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http://dx.doi.org/10.7780/kjrs.2015.31.2.3

A water stress evaluation over forest canopy using NDWI in Korean peninsula  

Seong, Nohun (Dept. of Spatial Information Engineering, Pukyong National University)
Seo, Minji (Dept. of Spatial Information Engineering, Pukyong National University)
Lee, Kyeong-Sang (Dept. of Spatial Information Engineering, Pukyong National University)
Lee, Changsuk (Dept. of Spatial Information Engineering, Pukyong National University)
Kim, Hyunji (Dept. of Spatial Information Engineering, Pukyong National University)
Choi, Sungwon (Dept. of Spatial Information Engineering, Pukyong National University)
Han, Kyung-Soo (Dept. of Spatial Information Engineering, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.31, no.2, 2015 , pp. 77-83 More about this Journal
Abstract
Leaf water content is one of important indicators that shows states of vegetation. It is important to monitor vegetation water content using remote sensing for forest management. In this study, we investigated the degree of water stress in Korean peninsula with Normalized Difference Water Index (NDWI) to study the water content of vegetation canopy. We calculated the NDWI using SPOT/VEGETATION S10 channel data over forest from 1999 to 2013. We calculated Simple Moving Average (SMA) to remove temporal noises of NDWI in time series, and used standardized anomaly to investigate temporal changes. We classified the NDWI anomalies into three scales (low, moderate, and high) in order to monitor intuitively. We also investigated suitability of the NDWI as an evaluation criterion about water stress of vegetation canopy by comparing and verifying forest fires damaged area over 150 ha. Consequently, huge forest fire occurred 24 times during the study period. Also, negative anomalies appeared in every forest fire location and their neighboring areas. In particular, we found huge forest fires where NDWI anomalies were in 'high' scale.
Keywords
Water stress; NDWI; forest fire;
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Times Cited By KSCI : 2  (Citation Analysis)
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