检索结果-南通市图书馆

Multi-year monitoring of paddy rice planting area in Northeast China using MODIS time series data

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2013年第10期14卷 934-946页

作者： jing-jing SHI jing-feng huang feng ZHANG Institute of Agricultural Remote Sensing and Information Application Zhejiang University Key Laboratory of Agricultural Remote Sensing and Information System of Zhejiang Province Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health Zhejiang University

e The objective of this study was to investigate the tempo-spatial distribution of paddy rice in Northeast China using moderate resolution imaging spectroradiometer （MODIS） data. We developed an algorithm for detection and estimation of the transplanting and flooding periods of paddy rice with a combination of enhanced vegetation index （EVI） and land surface water index with a central wavelength at 2130 nm （LSW12130）. In two intensive sites in Northeast China, fine resolution satellite imagery was used to validate the performance of the algorithm at pixel and 3x3 pixel window levels, respectively. The commission and omission errors in both of the intensive sites were approximately less than 20%. Based on the algorithm, annual distribution of paddy rice in Northeast China from 2001 to 2009 was mapped and analyzed. The results demonstrated that the MODIS-derived area was highly correlated with published agricultural statistical data with a coefficient of determination （R^2） value of 0.847. It also revealed a sharp decline in 2003, especially in the Sanjiang Plain located in the northeast of Heilongjiang Province, due to the oversupply and price decline of rice in 2002. These results suggest that the approaches are available for accurate and reliable monitoring of rice cultivated areas and variation on a large scale.

关键词： Paddy rice Moderate resolution imaging spectroradiometer(MODIS) Northeast China Enhanced vegetation index Land surface water index

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Discrimination of rice panicles by hyperspectral reflectance data based on principal component analysis and support vector classification

引用

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2010年第1期11卷 71-78页

作者： Zhan-yu LIU jing-jing SHI Li-wen ZHANG jing-feng huang Institute of Agricultural Remote Sensing and Information System Application Zhejiang University Hangzhou 310029 China Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health Zhejiang University Hangzhon 310029 China Key Laboratory of Agricultural Remote Sensing and lnformation System in Zhejiang Province Hangzhou 310029 China

Detection of crop health conditions plays an important role in making control strategies of crop disease and insect damage and gaining high-quality production at late growth stages. In this study, hyperspectral reflectance of rice panicles was measured at the visible and near-infrared regions. The panicles were divided into three groups according to health conditions： healthy panicles, empty panicles caused by Nilaparvata lugens St^l, and panicles infected with Ustilaginoidea virens. Low order derivative spectra, namely, the first and second orders, were obtained using different techniques. Principal component analysis （PCA） was performed to obtain the principal component spectra （PCS） of the foregoing derivative and raw spectra to reduce the reflectance spectral dimension. Support vector classification （SVC） was employed to discriminate the healthy, empty, and infected panicles, with the front three PCS as the in- dependent variables. The overall accuracy and kappa coefficient were used to assess the classification accuracy of SVC. The overall accuracies of SVC with PCS derived from the raw, first, and second reflectance spectra for the testing dataset were 96.55%, 99.14%, and 96.55%, and the kappa coefficients were 94.81%, 98.71%, and 94.82%, respectively. Our results demonstrated that it is feasible to use visible and near-infrared spectroscopy to discriminate health conditions of rice panicles.

关键词： Rice panicle Principal component analysis (PCA) Support vector classification (SVC) Hyperspectra reflectance Derivative spectra

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A tasseled cap transformation for CBERS-02B CCD data

引用

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2011年第9期12卷 780-786页

作者： Li SHENG jing-feng huang Xiao-lu TANG Institute of Agricultural Remote Sensing and Information Application Zhejiang UniversityHangzhou 310029China Key Laboratory of Agricultural Remote Sensing and Information System of Zhejiang Province Hangzhou 310029China Yuhang Branch Bureau of Planning Hangzhou Urban Planning BureauHangzhou 311100China

The tasseled cap transformation of remote sensing data has been widely used in agriculture,forest,ecology,and *** this paper,tasseled cap transformation coefficients appropriate for data from a new sensor(China & Brazil Earth Resource Satellite(CBERS-02B)) are *** first three components after transformation captured 98% of the four-band variance,and represent the physical characteristics of brightness(coefficients:0.509,0.431,0.330,and 0.668),greenness(coefficients:0.494,0.318,0.324,and 0.741),and blueness(coefficients:0.581,0.070,0.811,and 0.003),*** hope these results will enhance the application of CBERS-02B charge-coupled device(CCD) data in the areas of agriculture,forest,ecology,and landscape.

关键词： Tasseled cap transformation CBERS-02B CCD Reflectance factor

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Science Letters:A new quantitative model of ecological compensation based on ecosystem capital in Zhejiang Province,China

引用

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2009年第4期10卷 301-305页

作者： Yan JIN jing-feng huang Dai-liang PENG Institute of Agricultural Remote Sensing and lnformation Application Key Laboratory of Agricultural Remote Sensing and lnformation System of Zhejiang Province Hangzhou 310029 China Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health Zhejiang University Hangzhou 310029 China

Ecological compensation is becoming one of key and multidiscipline issues in the field of resources and environmental management. Considering the change relation between gross domestic product (GDP) and ecological capital (EC) based on remote sensing estimation, we construct a new quantitative estimate model for ecological compensation, using county as study unit, and determine standard value so as to evaluate ecological compensation from 2001 to 2004 in Zhejiang Province, China. Spatial differences of the ecological compensation were significant among all the counties or districts. This model fills up the gap in the field of quantitative evaluation of regional ecological compensation and provides a feasible way to reconcile the conflicts among benefits in the economic, social, and ecological sectors.

关键词： Payment for ecosystem services (PES) Gross domestic product (GDP) Ecological capital (EC) Geospatial distribution

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Identification of Optimal Hyperspectral Bands for Estimation of Rice Biophysical Parameters

引用

Journal of Integrative Plant Biology 2008年第3期50卷 291-299页

作者： Fu-Min Wang jing-feng huang Xiu-Zhen Wang Institute of Agriculture Remote Sensing & Information System Application Zhejiang University Hangzhou 310029 China Institute of Meteorology Zhejiang Province Hangzhou 310029 China

The present study aims to identify the narrow spectral bands that are most suitable for characterizing rice biophysical parameters. The data used for this study come from ground-level hyperspectral reflectance measurements for five rice species at three levels of nitrogen fertilization during the growing period. Reflectance was measured in discrete narrow bands between 350 and 2 500 nm. Observed rice biophysical parameters included leaf area index （LAI）, wet biomass and dry biomass. The stepwise regression method was applied to identify the optimal bands for rice biophysical parameter estimation. This research indicated that combinations of four narrow bands in stepwise regression models explained 69% to 83% variability for LAI, 56% to 73% for aboveground wet biomass and 70% to 83% for leaf wet biomass. An overwhelming proportion of rice information was in a particular portion of near infrared （NIR）（1 100-1 150 nm）, red-edge （700-750 nm）, and a longer portion of green （550-600 nm）. These were followed by the moisture-sensitive NIR （950-1 000 nm）, the intermediate portion of shortwave infrared （SWlR）（1 650-1 700 nm）, and another portion of NIR （1 000-1 050 nm）.

关键词： biophysical parameters hyperspectral rice stepwise regression

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Detection of nitrogen-overfertilized rice plants with leaf positional difference in hyperspectral vegetation index

引用

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2010年第6期11卷 465-470页

作者： Qi-fa ZHOU Zhan-yu LIU jing-feng huang College of Life Sciences Zhejiang University Hangzhou 310058 China College of Environmental and Resource Sciences Zhejiang University Hangzhou 310029 China

The main objective of this work was to compare the applicability of the single leaf(the uppermost leaf L1 and the third uppermost leaf L3) modified simple ratio(mSR705 index) and the leaf positional difference in the vegetation index between L1 and L3(mSR705L1-mSR705L3) in detecting nitrogen(N)-overfertilized rice plants.A field experiment consisting of three rice genotypes and five N fertilization levels(0,75,180,285,and 390 kg N/ha) was conducted at Xiaoshan,Hangzhou,Zhejiang Province,China in *** hyperspectral reflectance(350-2500 nm) and the chlorophyll concentration(ChlC) of L1 and L3 were measured at different *** mSR705L1 and mSR705L3 indices appeared not to be highly sensitive to the N rates,especially when the N rate was high(above 180 kg N/ha).The mean mSR705L1-mSR705L3 across the genotypes increased significantly(P<0.05) or considerably from 180 to 285 kg N/ha treatment and from 285 to 390 kg N/ha treatment at all the ***,use of the difference(mSR705L1-mSR705L3) greatly reduced the influence of the stages and genotypes in assessing the N status with re-flectance *** results of this study show that the N-overfertilized rice plants can be effectively detected with the leaf positional difference in the mSR705 index.

关键词： Rice Nitrogen (N) Overfertilization Leaf position Hyperspectral reflectance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Mapping paddy rice with multi-date moderate-resolution imaging spectroradiometer (MODIS) data in China

引用

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第10期10卷 1509-1522页

作者： Hua-sheng SUN jing-feng huang Alfredo R. HUETE Dai-liang PENG feng ZHANG Institute of Agricultural Remote Sensing and lnformation Application Zhejiang University Hangzhou 310029 China Key Lab of Agricultural Remote Sensing and lnformation System Hangzhou 310029 China MOE Key Lab of Environmental Remediation and Ecological Health Zhejiang University Hangzhou 310029 China Department of Soil Water and Environmental Science University of Arizona Tucson AZ85721 USA Resources and Environment Department Xinjiang Agricultural University Urumchi 830052 China College of Surveying and Mapping Xuzhou Normal University Xuzhou 221116 China

The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in *** rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar *** characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor *** for single,early,and late rice identification were obtained from selected typical test *** algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the *** areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test *** factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were *** not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.

关键词： Remote sensing Moderate-resolution imaging spectroradiometer (MODIS) Enhanced vegetation index (EVI) Land surface water index (LSWI) Paddy rice China

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Assessing the Response of Seasonal Variation of Net Primary Productivity to Climate Using Remote Sensing Data and Geographic Information System Techniques in Xinjiang

引用

Journal of Integrative Plant Biology 2008年第12期50卷 1580-1588页

作者： Dai-Liang Peng jing-feng huang Cheng-Xia Cai Rui Deng Jun-feng Xu Institute of Agriculture Remote Sensing and Information System Application Zhejiang University Hangzhou 310029 China Xinjiang Institute of Meteorology Urumchi 830002 China

Net primary productivity （NPP） is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climatevegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index （NDVI） data and geographic information system （GIS） techniques. The impact of climatic factors （air temperature, precipitation and sunshine percentage） on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1 month as a whole. No correlation was found between NPP and sunshine percentage.

关键词： climate geographic information system techniques net primary productivity remote sensing seasonal variation serial correlation ageing time lag.

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Comparison of Vegetation Indices and Red-edge Parameters for Estimating Grassland Cover from Canopy Reflectance Data

引用

Journal of Integrative Plant Biology 2007年第3期49卷 299-306页

作者： Zhan-Yu Liu jing-feng huang Xin-Hong Wu Yong-Ping Dong Institute of Agriculture Remote Sensing and Information System Application Zhejiang University Hangzhou 310029 China Grassland Research Institute Chinese Academy of Agricultural Science Huhhot 010010 China

There has been a great deal of Interests in the estimation of grassland biophysical parameters such as percentage of vegetation cover （PVC）, aboveground biomass, and leaf-area index with remote sensing data at the canopy scale. In this paper, the percentage of vegetation cover was estimated from vegetation indices using Moderate Resolution Imaging Spectroradiometer （MODIS） data and red-edge parameters through the first derivative spectrum from in situ hypserspectral reflectance data. Hyperspectral reflectance measurements were made on grasslands in Inner Mongolia, China, using an Analytical Spectral Devices spectroradiometer. Vegetation indices such as the difference, simple ratio, normalized difference, renormalized difference, soil-adjusted and modified soil-adjusted vegetation indices （DVI, RVI, NDVI, RDVI, SAVI L=0.5 end MSAVI2） were calculated from the hyperspectral reflectance of various vegetation covers. The percentage of vegetation cover was estimated using an unsupervised spectral-contextual classifier automatically. Relationships between percentage of vegetation cover and various vegetation indices and red-edge parameters were compared using a linear and second-order polynomial regression. Our analysis indicated that MSAVI2 and RVI yielded more accurate estimations for a wide range of vegetation cover than other vegetation indices and red-edge parameters for the linear and second-order polynomial regression, respectively.

关键词： grassland hypserspectral remote sensing percentage of vegetation cover red-edge parameter vegetation index

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Quantifying biochemical variables of corn by hyperspectral reflectance at leaf scale

引用

Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2008年第5期9卷 378-384页

作者： Qiu-xiang YI jing-feng huang Fu-min WANG Xiu-zhen WANG Institute of Remote Sensing and lnformation Technology Zhejiang University Hangzhou 310029 China Institute of Zhejiang Meteorology Hangzhou 310004 China

To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen(N),crude fat(EE) and crude fiber(CF) concentrations,by spectral reflectance and the first derivative reflectance at fresh leaf scale. The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed,and a set of estimation models were established using curve-fitting analyses. Coefficient of determination(R2),root mean square error(RMSE) and relative error of prediction(REP) of estimation models were calculated for the model quality evaluations,and the possible opti-mum estimation models of three biochemical variables were proposed,with R2 being 0.891,0.698 and 0.480 for the estimation models of N,EE and CF concentrations,respectively. The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation,and that the first derivative reflectances at 759 nm,1954 nm and 2370 nm were most suitable to develop the estimation models of N,EE and CF concentrations,respectively. In addition,the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained,especially for nitrogen(r=0.948).

关键词： Biochemical variables Corn The first derivative spectral reflectance Spectral reflectance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：