摘要
该文采用M OD IS N DV I时序数据对东北区土地覆盖分类进行研究,以验证M OD IS区域土地覆盖制图的可靠性。通过试验发现经过Sav izky-G o lay滤波处理能有效去除云、缺失数据及异常值的影响,使得N DV I时序曲线能更好的反映植被季相变化特征,分类结果表明N DV I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 tem perature,LST)数据解决这一问题,利用所得温度/植被指数TV I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,N DV I及TV I时序数据的分类精度分别为62.26%与71.63%。结果表明TV I比N DV I对土地覆盖类型中的植被类型识别更有效。
The authors studied the regional land cover classification based on MODIS time-series data. Tne stuoy 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.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2006年第9期94-99,F0004,共7页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家科技基础条件平台工作项目(2004DKA10060)资助
