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Proceedings Paper

A tool for NDVI time series extraction from wide-swath remotely sensed images
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Paper Abstract

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Paper Details

Date Published: 4 September 2015
PDF: 7 pages
Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100T (4 September 2015); doi: 10.1117/12.2186158
Show Author Affiliations
Zhishan Li, East China Normal Univ. (China)
Ctr. for Earth Observation and Digital Earth (China)
Runhe Shi, East China Normal Univ. (China)
Ctr. for Earth Observation and Digital Earth (China)
Colorado State Univ. (United States)
Cong Zhou, East China Normal Univ. (China)
Ctr. for Earth Observation and Digital Earth (China)


Published in SPIE Proceedings Vol. 9610:
Remote Sensing and Modeling of Ecosystems for Sustainability XII
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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