NDLI: Land Cover Classification Based on Multi-temporal MODIS NDVI and LST in Northeastern China

Content Provider	IEEE Xplore Digital Library
Author	Pan Gong Zhongxin Chen Huajun Tang Fengrong Zhang
Copyright Year	2006
Description	Author affiliation: Coll. of Resource & Environ., China Agric. Univ., Beijing (Pan Gong)
Abstract	This paper investigated the regional land cover classification based on multi-temporal MODIS data. The study area lies in Northeastern China, where there are diverse and relative homogeneous land cover types. Through experiment, NDVI time-series data can be used to distinguish the woody (perennial) and herbaceous (annual), vegetation and non-vegetation categories depending on the seasonal differences. Grassland and cropland (one-crop-per-year), needle-leaf deciduous forest and broad leaf deciduous forest have similar phenological characteristics easy to be confused. We add the LST (land surface temperature) data to resolve this problem. But built-up area and bare land must depend on further information to be divided. Validated results with 363 ground truth filed samples; the result shows that the temperature-vegetation index (TVI) includes more information. The overall land cover classification accuracies with NDVI and TVI are 62.26% and 71.63% respectively. Based on this study, we concluded that TVI is more sensitive to land cover than NDVI, and MODIS data has its strength in the regional land cover mapping.
Starting Page	1149
Ending Page	1152
File Size	321646
Page Count	4
File Format	PDF
ISBN	0780395107
DOI	10.1109/IGARSS.2006.297
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MODIS Vegetation mapping Land surface temperature TV interference Remote sensing Agriculture Educational institutions Computer aided analysis Land surface Productivity
Content Type	Text
Resource Type	Article

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