Fire Severity and Vegetation Recovery on Mine Site Rehabilitation Using WorldView-3 Imagery

Abstract

As open-cut coal mines progress towards closure, mining companies have an obligation to provide certainty to stakeholders that their rehabilitated landscapes have the capacity to withstand future disturbance impacts such as fire and drought. This paper describes the assessment of fire severity and recovery using WorldView-3 spectral indices following an experimental fire in a 19-to 21-year old coal mine rehabilitation in semi-arid Central Queensland, Australia. In a highly heterogeneous reconstructed environment, the differenced Normalized Difference Vegetation Index (dNDVI) outperformed the differenced Normalized Burn Ratio (dNBR) with an overall map accuracy of 65% and 58%, respectively. The combination of red and near infra-red multispectral bands proved more effective at classifying severity compared with the shortwave infra-red, particularly when pre-fire imagery was dominated by highly cured grasses (>70%) and post-fire imagery contained a high coverage of residual ash. Recovery trends using spectral indices demonstrate the trajectory towards vegetation recovery, with 62% of the burnt site demonstrating high regrowth in the first two years following fire. This is supported by in situ recovery trends of understory biomass suggesting that under the study conditions, the rehabilitated site has the capacity to withstand impacts from a wildfire and recover to pre-fire levels.

Remote Sensing of Mine Site Rehabilitation for Ecological Outcomes: A Global Systematic Review

“…Although now considered a low spatial and temporal resolution earth observation satellite, the Landsat series sensors were used consistently to characterize a range of rehabilitation features including land cover change [52][53][54][55][56][57][58], vegetation health [42,59], species level maps, including invasive species [60,61], vegetation biomass [62], successional development and age class differentiation [22,27,63], carbon sink calculations [64], disturbance and recovery change patterns [65], and surface temperature changes, as a function of vegetation cover and soil moisture properties [66]. Additionally, moderate to high spatial resolution earth observation sensors such as Satellite Pour l'Observation de la Terre (SPOT), IKONOS, Quickbird, RapidEye, GeoEye-1, and WorldView were typically employed in land cover studies, demonstrating the potential of classification methods using single or bi-temporal imagery [31,44,[67][68][69][70], while other studies assessed rehabilitation for resilience and recovery from secondary disturbances [29,71].…”

“…However, remote sensing assessments of mine site rehabilitation require considerable knowledge and skill to interpret outputs of analysis and derive meaningful results. This is highlighted by a number of studies emphasizing the heterogeneous nature of mine site rehabilitation and the unique spatial and temporal challenges for remote sensing assessments [21][22][23][24][25][26][27][28][29][30]. Alternatively, the distinctive spectral, temporal and spatial patterns of rehabilitated landscapes provides opportunities for remote sensing to derive valuable ecological information.…”

“…As a constructed landscape, rehabilitation is typically made up of discrete patches of vegetation in different stages of development, with underlying soil characteristics and landform slopes and topography that can vary significantly over short distances; particularly when compared to neighboring unmined land [12]. Additionally, rehabilitation managers often vary inputs, such as seed mixes, topsoil depth, and site preparation techniques, resulting in high levels of spectral heterogeneity within and between patches, across post-mining landscapes [21][22][23][24][25][26][27][28][29][30]. Nonetheless, the advantage of a remote sensing approach that uses discrete classification at fine spatial scales, is the potential to characterize the heterogeneity and the patterns associated with fine scale rehabilitation history, such as topsoil distribution, landform contour banks, and seeding patterns, using innovative classification techniques [31].…”

“…In particular, the SER sub-attribute of ecological resilience requires further research. Given that one of the key aims for mine site rehabilitation is an ecosystem that is self-sustainable, the measurement and demonstration of resilience is one key area for future work [12,29]. This is particularly salient given that disturbances such as fire, drought, disease, floods, and storms are inevitable and predicted to increase, given climate change.…”

Text Mining in Remotely Sensed Phenology Studies: A Review on Research Development, Main Topics, and Emerging Issues

“…Biodiversity and related ecosystem services issues resulted as connected, also, to studies about environmental disturbance phenomena, like fire. Many papers in rs+pheno studies analyzed the role of wildfires' behavior both as a driver of vegetation recovery patterns [101][102][103] and as influenced by fuel phenology and flammability [104,105]. In this latter case, a high potential exists for characterizing, classifying, and mapping fuel based on rs+pheno dynamics.…”