Mapping the annual area burned in the wetlands of the Okavango panhandle using a hierarchical classification approach

Abstract

This paper documents the methodology developed to identify burned areas accurately, and to quantify the spatial extent of the areas burned, in the wetlands of Botswana's Okavango panhandle in 2001. Physical identification of burned areas in marshy wetlands is extremely difficult. Burned areas are short-lived, limiting opportunities for ground-based measurement, which is often further hampered by extreme inaccessibility, and the unpredictable nature of the location and timing of burning. Given these challenges, satellite imagery has the potential to provide an excellent alternative for such analyses. However, burned areas can be spectrally confused with non-vegetated wetland areas such as open water and muddy flats, particularly when relying predominantly on the near-infrared band. This study addresses these constraints by using a hierarchical classification of Landsat 7 ETM+ imagery to remove wet and well-vegetated areas prior to burned-area identification, and by using the thermal band data to improve the separation between wet and burned areas. These techniques resulted in good designation of burned areas, a reduction in the misclassification of unburned areas, and a refinement of the spatial distribution of areas burned in 2001. The approach should prove useful to practitioners seeking to manage fire in wetlands.

Mapping Wetland Burned Area from Sentinel-2 across the Southeastern United States and Its Contributions Relative to Landsat-8 (2016–2019)

“…In this effort, we used a machine learning algorithm, trained on wetland fires, to map burned area extent (2016-2019), using the Sentinel-2 archive across Florida, as well as parts of Alabama, Georgia, and South Carolina. Burned area in wetlands can go undetected when a burned area is visible but omitted by a burned area algorithm due to low burn severity, burnable wetlands being masked out, or an atypical burn signal [11,38]. Burned area in wetlands can also go undetected when the burned area was never visible during image collection dates because of rapid vegetation recovery and cloud cover [25,26].…”

“…In wetlands, using satellites that provide shortwave infrared bands may be especially important. As water levels rise in vegetated wetlands, the spectral reflectance in the NIR declines [38], meaning that saturated wetlands can look very similar to burned areas. Even NBR, however, tends to perform less consistently in unforested areas [73], where the index may respond more to soil wetness than plant coverage [12].…”

“…Even NBR, however, tends to perform less consistently in unforested areas [73], where the index may respond more to soil wetness than plant coverage [12]. Using Landsat satellites, indices that incorporated the thermal band were found to reduce confusion [34,38]. For sensors that lack the thermal band, such as Sentinel-2, we demon-strated that ancillary sources of data, such as GRIDMET standardized precipitation index can potentially help the algorithm identify when darker-than-normal ground conditions may be attributed to an increase in wetness instead of a burn event.…”

“…Efforts to remotely track wetland fires have predominantly mapped and tracked post-fire spectral recovery within known wetland burn perimeters [12,[35][36][37]. Meanwhile, efforts to find and map wetland fires with satellite imagery, alone, have been very limited and have primarily relied on unsupervised classification approaches [11,38]. The probability of mapping wetland fires will depend in part on the persistence of the burn signal, which can be much shorter for wetlands relative to upland forests, and shorter for wet and warm southeastern ecosystems, relative to drier western ecosystems (Figure 1).…”

A 3000-year record of vegetation changes and fire at a high-elevation wetland on Kilimanjaro, Tanzania

“…Charcoal accumulations are lower from 400 to 500 yr BP to the present at both Kanderi and Tsavo (Gillson, 2004) and at Esambu, Amboseli (Githumbi et al, 2018b). The differing signals in charcoal accumulation highlight local-scale fuel and fire responses, the spatial heterogeneity of savannah fire regimes, the understudied complexities of fire regimes at savannah-wetland edges (Kirby et al, 1988; Kirkman, 1995; Casanova and Brock, 2000; Cassidy, 2007; Nielsen et al, 2013; Saintilan and Rogers, 2015), and more broadly the role of human activities in and around wetlands (Seki et al, 2018).…”