[국내논문]Monitoring and Analyzing Water Area Variation of Lake Enriquillo, Dominican Republic by Integrating Multiple Endmember Spectral Mixture Analysis and MODIS Data원문보기
Lake Enriquillo, the largest lake in the Dominican Republic, recently has undergone unusual water area changes since 2001 thus it has been affected seriously by local community's livelihood. Earthquakes and seismic activities of Hispaniola plate tectonic coupled with human activities and climate cha...
Lake Enriquillo, the largest lake in the Dominican Republic, recently has undergone unusual water area changes since 2001 thus it has been affected seriously by local community's livelihood. Earthquakes and seismic activities of Hispaniola plate tectonic coupled with human activities and climate change are addressed as factors causing the increasing. Thus, a thorough study on relationship between lake area changing, and those factors is needed urgently. To do so, this study applied MESMA on MODIS data to extract water area of Lake Enriquillo during 2001 and 2012 bimonthly, with six issues 12-year. MODIS provides high temporal resolution, and its coarse spatial resolution is compensated by MESMA fraction map. The increase in water area was $142.2km^2$, and the maximum lake area was $338.0km^2$ (in 2012). Water areas extracted by two Landsat scenes at two different times with three image classification approaches (ISODATA, MNDWI, and TCW) were used to assess accuracy of MODIS and MESMA results; it indicated that MESMA water areas are same as ISODATA's, less than 0.4%, while the highest difference is between MESMA and TCW, 2.4%. A number of previously formulated hypotheses of lake area change were investigated based on the outcomes of the present study, though none of them could fully explain the changes.
Lake Enriquillo, the largest lake in the Dominican Republic, recently has undergone unusual water area changes since 2001 thus it has been affected seriously by local community's livelihood. Earthquakes and seismic activities of Hispaniola plate tectonic coupled with human activities and climate change are addressed as factors causing the increasing. Thus, a thorough study on relationship between lake area changing, and those factors is needed urgently. To do so, this study applied MESMA on MODIS data to extract water area of Lake Enriquillo during 2001 and 2012 bimonthly, with six issues 12-year. MODIS provides high temporal resolution, and its coarse spatial resolution is compensated by MESMA fraction map. The increase in water area was $142.2km^2$, and the maximum lake area was $338.0km^2$ (in 2012). Water areas extracted by two Landsat scenes at two different times with three image classification approaches (ISODATA, MNDWI, and TCW) were used to assess accuracy of MODIS and MESMA results; it indicated that MESMA water areas are same as ISODATA's, less than 0.4%, while the highest difference is between MESMA and TCW, 2.4%. A number of previously formulated hypotheses of lake area change were investigated based on the outcomes of the present study, though none of them could fully explain the changes.
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문제 정의
The objectives of this study were to extract water area in a 2001-2012 time-series for mapping and assessment of the spatial patterns of the water area changes of Lake Enriquillo in the Dominican Republic. This saline, terminal lake, the largest and most important in the Dominican Republic, is located on the central plateau of Hispaniola, along with the border with Haiti.
The primary objective of this study was to determine, by MESMA, the variation of Lake Enriquillo water area between 2001 and 2012. To explain the spatial patterns of fractional water area, we obtained both RGB image results and MESMA results.
제안 방법
2008). It is found that MNDWI accuracy is better than NDWI and insufficient to provide accurate estimation of the spatial-temporal process of water inundation over the marshlands through linear interpolation. Three supervised image classification methods (density slicing, classification trees, and feature extraction) were examined based on Landsat TM and ETM+ (Roach et al.
2012). In the research, an integrated threshold of NDWI and NDVI is adopted along with SRTM (Shuttle Radar Topography Mission); then the result was used to analyze flood hazard.
This paper introduces a MESMA method that utilizes sub-pixel MODIS images to produce water-cover maps. The result of MESMA and MODIS was verified by the synchronous date Landsat data which processed by three unsupervised classification methods (ISODATA, MNDWI and the tasseled cap wetness (TCW).
Concerning three major types of land cover at the study site, about 50 pixels were selected in the MODIS for each endmember type. We refined the selected pixels by visualization of the PPI results, and then, to confirm the endmembers, we geographically linked the PPI images to the MODIS and Landsat-5 TM / Landsat-7 ETM+ band-combination (3/2/1, 4/3/2, 4/5/3) images. Finally, we grouped the endmembers into three classes: soil (exposed soil, sand), vegetation (grass, forest) and shade (water).
(2009), additionally, discovered that the two-endmember model effectively discriminates rivers and lakes. Based on these research results, and according to the specific objective of the present study, we used two-endmember combinations to delineate the water area expansion of Lake Enriquillo.
(2012b) argued that both EAR and MASA are helpful for choosing strictly defined land-cover types. Based on these findings, we utilized EAR to determine the optimal endmember selection for each image.
In this study, for optimal endmember selection, we used 30 two-endmember models from the endmember library (15 representing soil and 15 representing vegetation). As the second endmember, photometric shade, defined as a spectrum for which the reflectance values of all bands are equal to zero (Adams and Smith 1986), was applied.
As the second endmember, photometric shade, defined as a spectrum for which the reflectance values of all bands are equal to zero (Adams and Smith 1986), was applied. As two-endmember MESMA modeling constraints, RMSE (0.045), Maximum (1.050), and Minimum (-0.050) fraction, selected based on our analysis of all of the MODIS images, were applied.
The fraction-valued pixels also are classified into two groups: 1) those off of the shoreline, which is excluded from the water area calculation; 2) those located along the shoreline, which is considered as edge area. To determine whether or not the pixel belongs to the shoreline, visual inspection with color composites made from three multispectral intervals (Near Infrared, Red, and Green) is performed. After classification, the water area on each pixel is calculated by multiplying the fraction value by the pixel size (250 m by 250 m).
3, 2009). In order to develop a reference dataset with the Landsat-7 ETM+ image, water area was extracted by three relatively simple, fast and accurate methods: (1) the Modified Normalized Difference Water Index (MNDWI); (2) unsupervised classification (ISODATA), and (3) the tasseled cap wetness (TCW) index. Xu (2006) claimed that MNDWI is more suitable for water area delineation that entails removal of built-up land noise as well as vegetation and soil noise; ISODATA is well known for effective land-cover classification, multispectral water area classification, and noise elimination (Zhang 2000); TCW is used to delineate flood-affected areas immediately before and after a flood (Jain et al.
이론/모형
2011). Poyang Lake water body was created annually temporally by Landsat with the Normalized Difference Water Index (NDWI) and the Modified Normalized Difference Water Index (MNDWI) in order to analyze seasonal changing and water inundation (Hui et al. 2008). It is found that MNDWI accuracy is better than NDWI and insufficient to provide accurate estimation of the spatial-temporal process of water inundation over the marshlands through linear interpolation.
Recently the lake has undergone unusual water area changes, the causes of which are as yet unexplained. This paper introduces a MESMA method that utilizes sub-pixel MODIS images to produce water-cover maps. The result of MESMA and MODIS was verified by the synchronous date Landsat data which processed by three unsupervised classification methods (ISODATA, MNDWI and the tasseled cap wetness (TCW).
성능/효과
The second EWA values, those between MODIS and the areas delineated by the same three methods from Landsat-5 TM, respectively, were 0.4%, 0.4%, and 2.4%.
The first EWA values, those between the fractional water area from MODIS and the areas delineated by MNDWI, ISODATA, and TCW from Landsat-7 ETM+, respectively, were 0.5%, 0%, and 2.0%. The second EWA values, those between MODIS and the areas delineated by the same three methods from Landsat-5 TM, respectively, were 0.
4%. These results show that the MODIS-derived fractional water area results by MESMA were very close to those for the processed reference images: approximately 99.1% and 98.9% average accuracies, respectively.
0 km2 (in 2012). The results of this study show that MESMA effectively generates fractional covers of water area on land. They also suggest the special applicability of MESMA analysis to the identification and assessment of climate-change-effected water variation and potential disaster areas.
후속연구
Additionally, some hypotheses of lake area change mechanisms were investigated based on the outcomes of the present study, though none of them could fully explain the changes. This fact suggests that further investigations will require monthly water area data.
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