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Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland

Science china Earth sciences 2010年第S1期53卷 26-33页

作者： CHEN Wei1,2,CAO ChunXiang1,HE QiSheng1,2,GUO HuaDong3,ZHANG Hao1,2,LI RenQiang4,ZHENG Sheng1,2,XU Min1,2,GAO MengXu1,2,ZHAO Jian1,2,LI Sha1,NI XiLiang1,2,JIA HuiCong1,JI Wei1,TIAN Rong1,2,LIU Cheng1,2,ZHAO YuXing5 & LI JingLu6 1 State key laboratory of Remote Sensing Science,Jointly Sponsored by the institute of Remote Sensing Applications of chinese academy of sciences and beijing Normal University,beijing 100101,china 2 Graduate University of chinese academy of sciences,beijing 100049,china 3 Center for Earth observation and Digital Earth,chinese academy of sciences,beijing 100190,china 4 china key laboratory of ecological network observation and modeling,institute of geographical sciences and natural resources research,chinese academy of sciences,beijing 100101,china 5 Ordos Forestry Sand Control Science institute,Dongsheng 017000,china 6 Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen 017300,china State key laboratory of Remote Sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate University of chinese academy of sciences Beijing China Center for Earth observation and Digital Earth Chinese Academy of Sciences Beijing China china key laboratory of ecological network observation and modeling Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Ordos Forestry Sand Control Science institute Dongsheng China Inner Mongolia Biomass Thermoelectricity Limited Company Wushen China

The leaf area index(LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the *** addition,it is used by most process-oriented ecosystem *** paper investigates the potential of HJ-1 CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us ***(Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric *** was extracted using the threshold of the normalized difference vegetation index,with which water bodies and farmland were separated,in combination with a vegetation map of the People's Republic of china(1:1000000).Using the geometric-optical model,we derive the per-pixel reflectance as a simple linear combination of two components,namely sunlit background and *** fraction of sunlit background is related to the shrub *** the support of HJ-1 CCD data,we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ *** addition,we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub *** total,18 sample plots collected in Wushen Banner of Inner Mongolia are used for *** results of the shrub LAI show good agreement with R2 of 0.817 and a root-mean-squared error of 0.173.

关键词： shrub leaf area index inversion HJ-1 data geometric-optical model MODTRAN Mu Us Sandland

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GIS and ANN model for landslide susceptibility mapping

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Journal of geographical sciences 2001年第3期11卷 374-381页

作者： XU Zeng-wang (State key laboratory of resources and Environment Information System, institute of Geographic sciences and natural resources research, CAS, beijing 100101, china) State key laboratory of resources and Environment Information System Institute of Geographic Sciences and Natural Resources Research CAS

Landslide hazard is as the probability of occurrence of a potentially damaging landslide phenomenon within specified period of time and within a given area. The susceptibility map provides the relative spatial probability of landslides occurrence. A study is presented of the application of GIS and artificial neural network model to landslide susceptibility mapping, with particular reference to landslides on natural terrain in this paper. The method has been applied to Lantau Island, the largest outlying island within the territory of Hong Kong. A three-level neural network model was constructed and trained by the back-propagate algorithm in the geographical database of the study area. The data in the database includes digital elevation modal and its derivatives, landslides distribution and their attributes, superficial geological maps, vegetation cover, the raingauges distribution and their 14 years 5-minute observation. Based on field inspection and analysis of correlation between terrain variables and landslides frequency, lithology, vegetation cover, slope gradient, slope aspect, slope curvature, elevation, the characteristic value, the rainstorms corresponding to the landslide, and distance to drainage Une are considered to be related to landslide susceptibility in this study. The artificial neural network is then coupled with the ArcView3.2 GIS software to produce the landslide susceptibility map, which classifies the susceptibility into three levels: low, moderate, and high. The results from this study indicate that GIS coupled with artificial neural network model is a flexible and powerful approach to identify the spatial probability of hazards.

关键词： GIS artificial neural network model landslide susceptibility mapping

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Saline-alkali land in the Yellow River Delta: amelioration zonation based on GIS

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Journal of geographical sciences 2001年第3期11卷 313-320页

作者： GUAN Yuan-xiu, LIU Gao-huan, WANG Jin-feng (State key laboratory of resources and Environment Information System, institute of Geographic sciences and natural resources research, CAS, beijing 100101, china) State key laboratory of resources and Environment Information System Institute of Geographic Sciences and Natural Resources Research CAS

Soil salinization is one of the major land degradation types and has greatly influenced sustainable agricultural development. Zonation of saline-alkali land is the precondition for effective amelioration. The present situation of saline-alkali land is monitored by remote sensing image processing. Causes for land salinization are analyzed, especially the two key factors, ground water depth and its mineralization degree, are analyzed by using long-term observation data. Previously, zonation of saline-alkali soil was made descriptively and artificially. Based on the present situation of saline-alkali land, ground water depth and ground water mineralization degree, the zonation of saline-alkali land for amelioration in the Yellow River Delta was completed quantitatively. Four different types of saline-alkali land amelioration zones are delineated, namely, easy ameliorated zone, relatively difficult ameliorated zone, difficult ameliorated zone and unfavorable ameliorated zone. Countermeasures for ameliorating saline-alkali soils are put forward according to ecological conditions of different saline-alkali land zones.

关键词： GIS the Yellow River Delta saline-alkali land zonation

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中国科学院生态系统网络观测与模拟重点实验室CERN综合研究中心研究成果与发展

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自然资源学报 2010年第9期25卷 1458-1467页

作者： Synthesis research Center of chinese Ecosystem research network,CAS(institute of Geographic sciences and natural resources research,CAS,beijing 100101,china) 中国科学院地理科学与资源研究所北京100101

介绍了中国生态系统研究网络(CERN)综合研究中心成立以来的发展历程和主要研究成果,以及未来研究方向及预期发展。取得的代表性研究成果主要有:CERN动态监测数据与生态系统空间信息数据管理和共享系统的开发、陆地生态系统碳和水热通量... 详细信息

介绍了中国生态系统研究网络(CERN)综合研究中心成立以来的发展历程和主要研究成果,以及未来研究方向及预期发展。取得的代表性研究成果主要有:CERN动态监测数据与生态系统空间信息数据管理和共享系统的开发、陆地生态系统碳和水热通量观测研究、陆地生态系统碳储量的时空格局特征研究、陆地生态系统多尺度模拟综合集成研究和青藏高原生态系统格局与全球变化相互作用关系研究等。未来的研究方向主要集中在陆地生态系统碳氮水循环及其耦合,区域碳汇功能动态,生态敏感区、脆弱区和过渡区对全球气候变化的响应与适应,生态监测、模拟与生态信息应用以及全球气候变化主要因子对生态系统关键过程的影响。未来除了履行CERN综合研究中心的基本职能外,争取在以上研究方向取得有国际影响的开拓性研究成果。

关键词： CERN 综合研究中心研究成果陆地生态系统

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Impacts of climate change and grazing intensity on soil organic carbon in alpine meadow

Impacts of climate change and grazing intensity on soil orga...

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2011 International Conference on Business Management and Electronic Information(BMEI 2011)

作者： Xiaojia Li 1 2 Xianzhou Zhang 1 Hongtao Jiang 3 Qinglong Ma 4 Zhenxi Shen 1 Yuzhi Fan 1 2 Wei Yan 1 2 1 key laboratory of Ecosystem network observation and modeling institute of Geographic sciences and natural resources research chinese academy of sciences beijing china 2 Graduate University of chinese academy of Science beijing china 3 School of Geography beijing Normal University beijing china 4 NO.2 Middle School of Xilingol League Xilinhot Inner Mongolia china

In this paper,soil organic carbon was simulated in the next 50 years with CENTURY model in different climate scenarios at Damxung alpine meadow *** result shows that temperature and precipitation are the main contributor to the changes of soil organic *** in temperature and precipitation can reduce the accumulation of soil organic carbon resulting in the release of soil *** results are consistent in three climate change scenarios （temperature and precipitation increasing,temperature increasing and precipitation unchangeable,temperature unchangeable and precipitation increasing）.The content of soil organic carbon decreased,only slightly difference in extent in the three *** intensity was also a main factor to affect soil organic carbon and the influence on soil organic fractions was different.

关键词： soil organic carbon climate change CENTURY model alpine meadow

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