Remote-sensing based monitoring of planting structure and growth condition of major crops in Northeast China

被引：0

作者：

Huang Q. ^{[1
,2
]}

Tang H. ^{[1
,2
]}

Zhou Q. ^{[1
]}

Wu W. ^{[1
]}

Wang L. ^{[1
]}

Zhang L. ^{[1
]}

机构：

[1] Key Laboratory of Resource Remote Sensing and Digital Agriculture, Ministry of Agriculture, Institute of Agricultural Resources and Regional Planning of Chinese Academy of Agricultural Sci.

[2] Hulunber Grassland Ecosystem Observation and Research Station

来源：

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2010年 / 26卷 / 09期

关键词：

Accuracy assessment; Crops; Growth; MODIS data; Monitoring; NDVI; Northeast China; Planting structure; Remote sensing;

D O I：

10.3969/j.issn.1002-6819.2010.09.037

中图分类号：

学科分类号：

摘要：

Taking the main crops in Northeast China as an example, large-scale crop planting areas automatic identification methods were researched based on time-series of MODIS NDVI Datasets in this paper. The characteristics of NDVI time series of spring wheat, spring corn, soybeans and rice in Northeast China were firstly analyzed, and then the threshold values of extracting different crops were set and the extraction models of above-mentioned four kinds of crops were established, and finally the spatial distribution of these four crops of 2009 were obtained. MODIS data of Northeast China of 2009 were used to monitor the growth condition of the four kinds of crops, and the growth condition were compared with the average crop growth of last five years. The results showed that the extraction accuracy of crops planting structure was more than 87% compared with what with years of average statistical data, and crops growth condition showed different characteristics both in spatial and temporal. Research shows that it is feasible to extract different crops planting structure and monitor crops growth condition in large scale using MODIS data, which provides effective ways for large scale crops planting structure extraction in China agriculture remote sensing monitoring system.

引用

页码：218 / 223

页数：5

共 23 条

[1] Liu H., The introduction of MARS plan of European commission and Chinese agriculture remote sensing application, Chinese Agricultural Resources and Regional Planning, 20, 3, pp. 55-57, (1999)
[2] Pradhan S., Crop area estimation using GIS, remote sensing and area frame sampling, International Journal of Applied Earth Observation and Geoinformation, 3, 1, pp. 86-92, (2001)
[3] Liu H., Jin M., Gong W., Applications of remote sensing in agriculture in the United States, Chinese Agricultural Resources and Regional Planning, 20, 2, pp. 56-60, (1999)
[4] The LACIE crop years - An assessment of the crop conditions experienced in the three years of LACIE
[5] Multiple Frame Agricultural Surveys. Volume II: Agricultural Surveys Programs Based on Area Frame or Dual Frame (Area and List) Sample Designs, (1998)
[6] Treitz P., Rogan J., Remote sensing for mapping and monitoring land-cover and land-use change: An introduction, Progress in Planning, 61, pp. 269-279, (2004)
[7] Loveland T.R., Reed B.C., Brown J.F., Et al., Development of a global land cover characteristics database and IGBP Discover from 1-km AVHRR Data, International Journal of Remote Sensing, 21, 6-7, pp. 1303-1330, (2000)
[8] Garedew E., Sandewall M., Soderberg U., Et al., Land-use and land-cover dynamics in the central rift valley of ethiopia, Environmental Management, 44, 4, pp. 683-694, (2009)
[9] Fu Y., Xiao J., Xiao R., Et al., Analysis and simulation prediction on LUCC of Xining city based on RS and GIS, Transactions of the CSAE, 25, 7, pp. 211-218, (2009)
[10] Zou J., Chen Y., Uchida S., Et al., Method for extracting winter wheat area using Terra MODIS data and its accuracy analysis, Transactions of the CSAE, 23, 11, pp. 195-200, (2007)

← 1 2 3 →