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http://dx.doi.org/10.7780/kjrs.2018.34.2.1.9

Detecting Phenology Using MODIS Vegetation Indices and Forest Type Map in South Korea  

Lee, Bora (Forest Ecology & Climate Change Division, National Institute of Forest Science)
Kim, Eunsook (Forest Ecology & Climate Change Division, National Institute of Forest Science)
Lee, Jisun (Forest Ecology & Climate Change Division, National Institute of Forest Science)
Chung, Jae-Min (Korea National Arboretum)
Lim, Jong-Hwan (Forest Ecology & Climate Change Division, National Institute of Forest Science)
Publication Information
Korean Journal of Remote Sensing / v.34, no.2_1, 2018 , pp. 267-282 More about this Journal
Abstract
Despite the continuous development of phenology detection studies using satellite imagery, verification through comparison with the field observed data is insufficient. Especially, in the case of Korean forests patching in various forms, it is difficult to estimate the start of season (SOS) by using only satellite images due to resolution difference. To improve the accuracy of vegetation phenology estimation, this study reconstructed the large scaled forest type map (1:5,000) with MODIS pixel resolution and produced time series vegetation phenology curves from Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from MODIS images. Based on the field observed data, extraction methods for the vegetation indices and SOS for Korean forests were compared and evaluated. We also analyzed the correlation between the composition ratio of forest types in each pixel and phenology extraction from the vegetation indices. When we compared NDVI and EVI with the field observed SOS data from the Korea National Arboretum, EVI was more accurate for Korean forests, and the first derivative was most suitable for extracting SOS in the phenology curve from the vegetation index. When the eight pixels neighboring the pixels of 7 broadleaved trees with field SOS data (center pixel) were compared to field SOS, the forest types of the best pixels with the highest correlation with the field data were deciduous forest by 67.9%, coniferous forest by 14.3%, and mixed forest by 7.7%, and the mean coefficient of determination ($R^2$) was 0.64. The average national SOS extracted from MODIS EVI were DOY 112.9 in 2014 at the earliest and DOY 129.1 in 2010 at the latest, which is about 0.16 days faster since 2003. In future research, it is necessary to expand the analysis of deciduous and mixed forests' SOS into the extraction of coniferous forest's SOS in order to understand the various climate and geomorphic factors. As such, comprehensive study should be carried out considering the diversity of forest ecosystems in Korea.
Keywords
Forest type map; MODIS NDVI; MODIS EVI; Phenology;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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