Abstract
Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.
Highlights
Forests play an important role in the global ecological, environmental and recreational functions [1,2]
We primarily present an overview on the status of detecting forest fire hot spots and fire areas by using satellite sensors in China over the past three decades, and analyze a few developed algorithms used for detecting fires with greater accuracies
We evaluate forest fire risk potential models that have been used for predicting the forest fires occurrence in China
Summary
Forests play an important role in the global ecological, environmental and recreational functions [1,2]. Given the high cost and potential hazards associated with the ground-based and air-borne fire monitoring, space-borne satellite sensors have been widely used to detect and monitor forest fires in recent years [18,19,20,21]. Radiation in the visible (VIS, 0.4–0.7 μm), the near infrared (NIR, 0.7–1.3 μm), the short-wave infrared (SWIR, 1.3–8 μm), the middle infrared (MIR, 3–8 μm), and the thermal infrared (TIR, 8–13 μm) The satellite sensors such as NOAA/AVHRR, Chinese FY (FengYun)-series, MODIS, CBERS (China-Brazil Earth Resources Satellite), and ESA (European Space Agency) ENVISAT (Environmental Satellite) have been widely applied to detect forest fire hot spots and burned areas in.
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More From: International Journal of Environmental Research and Public Health
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