DMSP-OLS estimation of tropical forest area impacted by surface fires in Roraima, Brazil: 1995 versus 1998

Abstract

A procedure has been developed to locate and estimate the area of heavy forest burning based on the frequency of DMSP-OLS (US Air Force Defense Meteorological Satellite Program Operational Linescan System) re detection from time series of observations across the re season. A calibration was developed for Roraima, Brazil, using Landsat Thematic Mapper (TM) data acquired near the end of the 1998 burn season and analysed to identify unburnt, partially burnt and heavily burnt forest areas. A re detection frequency threshold of ve nights was used to map heavily burnt forest using the 3 months of DMSP-OLS observations. The threshold of ve re detections, which could occur anytime during the 3-month time period, was selected to constrain errors of commission involving unburnt forest to 10% of the total area for unburnt forest in the calibration area. At this threshold setting the DMSP-OLS estimate of heavily burnt forest area covered 79% of the Landsat measured area. It was found that 77% of the 1998 heavily burnt forest area was outside of the state's protected areas (national parks, reserves, indigenous areas). Two of the protected areas sustained a substantial increase in heavily burnt forest in 1998 relative to 1995 (Reserva Biológica MucajaÌ and Parque IndÌgena Yanomami). The 1998 forest burning in these two areas was concentrated in their eastern-most sections. The core of the Yanomami area did not sustain extensive burning in 1998. Protected areas in the north-eastern section of the state, where forests are mixed with cerrado, had moderate increases in heavily burnt forest in 1998. Other protected areas were largely free of the heavy forest burning, which was concentrated to the west of the state's primary cerrado zone.

Estimating Land Development Time Lags in China Using DMSP/OLS Nighttime Light Image

“…NTL data has been widely applied in various aspects of social science research such as socioeconomic development [9,12,17], energy consumption [11,18,19], light pollution [20], forest fire monitoring [21][22][23], snow cover detection [24], war studies [25], etc. Great achievements have been made in urban studies using NTL data in the last few decades.…”

Validación y comparación de los productos MODIS y AATSR para la detección de focos activos en la España peninsular y Baleares en el año 2003

“…Trabajando en una banda algo más corta, los sensores ATSR y AATSR a bordo de los satélites europeos ERS y Envisat también se han utilizado para detección de incendios activos, de cara a evaluar el impacto del fuego a escala planetaria (Arino y Melinotte, 1998). Con otro enfoque complementario, los datos nocturnos del satélite DMSP también han ofrecido una información de gran interés sobre incendios activos, aunque en este caso se observa no el calor, sino la luz desprendida por estos eventos (Elvidge, 2001). Más recientemente, el sensor MODIS se está empleando globalmente con esta misma finalidad, gracias a disponer de varios canales en el infrarrojo medio y térmico.…”

Use of Remote Sensing in Wildfire Management

“…Firstly, active fires can be detected from the light they emit in the visible part of the spectrum; however, the discrimination of the fire-emitted light is only possible at night (Cahoon et al, 1992, Elvidge, 2001. Since most of the fires occur and have their highest intensity during the day, the detection of them solely at night is not of high interest for operational fire management.…”