SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Developing land use land cover maps for the Lower Mekong Basin to aid hydrologic molding and basin planning 
Authors:Spruce, J., J. Bolten, R. Srinivasan and C. Lakshmi 
Year:2018 
Journal:Remote Sensing 
Volume (Issue):10(12) 
Pages: 
Article ID:1910 
DOI:10.3390/rs10121910 
URL (non-DOI journals): 
Model:none 
Broad Application Category:data or component development 
Primary Application Category:data and/or component contribution to SWAT 
Secondary Application Category:land use resolution effects 
Watershed Description:"Sub basin 7" Within the lower Mekong river which aligns mostly with the Chi River draining in northeast Thailand. 
Calibration Summary: 
Validation Summary: 
General Comments:The authors state: "This effort used NASA remote sensing systems and data to help improve Mekong River Commission (MRC) Soil Water Assessment Tool (SWAT) models for sub-basins (SBs) 1–8. The project included computation and updates of LULC maps that were in turn used as a primary input to MRC SWAT hydrologic models developed for multiple sub-basins of the LMB." However, the study area was limited to what is essentially the Chi River System that is located in northeast Thailand, although the southeast part of the drainage area differs from what is normally delineated; e.g., see study at https://doi.org/10.2208/jscejhe.67.I_31. The river name is incorrectly stated as "Chu" in the text of this study but is correctly called "Chi" in Figure 2. 
Abstract:This paper discusses research methodology to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellite data. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthly NDVI maps with the Time Series Product Tool software package and then used to classify regionally common forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATA clustering was used to derive most LULC classifications. MODIS and Landsat classifications were combined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB. The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared random locations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commission data (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of ~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%. The project enabled updated regional LULC maps that included more detailed agriculture LULC types. LULC maps were supplied to project partners to improve use of Soil and Water Assessment Tool for modeling hydrology and water use, plus enhance LMB water and disaster management in a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planning and assessment. 
Language:English 
Keywords:land use land cover mapping; SWAT hydrologic modeling disaster management; water resource management; agricultural monitoring