检索结果-南通市图书馆

Science China(Information Sciences) 2011年第1期54卷 197-203页

作者： GENG XiuRui1,ZHAO YongChao1,LIU SuHong2 & WANG FuXiang3.1key laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics,Chinese Academy of Sciences,Beijing 100080,China 2State key laboratory of Remote Sensing Science,Jointly Sponsored by Beijing normal university and the Institute of Remote Sensing Applications of Chinese Academy of Sciences, School of geography,Beijing normal university,Beijing 100875,China 3.chool of Electronics and Information Engineering,Beihang university,Beijing 100191,China 1. key laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100080 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences School of Geography Beijing Normal University Beijing 100875 China3. School of Electronics and Information Engineering Beihang University Beijing 100191 China

This paper gives the definition of the high-dimensional cross product and its calculation by extending the 3.D cross product definition into the high-dimensional vector *** on the properties of the cross product,the volume variance index(VVI)is proposed to be used in extracting automatically the endmembers of the hypherspectral imagery which eliminates the shortcoming of the traditional method of using simplex only where the extraction results were easily impacted by the abnormal pixels.A case study of endmembers extraction experiment using the VVI method with the AVIRIS data for Cuprite has shown a very good result.

关键词： endmember simplex hyperspectral imagery cross product

Estimating surface evapotranspiration using combined MODIS and CBERS-02 data

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2005年第S2期48卷 145-160页

作者： XIN Xiaozhou1,2, LIU Qinhuo1, TANG Yong1,3. TIAN Guoliang1, GU Xingfa1, LI Xiaowen1,2, ZHENG Hongsheng4 & CHEN Jiayi4 1. State key laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 2. Research Center for Remote Sensing and GIS, Department of geography, Beijing {3. university, Beijing 100875, China 3. Graduate university of Chinese Academy of Sciences, Beijing 10003., China 4. Department of Atmospheric Physics, Peking university, Beijing 100871, China 1. State key laboratory of Remote Sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences 100101 Beijing China2. Research Center for Remote Sensing and GIS Department of Geography Beijing Normal University 100875 Beijing China3. Graduate University of Chinese Academy of Sciences 100039 Beijing China4. Department of Atmospheric Physics Peking University 100871 Beijing China

Spatial scale error is one of the most serious problems in the estimates of land surface heat fluxes of sensible and latent from satellite-borne data such as MODIS 1km resolution reflectance and emissive data. One of the feasible and economic ways to decrease the spatial scale error is to use high resolution land use class data together with the MODIS data. CBERS-02 data were used to produce land use class of Baiyangdian area, Hebei Province, China in the autumn of 2004. The area ratio of each class in MODIS pixel was calculated, and used to derive the heat fluxes of the mixed pixel. The results showed that the estimated heat fluxes of soil, sensible and latent have been changed remarkably after using the high resolution land class data. It could be concluded from the comparison between simulated and ground-measured fluxes as well as the theoretical analysis that high resolution land class data are useful to diminishing the scale error of heat fluxes estimated from low resolution satellite data.

关键词： surface evapotranspiration spatial scale error MODIS CBERS land class.

Spatial patterns of ecosystem carbon residence time in Chinese forests

在线全文

学校读者我要写书评

暂无评论

中国科学：地球科学英文版 2010年第8期53卷 1229-1240页

作者： ZHOU Tao1,2, SHI PeiJun1,2, JIA GenSuo3. LI XiuJuan1,2 & LUO YiQi4 1 State key laboratory of Earth Surface Processes and Resource Ecology, Beijing normal {3., Beijing 100875, China 2 Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing 100875, China 3.key laboratory of regional Climate-Environment Research for Temperate East Asia, Chinese Academy of Sciences, Beijing 100029, China 4 Department of Botany and Microbiology, {3. of Oklahoma, Norman, OK 73.19, USA 1. State key laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Beijing 100875 China2. Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs & Ministry of Education Beijing 100875 China3. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia Chinese Academy of Sciences Beijing 100029 China4. Department of Botany and Microbiology University of Oklahoma Norman OK 73019 USA

Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3.years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (3..1 and 3..3.years, respectively), and the evergreen broadleaf forest had the lowest value (3..7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.

关键词： carbon residence time carbon cycle forest ecosystem data-model fusion inverse modeling genetic algorithm

Information flow and controlling in regularization inversion of quantitative remote sensing

在线全文

学校读者我要写书评

暂无评论

Science China Earth Sciences 2005年第1期48卷 74-83页

作者： YANG Hua, XU Wangli, ZHAO Hongrui, CHEN Xue & WANG Jindi Research Center for Remote Sensing and GIS, School of geography, Beijing normal university, State {3. laboratory of Remote Sensing Science, Beijing {3. laboratory for Remote Sensing of Environment and Digital Cities, Beijing 100875, China Department of Mathematics, Beijing normal university, Beijing 100875, China 1. Research Center for Remote Sensing and GIS School of Geography Beijing Normal University State Key Laboratory of Remote Sensing Science Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities 100875 Beijing China 2. Department of Mathematics Beijing Normal University 100875 Beijing China

In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.

关键词： regularization inversion, information flow, Shannon entropy decrease, information matrix.

Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

在线全文

学校读者我要写书评

暂无评论

Science China Earth Sciences 2010年第S1期53卷 16-25页

作者： GUO ZhiFeng1,CHI Hong1,2 & SUN GuoQing1,3.1State key laboratory of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing normal {3.,Institute of Remote Sensing Applications,Chinese Academy of Sciences,Beijing 100101,China 2Graduate {3. of Chinese Academy of Sciences,Beijing 100049,China 3.epartment of geography {3. of Maryland,College Park,MD 20742,USA 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 Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China2. Graduate University of Chinese Academy of Sciences Beijing 100049 China3. Department of Geography University of Maryland College Park MD 20742 USA

The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon *** aboveground biomass(AGB) is an important component in the land surface carbon *** this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory *** resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf *** models were used to estimate biomass for all GLAS footprints of forest located in the study *** GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 *** data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t *** pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this *** was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estim

关键词： Disaster and Environment Monitoring and Forecast Satellite ICESat GLAS waveform boreal forest forest aboveground biomass multiple linear regression

Principle of small target detection for hyperspectral imagery

在线全文

学校读者我要写书评

暂无评论

Science China Earth Sciences 2007年第8期50卷 1225-1231页

作者： GENG XiuRui1,2,3.& ZHAO YongChao2,3.4 1 Research Center for Remote Sensing and GIS, Department of geography, Beijing normal university, Beijing 100875, China 2 State {3. laboratory of Remote Sensing Science, Chinese Academy of Sciences, Beijing 100101, China 3.Institute of Erectronics, Chinese Academy of Sciences, Beijing 100080, China 4 Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem Sciences university of California Berkeley, CA 94720-3.14, USA 1. Research Center for Remote Sensing and GIS Department of Geography Beijing Normal University Beijing 100875 China 2. State key laboratory of Remote Sensing Science Chinese Academy of Sciences Beijing 100101 China 3. Institute of Erectronics Chinese Academy of Sciences Beijing 100080 China 4. Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem Sciences University of California Berkeley CA 94720-3114 USA

This paper generalizes the progress of algorithms in small target detection for hyperspectral imaging, and finds that whitening the image is the key point of many methods in small target detection. An al-gorithm is presented to detect desired targets by converting large targets into small ones based on the weighted sample autocorrelation matrix.

关键词： hyperspectral whiten target detection

Synchronous estimation of DTM and fractional vegetation cover in forested area from airborne LIDAR height and intensity data

在线全文

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2008年第S2期51卷 176-187页

作者： BAO YunFei1,2,CAO ChunXiang1,ZHANG Hao1,CHEN ErXue3.HE QiSheng1,2,HUANG HuaBing1,LI ZengYuan3.LI XiaoWen1,4 & GONG Peng1 1 State key laboratory of Remote Sensing Science,jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing normal {3.,Beijing 100101,China 2 Graduate {3. of the Chinese Academy of Sciences,Beijing 100049,China 3.Institute of Forest Resource Information Technique,the Chinese Academy of Forestry,Beijing 100091,China 4 Research Center for Remote Sensing and GIS,Department of geography and Beijing key laboratory for Remote Sensing of Environment and Digital Sites,Beijing normal {3.,Beijing 100875,China State key laboratory of Remote Sensing Science jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China Graduate university of the Chinese Academy of Sciences Beijing 100049 China Institute of Forest Resource Information Technique the Chinese Academy of Forestry Beijing 100091 China Research Center for Remote Sensing and GIS Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Sites Beijing Normal University Beijing 100875 China

We proposed a method to separate ground points and vegetation points from discrete return,small footprint airborne laser scanner data,called skewness change *** method,which makes use of intensity of laser scanner data,is especially applicable in steep,and forested *** does not take slope of forested area into account,while other algorithms consider the change of slope in steep forested *** ground points and vegetation points can be used to estimate digital terrain model(DTM) and fractional vegetation cover,respectively.A few vegetation points which were classified into the ground points were removed as noise before the generation of *** method was tested in a test area of 10000 square meters.A LiteMapper -5600 laser system was used and a flight was carried out over a ground of 700―800 *** this tested area,a total number of 1546 field measurement ground points were measured with a total station TOPCON GTS-602 and TOPCON GTS -7002 for validation of DTM and the mean error value is -18.5 cm and the RMSE(root mean square error) is ±20.9 cm.A data trap sizes of 4m in diameter from airborne laser scanner data was selected to compute vegetation fraction *** of fractional vegetation cover was carried out using 15 hemispherical photographs,which are georeferenced to centimeter accuracy by differential *** gap fraction was computed over a range of zenith angles 10° using the gap light analyzer(GLA) from each hemispherical *** R2 for the regression of fractional vegetation cover from these ALS data and the respective field measurements is *** this study presents a method for synchronous estimation of DTM and fractional vegetation cover in forested area from airborne LIDAR height and intensity data.

关键词： LIDAR intensity skewness synchronous DTM fractional vegetation cover

The environmental signal of an early Holocene pollen record from the Shiyang River basin lake sediments, NW China

在线全文

学校读者我要写书评

暂无评论

Chinese Science Bulletin 2002年第4期47卷 267-273页

作者： ZHU Yan, CHEN Fahu & Madsen DavidCollege of geography and Environment, Northwest normal university, Lanzhou 73.070, China National {3. laboratory of West Environmental System, Lanzhou university, Lanzhou 73.000, China Utah Geological Surv College of geography and Environment Northwest Normal University National key laboratory of West Environmental System Lanzhou University

Pollen analyses of 85 samples from the San-jiaocheng section well along the margin of a palaeolake at the end of the Shiyang River, NW China, show that Picea and Sabina dominate the pollen assemblage. Together they reach as high as 40%-60%, with the percentage of Picea varying inversely with that of Sabina. Similar results were obtained from another section in the Shiyang River drainage. Using modern ecological habitat relationship analogues, pol-len transport characteristics, and the overall pollen assem-blage, we propose that both Picea and Sabina pollen were transported by the river from the mountains at the upper reaches of the Shiyang River, and that the assemblage is more indicative of changes in upland vegetation than of local conditions near the section. This interpretation is supported by pollen data derived from surface samples, water samples, and riverbed samples. Using a moisture indicator (the Picea to Sabina ratio) and calculated pollen concentrations, we identify a series of

关键词： NW China The environmental signal of an early Holocene pollen record from the Shiyang River basin lake sediments

A study on determining the location of groundwater divide using a mathematical morphology method

在线全文

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2006年第z2期49卷 141-148页

作者： PAN Yun, GONG Huili, DUAN Fuzhou & HU Zhuowei key laboratory of 3. Information Acquisition and Application, Ministry of Education, Capital normal {3., Beijing 10003., China key laboratory of Resource Environment and GIS of Beijing, Capital normal {3., Beijing 10003., China Capital normal Univ Minist Educ Key Lab D Informat Acquisit & Applicat 3 Beijing 100037 Peoples R China Capital normal Univ Key Lab Resource Environm Beijing 100037 Peoples R China Capital normal Univ GIS Beijing Beijing 100037 Peoples R China

Placement of a groundwater divide indicates sink areas and spatial distribution, knowledge of which helps in the mapping of regional aquifer properties and the management of groundwater resources. By applying mathematical morphology to a conceptual model of a watershed and characteristic erosion and dilation operations, this paper proposes a structuring element with which to extract the shape and location of groundwater divide. With due consideration to watershed linearity, a structuring element with three origins is designed to connect watershed points. After erosion, closing, and dilation operations, the groundwater divide is determined; the results indicate this method's feasibility and accuracy.

关键词： groundwater divide, mathematical morphology, structuring element.

Cloning, sequencing and expression of the coat protein gene of Cocksfoot mottle virus

在线全文

学校读者我要写书评

暂无评论

Progress in Natural Science:Materials International 2007年第2期17卷 222-225页

作者： DONG Zhi, GUO Xiaoyu, ZHANG Hailong and ZHANG Feiyun ( College of Life Science, Capital normal university, Beijing 10003., China College of Resources Environment and Tourism, Capital normal university, Beijing 10003., China Beijing key laboratory for Resources Environment and geography Information System, Beijing 10003., China) [a]College of Life Science Capital Normal University Beijing China [b]College of Resources Environment and Tourism Capital Normal University Beijing China [c]Beijing key laboratory for Resources Environment and geography Information System Beijing China

The coat protein (CP) gene of Cocksfoot mottle virus (CfMV) was amplified by RT-PCR and inserted into expression vector pGEX-4T-1, and the resulting plasmid was designated as pGEXCfMV-JANCP. The fusion protein GST-CP was expressed in BL21 (DE3. pLysS after IPTG induction. The results of SDS-PAGE and Western blot analysis showed that the CfMV-CP gene was efficiently expressed in E. coli BL21 (DE3. pLysS through IPTG induction and the 56.0 kD protein was obtained.

关键词： Cocksfoot mottle virus sequence analysis prokaryotic expression.