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| 基于MODIS温度/植被指数的东北地区土地覆盖分类 | |
| 引用本文： | 宫攀,陈仲新,唐华俊,张凤荣,张明伟.基于MODIS温度/植被指数的东北地区土地覆盖分类[J].农业工程学报,2006,22(9):94-99. |
| 作者姓名： | 宫攀 陈仲新 唐华俊 张凤荣 张明伟 |
| 作者单位： | 1. 中国农业大学资源与环境学院土地资源管理系,北京,100094;农业部资源遥感与数字农业重点实验室,北京,100081;中国农科院农业资源与农业区划研究所,北京,100081 2. 农业部资源遥感与数字农业重点实验室,北京,100081;中国农科院农业资源与农业区划研究所,北京,100081 3. 中国农业大学资源与环境学院土地资源管理系,北京,100094 4. 农业部资源遥感与数字农业重点实验室,北京,100081;中国农科院农业资源与农业区划研究所,北京,100081;华中农业大学资源与环境学院,武汉,430070 |
| 基金项目： | 科技部科技基础条件平台建设计划 |
| 摘 要： | 该文采用MODIS NDVI时序数据对东北区土地覆盖分类进行研究，以验证MODIS区域土地覆盖制图的可靠性。通过试验发现经过Savizky-Golay滤波处理能有效去除云、缺失数据及异常值的影响，使得NDVI时序曲线能更好的反映植被季相变化特征，分类结果表明NDVI时序数列能较好的区分植被与非植被、草本(一年生)与木本(多年生)覆盖类型。但研究区内一年一熟的农作物与高盖度草地、落叶针叶林与落叶阔叶林具有相似的物候特征，混分现象比较严重。该研究通过添加地表温度(land surface temperature, LST)数据解决这一问题，利用所得温度/植被指数TVI对研究区进行土地覆盖分类。所得结果用363个野外调查样区进行验证，NDVI及TVI时序数据的分类精度分别为62.26％与71.63％。结果表明TVI比NDVI对土地覆盖类型中的植被类型识别更有效。 |
| 关 键 词： | 土地覆盖分类 |
| 文章编号： | 1002-6819（2006）09-0094-06 |
| 收稿时间： | 2006-01-16 |
| 修稿时间： | 2006-01-162006-05-11 |
Land cover classification based on MODIS temperature-vegetation index time-series data in Northeastern China |
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| Gong Pan,Chen Zhongxin,Tang Huajun,Zhang Fengrong and Zhang Mingwei.Land cover classification based on MODIS temperature-vegetation index time-series data in Northeastern China[J].Transactions of the Chinese Society of Agricultural Engineering,2006,22(9):94-99. | |
| Authors: | Gong Pan Chen Zhongxin Tang Huajun Zhang Fengrong and Zhang Mingwei |
| Institution: | College of Resource & Environment, China Agricultural University, Beijing 100094, China;Key Laboratory of Resource Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;Institute of Agricultural Resource & Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;Key Laboratory of Resource Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;Institute of Agricultural Resource & Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;Key Laboratory of Resource Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;Institute of Agricultural Resource & Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;College of Resource & Environment, China Agricultural University, Beijing 100094, China;Key Laboratory of Resource Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;Institute of Agricultural Resource & Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;College of Resource & Environment, Huazhong Agricultural University, Wuhan 430070, China |
| Abstract: | The authors studied the regional land cover classification based on MODIS time-series data. The study area is located in Northeastern China, in which there are relative homogeneous land cover types. Savitzky-Golay filter was used to reduce the effect on cloud overlay, loss of data and abnormal data. Classification results proved that NDVI time-series data could be used to differentiate better the woody(perennial) cover from the herbaceous(annual) cover, and vegetation from non-vegetation types depending on the seasonal differences. Grassland and cropland (one crop per-year), needle-leaf deciduous forest and broadleaf deciduous forest had similar phenological characteristics which were easy to be confused. However LST(land surface temperature) data was added to resolve this problem. The overall land cover classification accuracies using NDVI and TVI(temperature-vegetation index) were 62.26% and 71.63% respectively according to the validated results with 363 ground truth survey samples. The results show that the TVI includes more information and is more sensitive to land cover than NDVI, and MODIS data have their own advantages in the regional land cover mapping. |
| Keywords: | MODIS NDVI LST TVI |
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