ENVISAT multisensor data for fire monitoring and impact assessment

Abstract

The European ENVISAT satellite provides both optical and radar measurements of the Earth's surface. In this Letter, three ENVISAT instruments were used to investigate the extent and impact of the forest and peatland fires that devastated large areas in Central Kalimantan, Indonesia in 2002. Reduced spatial resolution MERIS imagery was used to identify simple land cover features and smoke plumes. Fire hotspots were detected by band 3.7 mm of Advanced Along Track Scanning Radiometer (AATSR) night-time acquisitions, and burnt areas were detected by Advanced Synthetic Aperture Radar (ASAR) wide swath radar imagery acquired before and after the fire event. The capability of ENVISAT to acquire data from different sensors simultaneously or within a short period of time greatly enhances the possibilities to monitor fire occurrence and assess fire impact.

Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

“…Moreover, research on forest fires in boreal forests has shown that the backscatter intensity from burned scars is stronger than that from unburned areas due to changes in moisture content [11,12,[15][16][17]. Siegert and Ruecker [18] and Huang and Siegert [19] made similar observations in a tropical rain forest environment, but found that fires caused a decrease in backscatter under dry weather conditions whereas under wet conditions burned areas could not be discriminated from unburned areas.…”

“…The same conclusion could not be drawn for forested areas as approximately 70% of the omitted areas showed values higher than 0.5 degrees of dNDMI. In this case, the influence of local incidence angle might have caused the misclassifications since studies have shown that the backscatter coefficient of burned areas varies as a function of the incidence angle [19,52]. It was observed that 40% of the omitted burned forest was located in areas with local incidence angles ≤25° and ≥50°.…”

An improved algorithm for the detection of plumes caused by natural or technological hazards using AVHRR imagery

“…However, while the detection of natural or technological fires using satellite images has been given much attention and is now performed on a routine basis (Cahoon et al, 1994;Christopher et al, 1996;Chrysoulakis & Cartalis, 2000, 2003bHuang & Siegert, 2005;Kaufman et al, 1990;Prins et al, 1998;Pu et al, 2004), fewer interest has been given to automatic plumes detection. Methods have been developed for plume detection based either on image photointerpretation using pseudocoloured compositions of Advance Very High Resolution Radiometer (AVHRR) spectral channels (Chung & Le, 1984;Kaufman et al, 1990;Randriambelo et al, 1998), or on retrieving of optical depth of heavy aerosol plumes (Wong & Li, 2002), or on multi-threshold methods based on spectral indices (Baum & Trepte, 1999;Chrysoulakis & Cartalis, 2003a;Chrysoulakis et al, 2005) and textural features (Christopher & Chou, 1997;Christopher et al, 1996), or on multi-threshold methods based on neural networks (Li et al, 2001).…”

“…The type of plume information that can be derived from satellite data includes location, timing and areal extent measurement, and to a certain extent a measure of the amount of aerosols and some types of trace gases released Penner et al, 1992). In several past studies, satellite data have been used to quantify the gaseous output from fires (Cahoon et al, 1994;Chrysoulakis & Cartalis, 2003a;Chrysoulakis & Opie, 2004;Chung, 2002;Dousset et al, 1993;Feingold et al, 2001;Ferrare et al, 1990;Huang & Siegert, 2005;Kaufman & Fraser, 1997;Kaufman et al, 1992;Khazenie & Richardson, 1993;Randriambelo et al, 1998;Rudich et al, 2003). Other studies examined the effects of large plumes on clouds (Feingold et al, 2001;Kaufman & Fraser, 1997;Kaufman & Nakajima, 1993;Rosenfeld, 1999;Rosenfeld & Lensky, 1998;Rudich et al, 2003) and the feasibility of using satellite images to detect largescale pollution episodes (Cahoon et al, 1994;Chung & Le, 1984).…”

Global burned area maps from MERIS

“…MERIS was mainly designed for ocean colour applications, as it provides high spectral resolution in the range of the blue to the near infrared regions (Gower and Borstad 2004). The application of MERIS data to fire applications is scarce: identification of smoke plumes (Huang and Siegert 2004), discrimination of burn severity (De Santis and Chuvieco 2007;Roldan-Zamarron, Merino-De-Miguel et al 2006). Mapping BA with MERIS has only been performed at regional level (Oliva, Martin et al 2011) using different vegetation indices while (González-Alonso 2009) combined fire hotspots from MODIS and NIR reflectance values from MODIS and MERIS imagery.…”