Search Results (82)

The cessation of traditional mountain grazing has emerged as a principal driver of habitat degradation and the local extinction of Parnassius apollo (Linnaeus, 1758) in Serbia. While previous studies have cited multiple contributing factors, our research provides evidence that the abandonment of extensive livestock grazing has triggered vegetation succession, the disappearance of the larval host plant (Sedum album), and a reduction in microhabitat heterogeneity—conditions essential for the persistence of this stenophagous butterfly species. Through satellite-based analysis of vegetation dynamics (2015–2024), we identified clear structural differences between habitats that currently support populations and those where the species is no longer present. Occupied sites were characterized by low levels of exposed soil, moderate grass coverage, and consistently high shrub and tree density, whereas unoccupied sites exhibited dense encroachment of grasses and woody vegetation, leading to structural instability. Furthermore, MODIS-derived indices (2010–2024) revealed a consistent decline in vegetation productivity (GPP, FPAR, LAI) in succession-affected areas, alongside significant correlations between elevated land surface temperatures (LST), thermal stress (TCI), and reduced photosynthetic capacity. A wildfire event on Mount Stol in 2024 further exacerbated habitat degradation, as confirmed by remote sensing indices (BAI, NBR, NBR2), which documented extensive burn scars and post-fire vegetation loss. Collectively, these findings indicate that the decline of P. apollo is driven not only by ecological succession and climatic stressors, but also by the abandonment of land-use practices that historically maintained suitable habitat conditions. Our results underscore the necessity of restoring traditional grazing regimes and integrating ecological, climatic, and landscape management approaches to prevent further biodiversity loss in montane environments. Full article

This study used Jilin-1 satellite data and unmanned aerial vehicle (UAV)-collected visible-thermal infrared imagery to calculate twelve spectral indices and evaluate their effectiveness in distinguishing post-fire forest areas and identifying human-altered land-cover changes in Jinyun Mountain, Chongqing. The research goals included mapping wildfire impacts with M-statistic separability, measuring land-cover distinguishability through Jeffries–Matusita (JM) distance analysis, classifying land-cover types using the random forest (RF) algorithm, and verifying classification accuracy. Cumulative human disturbances—such as land clearing, replanting, and road construction—significantly blocked the natural recovery of burn scars, and during long-term human-assisted recovery periods over one year, the Red Green Blue Index (RGBI), Green Leaf Index (GLI), and Excess Green Index (EXG) showed high classification accuracy for six land-cover types: road, bare soil, deadwood, bamboo, broadleaf, and grass. Key accuracy measures showed producer accuracy (PA) > 0.8, user accuracy (UA) > 0.8, overall accuracy (OA) > 90%, and a kappa coefficient > 0.85. Validation results confirmed that visible-spectrum indices are good at distinguishing photosynthetic vegetation, thermal bands help identify artificial surfaces, and combined thermal-visible indices solve spectral confusion in deadwood recognition. Spectral indices provide high-precision quantitative evidence for monitoring post-fire land-cover changes, especially under human intervention, thus offering important data support for time-based modeling of post-fire forest recovery and improvement of ecological restoration plans. Full article

Wildfires threaten ecosystems, biodiversity, and human livelihood while exacerbating climate change. Accurate identification and monitoring of burned areas (BA) are critical for effective post-fire recovery and management. Although satellite multi-spectral imagery offers a practical solution for BA monitoring, existing methods often prioritize specific spectral bands while neglecting full spectral shape information, which encapsulates overall spectral characteristics. This limitation compromises adaptability to diverse vegetation types and environmental conditions, particularly across varying spatial scales. To address these challenges, we propose the time-series spectral-angle-normalized burn index (TSSA-NBR). This unsupervised BA extraction method integrates normalized spectral angle and normalized burn ratio (NBR) to leverage full spectral shape and temporal features derived from Sentinel-2 time-series data. Seven globally distributed study areas with diverse climatic conditions and vegetation types were selected to evaluate the method’s adaptability and scalability. Evaluations compared Sentinel-2-derived BA with moderate-resolution products and high-resolution PlanetScope-derived BA, focusing on spatial scale and methodological performance. TSSA-NBR achieved a Dice Coefficient (DC) of 87.81%, with commission (CE) and omission errors (OE) of 8.52% and 15.58%, respectively, demonstrating robust performance across all regions. Across diverse land cover types, including forests, grasslands, and shrublands, TSSA-NBR exhibited high adaptability, with DC values ranging from 0.53 to 0.97, CE from 0.03 to 0.27, and OE from 0.02 to 0.61. The method effectively captured fire scars and outperformed band-specific and threshold-dependent approaches by integrating spectral shape features with fire indices, establishing a data-driven framework for BA detection. These results underscore its potential for fire monitoring and broader applications in detecting surface anomalies and environmental disturbances, advancing global ecological monitoring and management strategies. Full article

Cultured epidermal autografts (CEAs) serve as an alternative permanent skin replacement, though high costs often limit their use in resource-constrained settings and to life-saving cases. This case report presents the first documented cosmetic application of a modified CEA technique in a bodybuilder, demonstrating favorable aesthetic outcomes. A 28-year-old Black male with a 20% total body surface area burn sustained in a domestic fire exhibited superficial and deep partial-thickness burns to the face, arms, torso, and feet. Refusing grafts from visible donor sites, treatment using a low-cost modified CEA approach was employed to minimize donor site morbidity. Keratinocytes harvested from a groin biopsy were cultured on Cutimed Sorbact^® (Essity AB, BSN Medical (Pty) Ltd., Pinetown, RSA) dressings with autogenous plasma and hydrogel supplementation and incubated at 37 °C for two weeks. Xenografts provided temporary coverage before CEA transplantation. Graft take was 85%, with minor (15%) loss at 21 days, requiring small autograft coverage. At two months, the Vancouver Scar Scale score was 4, indicating optimal pigmentation, smoother texture, and minimal scarring. These findings align with limited studies on CEAs for cosmetic applications, suggesting this cost-effective technique may broaden the scope of CEAs beyond life-saving interventions to include aesthetic reconstruction, reducing both donor site morbidity and scarring. Full article

The surface fragmentation of karst landscapes leads to a high degree of coupling between fire scar site boundaries and topographic relief. However, the applicability of spatio-temporal data fusion methods for fire scar extraction in such geomorphological areas remains systematically unevaluated. This study developed a spatial–temporal adaptive fusion model integrating Landsat 30-m data with MODIS daily observations to generate continuous high-precision dNBR datasets. Using a typical karst fire region in Guizhou and Yunnan, China, as a case study, we validated the method’s effectiveness for fire trace extraction in fragmented landscapes. The proposed fusion technique addresses cloud cover limitations in humid climates by constructing continuous NBR time series, enabling precise fire boundary delineation and severity quantification. We comparatively implemented multiple fusion approaches (FSDAF, STARFM, and STDFA) and evaluated their performance through both spectral (RMSE, AD, and PSNR) and spatial (Edge, LBP, and SSIM) metrics. Key findings include the following: (1) FSDAF outperformed other methods in spectral consistency and spatial adaptation, particularly for heterogeneous mountainous terrain with fragmented vegetation. (2) Comparative experiments demonstrated that pre-calculating vegetation indices before temporal fusion (Strategy I) produced superior results to post-fusion calculation (Strategy II). Moreover, in our karst landscape study area, our proposed Hybrid Strategy selection framework can dynamically optimize the fusion process of multi-source satellite data, which is significantly better than a single fusion strategy. (3) The dNBR-based extraction achieved 90.00% producer accuracy, 69.23% user accuracy, and a Kappa coefficient of 0.718 when validated against field data. This study advances fire monitoring in karst regions by significantly improving both the spatio-temporal resolution and accuracy of burn scar detection compared to conventional approaches. The framework provides a viable solution for fire impact assessment in topographically complex landscapes under cloudy conditions. Full article

Wildfires significantly impact ecosystems, economies, and biodiversity, particularly in fire-prone regions like the Caatinga biome in Northeastern Brazil. This study integrates machine learning with climate and land use data to model current and future fire dynamics in the Caatinga. Using MaxEnt, fire probability maps were generated based on historical fire scars from Landsat imagery and environmental predictors, including bioclimatic variables and human influences. Future projections under SSP1-2.6 (low-emission) and SSP5-8.5 (high-emission) scenarios were also analyzed. The baseline model achieved an AUC of 0.825, indicating a strong predictive performance. Key drivers of fire risk included the mean temperature of the driest quarter (with an importance of 14.1%) and isothermality (12.5%). Temperature-related factors were more influential than precipitation, which played a secondary role in shaping fire dynamics. Anthropogenic factors, such as proximity to farming and urban areas, also contributed to fire susceptibility. Under the optimistic scenario, low-fire-probability areas expanded to 29.129 Mha, suggesting a reduced fire risk with climate mitigation. However, high-risk zones persisted in the Western Caatinga. The pessimistic scenario projected an alarming expansion of very-high-risk areas to 12.448 Mha, emphasizing the vulnerability of the region under severe climate conditions. These findings underline the importance of temperature dynamics and human activities in shaping fire regimes. Future research should incorporate additional variables, such as vegetation recovery and socio-economic factors, to refine predictions. This study provides critical insights for targeted fire management and land use planning, promoting the sustainable conservation of the Caatinga under changing climatic conditions. Full article

Chyulu Hills, Kenya, serves as one of the region’s water towers by supplying groundwater to surrounding streams and springs in southern Kenya. In a semiarid region, this water is crucial to the survival of local people, farms, and wildlife. The Chyulu Hills is also very prone to fires, and large areas of the range burn each year during the dry season. Currently, there are no detailed fire records or burn scar maps to track the burn history. Mapping burn scars using remote sensing is a cost-effective approach to monitor fire activity over time. However, it is not clear whether spectral burn indices developed elsewhere can be directly applied here when Chyulu Hills contains mostly grassland and bushland vegetation. Additionally, burn scars are usually no longer detectable after an intervening rainy season. In this study, we calculated the Differenced Normalized Burn Ratio (dNBR) and two versions of the Relative Differenced Normalized Burn Ratio (RdNBR) using Landsat Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) data to determine which index, threshold values, instrument, and Sentinel near-infrared (NIR) band work best to map burn scars in Chyulu Hills, Kenya. The results indicate that the Relative Differenced Normalized Burn Ratio from Landsat OLI had the highest accuracy for mapping burn scars while also minimizing false positives (commission error). While mapping burn scars, it became clear that adjusting the threshold value for an index resulted in tradeoffs between false positives and false negatives. While none were perfect, this is an important consideration going forward. Given the length of the Landsat archive, there is potential to expand this work to additional years. Full article

The semi-arid Caatinga biome is particularly susceptible to fire dynamics. Periodic droughts amplify fire risks, while anthropogenic activities such as agriculture, pasture expansion, and land-clearing significantly contribute to the prevalence of fires. This research aims to evaluate the effectiveness of a fire detection model and analyze the spatial and temporal patterns of burned areas, providing essential insights for fire management and prevention strategies. Utilizing deep neural network (DNN) models, we mapped burned areas across the Caatinga biome from 1985 to 2023, based on Landsat-derived annual quality mosaics and minimum NBR values. Over the 38-year period, the model classified 10.9 Mha (12.7% of the Caatinga) as burned, with an average annual burned area of approximately 0.5 Mha (0.56%). The peak burned area reached 0.89 Mha in 2021. Fire scars varied significantly, ranging from 0.18 Mha in 1985 to substantial fluctuations in subsequent years. The most affected vegetation type was savanna, with 9.8 Mha burned, while forests experienced only 0.28 Mha of burning. October emerged as the month with the highest fire activity, accounting for 7266 hectares. These findings underscore the complex interplay of climatic and anthropogenic factors, highlighting the urgent need for effective fire management strategies. Full article

It is of great significance to map forest fire burn scars for post-disaster management and assessment of forest fires. Satellites can be utilized to acquire imagery even in primitive forests with steep mountainous terrain. However, forest fire burn scar mapping extracted by the Burned Area Index (BAI), differenced Normalized Burn Ratio (dNBR), and Feature Extraction Rule-Based (FERB) approaches directly at pixel level is limited by the satellite imagery spatial resolution. To further improve the spatial resolution of forest fire burn scar mapping, we improved the image super-resolution reconstruction via sparse representation (SCSR) and named it modified image super-resolution reconstruction via sparse representation (MSCSR). It was compared with the Burned Area Subpixel Mapping–Feature Extraction Rule-Based (BASM-FERB) method to screen a better approach. Based on the Sentinel-2 satellite imagery, the MSCSR and BASM-FERB approaches were used to map forest fire burn scars at the subpixel level, and the extraction result was validated using actual forest fire data. The results show that forest fire burn scar mapping at the subpixel level obtained by the MSCSR and BASM-FERB approaches has a higher spatial resolution; in particular, the MSCSR approach can more effectively reduce the noise effect on forest fire burn scar mapping at the subpixel level. Five accuracy indexes, the Overall Accuracy (OA), User’s Accuracy (UA), Producer’s Accuracy (PA), Intersection over Union (IoU), and Kappa Coefficient (Kappa), are used to assess the accuracy of forest fire burn scar mapping at the pixel/subpixel level based on the BAI, dNBR, FERB, MSCSR and BASM-FERB approaches. The average accuracy values of the OA, UA, PA, IoU, and Kappa of the forest fire burn scar mapping results at the subpixel level extracted by the MSCSR and BASM-FERB approaches are superior compared to the forest fire burn scar mapping results at the pixel level extracted by the BAI, dNBR and FERB approaches. In particular, the average accuracy values of the OA, UA, PA, IoU, and Kappa of the forest fire burn scar mapping at the subpixel level detected by the MSCSR approach are 98.49%, 99.13%, 92.31%, 95.83%, and 92.81%, respectively, which are 1.48%, 10.93%, 2.47%, 15.55%, and 5.90%, respectively, higher than the accuracy of that extracted by the BASM-FERB approach. It is concluded that the MSCSR approach extracts forest fire burn scar mapping at the subpixel level with higher accuracy and spatial resolution for post-disaster management and assessment of forest fires. Full article

Fires affect forest dynamics in seasonally dry regions such as the Mediterranean Basin. There, fire impacts on tree growth have been widely characterized in conifers, particularly pine species, but we lack information on broadleaf tree species that sprout after fires. We investigated post-fire radial growth responses in two coexisting Mediterranean hardwood species (the evergreen Quercus ilex, the deciduous Celtis australis) using tree-ring width data. We compared growth data from burnt and unburnt stands of each species subjected to similar climatic, soil and management conditions. We also calculated climate–growth relationships to assess if burnt stands were also negatively impacted by water shortage, which could hinder growth recovery. Tree-ring data of both species allowed us to quantify post-fire growth enhancements of +39.5% and +48.9% in Q. ilex and C. australis, respectively, one year after the fire. Dry spring climate conditions reduced growth, regardless of the fire impact, but high precipitation in the previous winter enhanced growth. High June radiation was negatively related to the growth of unburnt Q. ilex and burnt C. australis stands, respectively. Post-fire growth enhancement lasted for five years after the fire and it was a transitory effect because the growth rates of burnt and unburnt stands were similar afterwards. Full article

Atrial fibrillation (AF) in the setting of heart failure (HF) with preserved ejection fraction (HFpEF) is a prevalent comorbidity and is enabled by adverse left atrial (LA) remodeling, dilation, and scar tissue formation. These changes are facilitated by poor left ventricular compliance. A growing body of clinical evidence and medical guidelines suggest that managing atrial tachyrhythms with catheter ablation (CA) is paramount to treating concomitant HF. This recommendation is complicated in that thermal CA modalities, namely radiofrequency ablation and cryoablation, are both therapeutic via inducing additional scar tissue. AF treatment with thermal CA may compound the atrial scar burden for patients who already have extensive scars secondary to HFpEF. Therefore, thermal CA could act as “gasoline” to the slowly burning “fire” within the LA, increasing the rate of AF recurrence. Pulsed-field ablation (PFA), which utilizes high-voltage irreversible electroporation, is a non-thermal CA technique that is capable of disrupting reentrant microcircuits and arrhythmogenic foci without inducing significant scar burden. PFA has the potential to mitigate the strong fibrosis response to thermal CA that predisposes to AF by serving as “water” rather than “gasoline”. Thus, PFA may increase the efficacy and durability of CA for AF in HFpEF, and subsequently, may decrease the risk of procedural complications from repeat CAs. In this article, we provide a summary of the clinical concepts underlying HFpEF and AF and then summarize the data to date on the potential of PFA being a superior CA technique for AF in the setting of comorbid HFpEF. Full article

Over the years, the Cape Peninsula has seen a rise in the number of fires that occur seasonally. This study aimed to investigate the extent of fire spread and associated damages during the 2023/2024 Cape Peninsula fire events. Remote sensing datasets from Sentinel-5P, Sentinel-2, Moderate Resolution Imaging Spectroradiometer (MODIS), and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) were used. Most of the fires on the northern side of the Cape Peninsula had a short burning span of between 6 and 12 h, but fires with a duration of 12–24 h were minimal. The northern area is composed of low forests and thickets as well as fynbos species, which were the primary fuel sources. Excessive amounts of carbon monoxide (CO) and black carbon (BC) emissions were observed. High speeds were observed during the period of the fires. This is one of the factors that led to the spread of the fire. Relative humidity at 60% was observed, indicating slightly dry conditions. Additionally, the Leaf Water Content Index (LWCI) indicated drier vegetation, enhancing fire susceptibility. High temperatures, low moisture and strong winds were the main drivers of the fire. The Normalized Burn Ratio (NBR) values for the targeted fires showed values close to −1, which signifies presence of a fire scar. The study can be of use to those in the fire management agencies and biodiversity conservation in the region. Full article

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional “wet” and “dry” zones that appear to express “deep” geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant “muscovite” that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the “lowlands” of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding “uplands”, such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues. Full article

In 2020, wildfires scarred over 4,000,000 hectares in the western United States, devastating urban populations and ecosystems alike. The significant impact that wildfires have on plants, animals, and human environments makes wildfire adaptation, management, and mitigation strategies a critical task. This study uses satellite imagery from Landsat to calculate burn severity and map the fire progression for the Dolan Fire of central Coastal California which occurred in August 2020. Several environmental factors, such as temperature, humidity, fuel type, topography, surface conditions, and wind velocity, are known to affect wildfire spread and burn severity. The aim of this study is the investigation of the relationship between these environmental factors, estimates of burn severity, and fire spread patterns. Burn severity is calculated and classified using the Difference in Normalized Burn Ratio (dNBR) before being displayed as a time series of maps. The Dolan Fire had a moderate severity burn with an average dNBR of 0.292. The ignition site location, when paired with the patterns of fire spread, is consistent with wind speed and direction data, suggesting fire movement to the southeast of the fire ignition site. Patterns of increased burn severity are compared with both topography (slope and aspect) and fuel type. Locations that were found to be more susceptible to high burn severity featured Long Needle Timber Litter and Mature Timber fuels, intermediate slope angles between 15 and 35°, and north- and east-facing slopes. This study has implications for the future predictive modeling of wildfires that may serve to develop wildfire mitigation strategies, manage climate change impacts, and protect human lives. Full article

The main population of ~5000 threatened Gunnison sage-grouse (GUSG; Centrocercus minimus) in Colorado depends on sagebrush plants that are killed by wildfires, with recovery taking decades, so frequent fire is a threat, but did it occur historically? Early land surveys showed that the historical (preindustrial) fire rotation (FR), the expected period to burn area equal to a focal land area, was 90–143 years in GUSG ranges, which is not classed as frequent fire (≤25 years). However, recent research, based on fire scars on trees at ten sites near sagebrush, suggested some frequent fire historically in the main population. That study was not spatial, essential to estimate FR, so spatial data were created in GIS with land-survey reconstructions, survey dates, fire-scar sites, mapped sagebrush, and Thiessen polygons around sites. The previous study assumed fires that burned 2+ sites likely burned across sagebrush. Historical FRs were calculated several ways over a common period. A recovery estimate of FR was 90–135 years, a land-survey estimate was 82–131 years, and three spatial scar-based estimates were 93–107 years, showing agreement. However, the comparison found that only 8.8% of the land-survey fire area was detected at fire-scar sites. Detailed analysis showed that 10 fire-scar sites were insufficient to detect historical fire sizes and distributions across the large 168,753 ha sagebrush area. Adequate fire reconstruction could require ~45–60 fire-scar sites, making it feasible to study only ~30,000 ha of sagebrush. Using the two remaining methods, which cross-validate, showed frequent fire did not occur historically in the study area, as historical FRs were 82–135 years. Full article