Abstract: The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.
Abstract: Retrieval of the surface reflectance is important in the
remotely sensed data analysis to obtain the atmospheric reflectance or
atmospheric correction. The relationship between visible and mid
infrared reflectance over land was investigated and developed in this
study. The surface reflectances of the two visible bands were
measured using a handheld spectroradiometer collected around
Penang Island. In this study, we use the assumption that the 2.1 μm
band is not affected by aerosol and it is transparent to most aerosol
types (except dust). Therefore the satellite observed signal is the
same as the surface signal in 2.1 μm band. The correlation between
the surface reflectance measured by the spectroradiometer in the blue
and red region and the 2.1 μm observed by the satellite has been
established. We investigate five dates of Landsat TM scenes in this
study. The finding obtained by this study indicates that the surface
reflectance can be retrieved from the 2.1 μm band.