Interannual Changes of Fire Activity in the Protected Areas of the SUN Network and Other Parks and Reserves of the West and Central Africa Region Derived from MODIS Observations

Abstract

Time series of fire occurrence, derived from MODIS data, have been used to characterise the spatio-temporal distribution of fire events during the 2004-2009 period in 17 protected areas (PAs) of West and Central Africa, with particular attention to those of the SUN network in Senegal, Burkina Faso, Benin and Niger. The temporal distribution of the fire activity and the number of fire occurences are quite different inside the PAs and in their surrounding area. A progressive increase of the length of the burning season is observed in the West Africa PAs. Quantitatively, the general trend over the last five years is an increase of the fire density (+22%) inside the PAs and a decrease (−27%) outside. The results indicate that the capacity of the PAs to maintain the biological diversity of the region is probably decreasing due to the combined effects of the anthropic pressure inside the PAs and of an on-going isolation process.

Standardized Time-Series and Interannual Phenological Deviation: New Techniques for Burned-Area Detection Using Long-Term MODIS-NBR Dataset

“…The images already have atmospheric corrections for gases, thin cirrus clouds and aerosols [55]. The MODIS data is increasingly used to monitor burned areas and active fire over large geographic areas (e.g., [56][57][58][59][60][61][62][63]). The study area is contained in just one MODIS scene (tile h13v10).…”

A Decade Long, Multi-Scale Map Comparison of Fire Regime Parameters Derived from Three Publically Available Satellite-Based Fire Products: A Case Study in the Central African Republic

“…As previously mentioned, a variety of satellite-based remote sensing variables have been developed to characterize fire seasonality, each of which has its' own definition and its own method of calculation (e.g., [22][23][24][25][26][27][28][29][30]). Here, fire seasonality is characterized according to the cumulative distribution of fire pixels detected within a grid cell [24,26,31].…”

“…Second, due to geographic differences in vegetation type, landscape fragmentation and land use practices, a steep gradient of fire behavior in the CAR provides an opportunity to compare satellite-based fire products across a broad range of fire regimes but within a relatively narrow spatial domain [40]. Lastly, the CAR was selected as a case study site because a rich history of satellite-based AF and BA monitoring in the region (e.g., [23,24,26,[28][29][30][31][41][42][43]) has provided insights into landscape fire activity that can be referenced during the interpretation of the more modern datasets. …”

“…For example, satellite-derived fire chronologies have been used to determine distributions of fire return intervals from which fire frequency can be calculated (e.g., [18][19][20][21]), and fire seasonality has been characterized using a variety of satellite-derived metrics including the peak [22], the mid-point [23,24], the length of fire period [25], the fire season duration [26], the core burning season [27,28], and the classification of early and late season fires [29,30].…”

“…Maps of annual fire occurrence and maps of the onset, peak and duration of the fire season are derived from each dataset and are compared across a variety of spatiotemporal scales since: (i) it is possible to derive these parameters from all three fire products; (ii) these parameters are most often used to describe fire regimes; and (iii) these parameters have been derived and interpreted at spatial resolutions ranging from the pixel level to coarse grid cells. Here, comparisons between the satellite-derived fire regime parameters are performed as part of a case study designed to exploit a well-known gradient of fire behavior across the Central African Republic (CAR), one of the most fire-affected countries in Africa whose burning patterns have been the subject of a wide range of past studies [23,24,26,[28][29][30][31][41][42][43].…”