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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chao Zhang Chunjiang Zhao Liangyun Liu Yuchun Pan Xia Jing Wanhui Chen |
| Copyright Year | 2004 |
| Description | Author affiliation: Nat. Eng. Res. Center for Inf. Technol. in Agric., Beijing, China (Chao Zhang; Chunjiang Zhao; Liangyun Liu; Yuchun Pan; Xia Jing; Wanhui Chen) |
| Abstract | With the urbanizing development of Beijing, the planting area and spatial distribution structure of Beijing suburb crops are changing constantly. Because the TM (Thematic Mapper) images of Beijing area during 2003 summer suffered from weather conditions, such as cloud or haze, it is difficult to obtain the satisfying classification with only one kind of remote sensing data. To get the first data of the exact area and spatial distribution of Beijing crops, a perfect classification strategy is designed in This work. The images of 2003's TM/ETM+ (Enhanced Thematic Mapper Plus) in comparative better weather conditions, MODIS (Moderate Resolution Imaging Spectroradiometer), NDVI (Normalized Difference Vegetation Index) standard products in 2003 and DEM (Digital Elevation Model) at 30 m spatial resolution of Beijing area are adopted. The classification system for main crops in Beijing is constructed which includes winter wheat, maize, soybean, clover, garden, orchard, etc. Based on the phenological features of the main crops, the different crops extracting plan is constructed respectively. The orchard and vegetable in greenhouse planting information are from the supervised classification with maximum likelihood methods. By means of the decision tree classification function of the ENVI (The Environment for Visualizing Images) software, the winter wheat and clover planting information are extracted by the logic operation algorithm among the 4 NDVI data from the TM/ETM+ images adopted in This work while the spring maize and soybean are extracted with the logic algorithm with MODIS NDVI. The results indicated that this classification strategy can not only improve the classification precision, but also decrease the post classification work. |
| Starting Page | 4004 |
| Ending Page | 4007 |
| File Size | 398016 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780387422 |
| DOI | 10.1109/IGARSS.2004.1370006 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-09-20 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Remote monitoring Crops MODIS Data mining Logic Software algorithms Clouds Remote sensing Vegetation mapping Digital elevation models |
| Content Type | Text |
| Resource Type | Article |
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