This is an article from the Summer 2015 VPS. For more VPS articles, click here
Project Team: Indonesia Disasters
Team Location: International Research Institute for Climate and Society (IRI) – Palisades, New York
Dr. Pietro Ceccato (International Research Institute for Climate and Society, The Earth Institute, Columbia University)
Fires associated with land-use conversion activities such as agricultural expansion, palm and pulp plantations, peat land alteration, and industrial deforestation are significant in the country of Indonesia. The use of remotely sensed data to assess deforestation and carbon emissions over Indonesia is crucial in the monitoring of fires, as ground-based methods are not viable. Fires are currently mapped using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, but its spatial resolution (500 meters) is not ideal for accurate mapping of burn scars in the region. Thus, researchers have sought to map burn scars at a higher spatial resolution. This study utilized Landsat to accomplish this task, given its spatial resolution of 30 meters, and tested a new methodology for identifying burn scars utilizing remotely sensed products over Central Kalimantan, Indonesia, using scenes from LandsatÛªs Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+). These scenes were used to assess a technique of transforming Red, Green, and Blue (RGB) color space to Hue, Saturation, and Value (HSV) space to decouple the hue from the saturation and value. When this technique was applied to a mid-infrared (MIR), near-infrared (NIR), and red false color composite, it enhanced the discrimination between vegetation, soil, and water ÛÒ distinguishing burn scars from their surroundings. A hue value range for burn scars was determined; however, clouds were a limiting factor in the analysis. The approach was a good first step in reducing the amount of information one must sift through to isolate burn scars; however, more work is needed to improve this technique and develop a more automated approach for their detection.