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

Zhishan Li; Runhe Shi; Cong Zhou

doi:10.1117/12.2186158

4 September 2015 A tool for NDVI time series extraction from wide-swath remotely sensed images

Zhishan Li, Runhe Shi, Cong Zhou

Proceedings Volume 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII; 96100T (2015) https://doi.org/10.1117/12.2186158
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

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.

Citation Download Citation

Zhishan Li, Runhe Shi, and Cong Zhou "A tool for NDVI time series extraction from wide-swath remotely sensed images", Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100T (4 September 2015); https://doi.org/10.1117/12.2186158

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