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위성영상 시공간 융합기법의 계절별 NDVI 예측에서의 응용
김예화,주경영,성선용,이동근 대한원격탐사학회 2017 大韓遠隔探査學會誌 Vol.33 No.2
시간해상도와 공간해상도가 높은 영상 자료는 효과적인 식생의 모니터링을 위해서 필수적이다. 하지만 단일 센서를 통한 영상은 공간해상도와 시간해상도가 높은 자료를 동시에 제공할 수 없는 한계점이 있다. 최근에는 위성영상의 공간적 해상도를 높이고 시간해상도를 보완하기 위해서 시공간 융합연구가 진행되고 있다. 그 중에서도 FSDAF(Flexible spatiotemporal data fusion) 방법론은 위성영상의 각 밴드를 융합하는 방법으로 적절한 것으로 나타났다. 본 연구에서는 FSDAF 융합기법을 활용하여 MODIS NDVI와 Landsat 영상으로 계산한 NDVI를 융합 후 검증을 실시하였으며 식생 계절 모니터링에서의 활용가능성을 제시하였다. 그 결과, 1월부터 12월까지 융합을 통해 NDVI 예측한 영상은 활엽수, 침엽수, 농지의 계절적인 특징을 잘 반영하고 있었다. 융합된 결과의 검증을 위하여 8월과 10월의 예측한 NDVI와 실제 값(Landsat NDVI) 간의 RMSE 값을 계산한 결과 각각 0.049와 0.085, 상관계수는 0.765, 0.642로 비교적 일치한 것으로 나타났다. 본 연구에서 활용된 FSDAF 시공간 융합 기법은 픽셀기반의 융합기법으로 다양한 공간스케일의 영상과도 융합 가능할 것이며 다양한 식생 관련 연구에 활용될 것으로 기대된다. Fine temporal and spatial resolution of image data are necessary to monitor the phenology of vegetation. However, there is no single sensor provides fine temporal and spatial resolution. For solve this limitation, researches on spatiotemporal data fusion methods are being conducted. Among them, FSDAF (Flexible spatiotemporal data fusion) can fuse each band in high accuracy. In this study, we applied MODIS NDVI and Landsat NDVI to enhance time resolution of NDVI based on FSDAF algorithm. Then we proposed the possibility of utilization in vegetation phenology monitoring. As a result of FSDAF method, the predicted NDVI from January to December well reflect the seasonal characteristics of broadleaf forest, evergreen forest and farmland. The RMSE values between predicted NDVI and actual NDVI (Landsat NDVI) of August and October were 0.049 and 0.085, and the correlation coefficients were 0.765 and 0.642 respectively. Spatiotemporal data fusion method is a pixel-based fusion technique that can be applied to various spatial resolution images, and expected to be applied to various vegetationrelated studies.
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위성영상 시공간 융합과 CASA 모형을 활용한 산지 개발사업의 식생 순일차생산량에 대한 영향 평가
김예화,주경영,성선용,이동근,Jin, Yi-Hua,Zhu, Jing-Rong,Sung, Sun-Yong,Lee, Dong-Ku 한국환경복원기술학회 2017 한국환경복원기술학회지 Vol.20 No.4
As the "Guidelines for GHG Environmental Assessment" was revised, it pointed out that the developers should evaluate GHG sequestration and storage of the developing site. However, the current guidelines only taking into account the quantitative reduction lost within the development site, and did not consider the qualitative decrease in the carbon sequestration capacity of forest edge produced by developments. In order to assess the quantitative and qualitative effects of vegetation carbon uptake, the CASA-NPP model and satellite image spatial-temporal fusion were used to estimate the annual net primary production in 2005 and 2015. The development projects between 2006 and 2014 were examined for evaluate quantitative changes in development site and qualitative changes in surroundings by development types. The RMSE value of the satellite image fusion results is less than 0.1 and approaches 0, and the correlation coefficient is more than 0.6, which shows relatively high prediction accuracy. The NPP estimation results range from 0 to $1335.53g\;C/m^2$ year before development and from 0 to $1333.77g\;C/m^2$ year after development. As a result of analyzing NPP reduction amount within the development area by type of forest development, the difference is not significant by type of development but it shows the lowest change in the sports facilities development. It was also found that the vegetation was most affected by the edge vegetation of industrial development. This suggests that the industrial development causes additional development in the surrounding area and indirectly influences the carbon sequestration function of edge vegetaion due to the increase of the edge and influx of disturbed species. The NPP calculation method and results presented in this study can be applied to quantitative and qualitative impact assessment of before and after development, and it can be applied to policies related to greenhouse gas in environmental impact assessment.
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