测定城市演变的方法[J].经济地理,1986,6(3):191-195. 被引量:4
  • 2陈利军,陈军,廖安平,何超英.30m全球地表覆盖遥感分类方法初探[J].测绘通报,2012(S1):350-353. 被引量:22
  • 3姚延娟,阎广建,王锦地.多光谱多角度遥感数据综合反演叶面积指数方法研究[J].遥感学报,2005,9(2):117-122. 被引量:21
  • 4Rasmussen M S. Operational Yield Forecast Using AVHRR NDVI Data: Reduction of Environmental and Inter-annual Variability [ J ]. International Journal of Remote Sensing, 1997, 18(5) : 1059--1077.
  • 5Benedetti Roberto, Paolo Rossini. On the Use of NDVI Profiles as a Tool for Agriculture Statistic : The Case Study of Wheat Yield Estimate and Forecast in Emilia Romagna[ J ]. Remote Sensing of Environment, 1993, 45: 311--326.
  • 6Chen J M, Black T A. Defining Leaf Area Index for Non-flat Leaves[ J]. Plant cell Environment, 1992, 15: 421--429.
  • 7Tian Y H, Curtis E Woodcock, Wang Y J, et al. Muhiscale Analysis and Validation of the MODIS LAI Product I. Uncertainty Assessment [ J ]. Remote Sensing Environment, 2002, 83 : 414-- 430.
  • 8Verhoef W. Light Scattering by Leaf Layers with Application to Canopy Reflectance Modeling: the SAIL Model [ J ]. Remote Sensing of Environment, 1984, 16 : 125--141.
  • 9Narendra S Goel, Richard L Thompson. Inversion of Vegetation Canopy Reflectance Models for Estimating Agronomic Variables. IV. Total Inversion of the SAIL Model [ J ]. Remote Sensing of Environment, 1984, 15: 237--253.
  • 10Fang H L, Liang S L, Andres Kuusk. Retrieving Leaf Area Index Using a Genetic Algorithm with a Canopy Radiative Transfer Model[ J]. Remote Sensing of Environment, 2003, SS : 257 --270.

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