Robust quantitative estimates of land use and land cover change are necessary to develop policy solutions and interventions aimed towards sustainable land management. Here, we evaluated the combination of Landsat and L-band Synthetic Aperture Radar (SAR) data to estimate land use/cover change in the dynamic tropical landscape of Tanintharyi, southern Myanmar. We classified Landsat and L-band SA...

Remote sensing data is useful for selection of aquaculture sites because it can provide water-quality products mapped over large regions at low cost to users. However, the spatial resolution of most ocean color satellites is too coarse to provide usable data within many estuaries. The Landsat 8 satellite, launched February 11, 2013, has both the spatial resolution and the necessary signal to no...

Automatic interpretation of digital images is a difficult task. In this paper, we have proposed knowledge based approach for Landsat image segmentation and interpreted without any prior image dependent information. It includes an integration of image processing techniques, knowledge from domain experts and ancillary information such as previous maps of the study area. We discuss three important...

Accurately estimating consumptive water use in the Colorado River Basin (CRB) is important for assessing and managing limited water resources in the basin. Increasing water demand from various sectors may threaten long-term sustainability of the water supply in the arid southwestern United States. We have developed a first-ever basin-wide actual evapotranspiration (ETa) map of the CRB at the La...

Based on fractal models for the horizontal distribution of cloud density, Landsat-type (i.e., 30 m resolution) radiance fields were simulated within the Nonlocal Independent Pixel Approximation (NIPA), an improved version of the Independent Pixel Approximation (IPA) that uses only the local optical thickness, Scale-by-scale analyses of liquid water variability inside stratus clouds indicate sca...

Remote sensing image data from sources such as Landsat or airborne multispectral digital cameras are typically in the form of digital count (DC) values. To compare images acquired by the same sensor system on different dates, or images acquired by different sensor systems, it is necessary to correct for differences in the DC values due to sensor characteristics (gain and offset), illumination o...

The objective of this paper was to evaluate the accuracy of two advanced blending algorithms, Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to downscale Moderate Resolution Imaging Spectroradiometer (MODIS) indices to the spatial resolution of Landsat. We tested two approaches: (i) “Index-then-Blend”...

Mapping and assessment of mangrove environment are crucial since the mangrove has an important role in the process of human-environment interaction. In Indonesia alone, 25% of South East Asia's mangroves available are under threat. Recognizing the availability and the ability of new sensor of Landsat data, this study investigates the use of Landsat ETM + 7 and Landsat 8, acquired in 2002 and 20...

Monitoring current forest characteristics in the taiga ́tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal for...

A framework for the identification and monitoring of forest clearcuts and their regeneration is presented. LANDSAT digital data are classified to detect clearcuts and their major regeneration components, including brush, grass, bare soil, and conifer. Historical LANDSAT digital data are used to provide a changedetection analysis of forest conditions. Area summaries of land cover are obtained fo...