Forest Cover Loss Research Articles

Monitoring forest cover and land use change in the Congo Basin under IPCC climate change scenarios

The Congo Basin tropical forests are home to many endemic and endangered species, and a global hotspot for forest fragmentation and loss. Yet, little has been done to document the region’s rapid deforestation, assess its effects and consequences, or project future forest cover loss to aid in effective planning. Here we applied the Random Forest (RF) supervised classification algorithm in Google Earth Engine (GEE) to map and quantify decadal changes in forest cover and land use (LCLU) in the Congo Basin between 1990 and 2020. We cross-validated our LCLU maps with existing global land cover products, and projected our validated results to 2050 under three climate change scenarios, using the Multiperceptron Artificial Neural Network and Markov chain algorithms of the Idrissi Land Change modeller from TerrSet. We found that, over 5.2% (215,938 km2), 1.2% (50,046 km2), and a 2.1% (86,658 km2) of dense forest cover were lost in the Congo Basin between 1990–2000, 2000–2010, and 2010–2020, totaling approximately 8.5% (352,642 km2) loss estimated between 1990–2020. For the period 2020–2050, we estimated a projected 3.7–4.0% (174,860–204,161 km2) loss in dense forest cover under all three climate change scenarios (i.e., 174,860 km2 loss projected for SSP1-2.6, 199,608 km2 for SSP2-4.5, and 204,161 km2 for SSP5-8.5), suggesting that approximately 12.3–12.6% (527,502 km2–556,803 km2) of dense forest cover could be lost over a 60-year period (1990–2050). Our study represents a novel application of spatial modeling tools and Machine Learning algorithms for assessing long-term deforestation and forest degradation within the Congo Basin, under human population growth and IPCC climate change scenarios. We provide spatial and quantitative results required for supporting long-term deforestation and forest degradation monitoring within Congo Basin countries, especially under the United Nations Framework Convention on Climate Change (UNFCCC) REDD+ (Reduce Emissions from Deforestation and Forest Degradation) program.

Assessment of global carbon dynamics due to mining-induced forest cover loss during 2000–2019 using satellite datasets

Mining activities significantly contribute to forest cover loss (FCL), subsequently altering global carbon dynamics and exacerbating climate change. The present study aims to estimate the contributions of mining-induced FCL to carbon sequestration loss (CSL) and carbon dioxide (CO₂) emissions from 2000 to 2019 using the proxy datasets. For FCL analysis, the global FCL data at 30 m spatial resolution, developed by Hansen et al. (2013), was employed in the Google Earth Engine (GEE) cloud platform. Furthermore, for CSL and CO₂ emissions assessment, Moderate Resolution Imaging Spectroradiometer (MODIS)-based Net Primary Productivity (NPP) data and Zhang and Liang (2020)-developed biomass datasets were used, respectively. The outcomes of the study exhibited approximately 16,785.90 km2 FCL globally due to mining activities, resulting in an estimated CSL of ∼36,363.17 Gg CO₂/year and CO₂ emissions of ∼490,525.30 Gg CO₂. Indonesia emerged as the largest contributor to mining-induced FCL, accounting for 3,622.78 km2 of deforestation, or 21.58% of the global total. Brazil and Canada followed, with significant deforestation and CO₂ emissions. The findings revealed that mining activities are a major driver of deforestation, particularly in resource-rich regions, leading to substantial environmental degradation. The relative FCL was notably high in smaller countries like Suriname and Guyana, where mining activities constituted a significant proportion of total deforestation. The present study underscores the urgent need for robust regulatory frameworks, sustainable land management practices, and coordinated international efforts to mitigate the adverse environmental impacts of mining. The findings of this study can inform policymakers and stakeholders, leading to more effective conservation strategies and benefiting society by promoting environmental sustainability and resilience against climate change.

Impact of forest cover loss on forest dependent avian species in Kenya

Forests provide vital ecosystem services and support a significant proportion of Earth's terrestrial biodiversity. Despite their ecological importance, global deforestation has accelerated in recent decades, posing a grave threat to biodiversity. Birds within these ecosystems are particularly important for conservation efforts, as they serve as indicators of forest health and overall biodiversity. In this study, we examined the relationship between species richness and functional metrics of forest-dependent birds in Kenya, focusing on the impact of habitat degradation and deforestation. Our objective was to determine how forest loss influences species richness and functional diversity indices, potentially leading to increased functional biotic homogenization. Using citizen science data from the Kenya Bird Map, we classified birds into three categories: forest specialists, forest generalists, and forest visitors. Our findings revealed a decline in both taxonomic richness and functional diversity, alongside an increase in functional evenness in response to forest loss, supporting the hypothesis that deforestation drives biotic homogenization. Forest visitors displayed a heightened sensitivity to forest loss, likely due to the reduction of edge habitats and increased human disturbances, underscoring the need for targeted conservation strategies. Our results underscore the critical role that policies like the Kenyan Forest Policy Act can play in mitigating anthropogenic pressures on forests. By highlighting the importance of preserving mature forests and maintaining forested lands, our study emphasizes how such policies could support biodiversity conservation and sustain essential ecosystem functions within Kenya's diverse forest ecosystems.

The importance of legal reserves in the conservation of the Dark-winged Trumpeter, Psophia obscura (Aves − Psophiidae), given climate change in the eastern Amazon

In recent decades, the Amazon rainforest has faced intense forest cover loss, compromising the environmental balance and negatively affecting local biodiversity. Along with these anthropogenic impacts, there are also the effects associated with climate change, which has intensified every year, causing severe droughts.Consequently, the formation of forest fragments is among the main factors of biodiversity loss, leading to a reduction of the species ’ living area, interrupting the gene flow between populations, and facilitating the occurrence of forest fires and hunting. One of the main measures to combat these impacts and their effects is the creation of protected areas by the governments of each country. In Brazil, environmental legislation requires all rural properties to protect a designated percentage of the region’s natural vegetation and that these areas, referred to as legal reserves, cannot be used or modified. However, there is still little information on these legal reserves’ effectiveness regarding their role in maintaining local biodiversity and their complementary function to the country’s official system of Protected Areas. In this sense, as a way to evaluate the effects of anthropogenic impacts on Amazonian biodiversity and the role of legal reserves in the face of predicted climate change, we evaluate how these reserves can contribute to the maintenance of a critically endangered bird species of the Amazon, the Dark-winged Trumpeter (Psophia obscura). This species is restricted to the “Belem Endemism Area (BEA),” located in the extreme east of the Brazilian Amazon. For this, we generated climate suitability models of the target taxon for the present and future pessimistic (SSP5-8.5) and optimistic (SSP2-4.5) scenarios for the year 2100. We obtained 27 unique occurrences of P. obscura within the BEA area. We then compared the area climatically suitable for the occurrence of this bird for the current and future emission scenarios, taking into account the availability of areas in the Legal Reserves within the BEA. Thus, we projected two alternative future scenarios: the first being optimistic with and without mitigation (Fut 4.5 of the implemented Legal Reserves − ILR and Fut 4.5 total legal reserves − RLT), and the second pessimistic with and without mitigation (Fut 8.5 of the ILR and Fut 8.5 TLR). Our results show that the legal reserves currently implemented are not fulfilling their role in conserving P. obscura. However, implementing the TLR that makes up the future scenario with mitigation can reverse this situation.

Examining thedrivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-makingmodels.

The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover changeand susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) productonthe Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models-including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)-was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue.

Co-Management Effects on Forest Restoration in Protected Areas of Bangladesh: A Remote Sensing and GIS-Based Analysis

Co-management is a promising forest governance strategy that integrates local communities’ traditional rights and forest dependencies while aiming to improve forest cover and ecosystem health. Bangladesh, facing high deforestation rates and limited per capita forest area, has implemented co-management initiatives since 2003 to restore forest cover and support the livelihoods of forest-dependent communities. While the socio-economic impacts of co-management are well studied, its effects on forest cover remain underexplored. This study addresses that gap by using three common spectral vegetation indices (NDVI, EVI, and MSAVI), calculated from Landsat 7 data, to analyze forest cover changes in five major protected areas under co-management. The results indicated that dense forest cover (41–71%) was initially prevalent in these areas, but a significant decline occurred between 2004 and 2015, with slope values ranging from −3.7 to −0.96. In contrast, the non-co-managed control site exhibited a much smaller decline (slope: −0.48 to −0.62) across all indices. Notable increases in agricultural land and forest–agriculture mosaics were also observed in the protected areas under co-management. Global Forest Watch data further confirmed substantial forest cover loss, particularly in CWS (158.77 ha) and SNP (0.49 ha). These findings highlight the need to reassess co-management strategies to address ongoing forest degradation.

Predicting the drivers of Bothrops snakebite incidence across Brazil: A Spatial Analysis

Snakebite envenoming poses a significant public health challenge on a global basis, affecting millions of people annually and leading to complications that may result in fatalities. Brazil stands as one of the countries most impacted by snakebite envenoming, with snakes of the Bothrops genus being responsible for most bites. The current study aimed to identify the determinants of Bothrops snakebite incidence across different regions of Brazil. An ecological study was conducted using municipality-aggregated data, with snakebite incidence as the dependent variable. The study period comprised the years 2015–2021. We constructed Species Distribution Models (SDMs) for Bothrops species, and information was collected on precipitation, runoff, maximum and minimum temperatures, native forest, historical forest loss, agriculture, and pasture in each Brazilian municipality. These data were employed to assess the association between snakebite incidence and biotic, climatic, and landscape factors. The data were analyzed using Generalized Least Squares (GLS) regression. The SDMs demonstrated good performance. The average annual snakebite incidence during the study period ranged from zero to 428.89 per 100,000 inhabitants, depending on the municipality. Higher incidence rates were concentrated primarily in municipalities in the northern region of the country. In this study, we found that nationwide, areas with extensive native forests and those that have historically experienced significant loss of forest cover exhibited higher snakebite incidence rates. Additionally, areas with higher temperatures and precipitation levels, as well as greater climatic suitability for the species B. jararaca, showed significantly higher snakebite incidence rates in the South and Southeast of Brazil, respectively. These associations may be linked to increased snake abundance and active behavior, as well as to engagement in activities favoring human-snake contact in these areas. The findings of this study can contribute to the improvement of prevention and control strategies for this public health issue in Brazil.

Mining-induced forest cover change of Paschim Bardhaman, a mining-based district of India

Mining activities are a recognized factor for Forest Cover Loss (FCL) worldwide. Huge forest cover areas are lost due to mining activities worldwide and in India. This study is conducted to identify the villages that experienced more FCL as a result of mining activities and also focuses on identifying the role of individual coal mines on FCL. Results indicate that the mining area increased to 70.79 km2 in 2020 from 25.56 km2 in 1990, and the vegetation area reduced to 149.22 km2 from 271 km2 at the same time. Mostly Jamuria, Barabani, Raniganj, and Pandabeswar blocks have lost large amounts of forest cover due to mining activities. Results also indicate that mining areas have increased nearly threefold and influenced the rate of FCL in the district. Village-level analysis of mining-induced FCL identified that more than ten villages had lost more than 10% of the total forest cover areas due to coal mine expansion resulting in environmental degradation. Analysis of spatial matrices indicates a fragmentation nature of vegetation cover areas of the selected coal mines and indicates that available vegetation areas are concentrated in some pocket areas. Local Indicators of Spatial Autocorrelation (LISA) based spatial patterns of mining-induced FCL show high cluster location in and around major coal mines of the area proving the role of open-cast coal mines on FCL and forest fragmentation. The analysis results may help the planners maintain the healthy environment of the affected villages by formulating alternative ways of forest cover increase.

Temporal assessment of forest cover dynamics in response to forest fires and other environmental impacts using AI.

The rapid reduction of forests due to environmental impacts such as deforestation, global warming, natural disasters such as forest fires as well as various human activities is an escalating concern. The increasing frequency and severity of forest fires are causing significant harm to the ecosystem, economy, wildlife, and human safety. During dry and hot seasons, the likelihood of forest fires also increases. It is crucial to accurately monitor and analyze the large-scale changes in the forest cover to ensure sustainable forest management. Remote sensing technology helps to precisely study such changes in forest cover over a wide area over time. This research analyzes the impact of forest fires over time, identifies hotspots, and explores the environmental factors that affect forest cover change. Sentinel-2 imagery was utilized to study changes in Brunei Darussalam's forest cover area over five years from 2017 to 2022. An object-based approach, Simple Non-Iterative Clustering (SNIC), is employed to cluster the region using NDVI values and analyze the changes per cluster. The results indicate that the area of the clusters reduced where fire incidence occurred as well as the precipitation dropped. Between 2017 and 2022, the increased forest fires and decreased precipitation levels resulted in the change in cluster areas as follows: 66.11%, 69.46%, 68.32%, 73.88%, 77.27%, and 78.70%, respectively. Additionally, hotspots in response to forest fires each year were identified in the Belait district. This study will help forest managers assess the causes of forest cover loss and develop conservation and afforestation strategies.

Global analysis of forest tipping points leading to changing water cycle dynamics

Forest cover loss is increasing at unprecedented rates, affecting the hydrologic systems of major freshwater-producing regions of the world. However, quantification of the tipping points of forest cover loss before hydrologic changes manifest and their impact in water yield and climatic conditions has remained elusive. In this study, we aim to systematically document the critical thresholds of tree cover loss leading to changing hydrologic functioning within regions that experienced extensive drought, fire, or clear-cutting events spanning different climates during the period from 2001 to 2016. Using the Hydrologic Sensitivity Index based on Budyko’s curve, we analyzed the changes in hydrologic responses to climate variability as landcover changes across the affected forests. Critical thresholds were derived by fitting Richard’s Curve function to the observed relationship between growing sensitive area and tree cover loss. Our analysis reveals decrease in water yields and warming trends during the early stages of tree cover loss in tropical forests (c = 16 %), with negative anomalies observed in rainforests of Central Africa and Maritime Southeast Asia. Boreal forests also show low thresholds (c = 18 %) with a strong tendency toward a warmer climate state and no clear tendency in water yields. Mixed forests show moderate thresholds (c = 25 %) with unclear water yield and climate trends. Conversely, Temperate forests exhibit the most resilience to hydrologic regime shifts with high critical thresholds of tree cover loss (c = 46––54 %), but a rapid alteration once their threshold is surpassed resulting primarily in increased water yields and a shift toward cooler climate conditions. As the potential for additional tree cover loss heightens, due to expected increases in the frequency and intensity of droughts and wildfires, the analyses presented provides a quantitative framework to monitor and assess the impacts of changing forest cover conditions on the water cycle behavior of some of the largest freshwater producing regions of the world.

Can Change in Forest Cover Be Linked to the Management Effectiveness of Protected Areas? The Indian Scenario

Protected areas are an effective mechanism usually supported by a statute to conserve and protect wildlife-rich areas worldwide. Such extensive external management needs elaborate planning, regular monitoring, and periodic assessment of results. Thus, management effectiveness evaluation (MEE) has emerged as one of the major tools for quantifying the performance of any protected area globally since 2006. India has successfully conducted a complete round of management effectiveness evaluation of all its terrestrial protected areas (except conservation reserves and community reserves), with 25 such areas already undergoing a repeat assessment. Simultaneously, India biennially carries out a country-wide status of forest cover in all its states and union territories. This study has correlated the trend in change in forest cover for the states that contain those 25 repeat evaluated protected areas with their change in MEE scores over the same period. Our study found a positive correlation between the change in forest cover and the change in management effectiveness score from 2005–2006 to 2018–2019. Owing to increased protection regimes in the PAs including the degraded areas if they make part of such areas, the habitat often shows recovery. Effective habitat conservation is thus intertwined with the monitoring and preservation of the wildlife populations in the protected areas; therefore, reduction in forest cover equally impacts the management scores. However, in states where the loss in forest cover has been reported, more protected areas need to be assessed to plan complementary strategies for both habitat and species conservation.

Environmental Dynamics in The Sumatran Coffee Landscapes: Opportunities and Challenges Through Spatial Perspectives

The coffee industry in Indonesia, particularly in the Sumatran landscape, emerges as a vital contributor to the nation's economy, impacting regional growth. Nevertheless, this landscape faces ecological threats from rapid deforestation, resulting in a substantial loss of primary forest cover. This historical deforestation along with climate crisis presents challenges for coffee plantations. The study employs geospatial analysis to comprehensively outline challenges and opportunities for smallholder coffee farmers in Sumatra, particularly in the Arabica (Central Aceh) and Robusta (Tanggamus) landscapes. The study shows non-shade coffee plantations covered approximately 23,453 ha in Central Aceh and 43,991 ha in Tanggamus. Additionally, mixed agroforestry areas were prevalent, comprising about 132,569 ha in Tanggamus and 19,450 ha in Central Aceh. Tanggamus and Central Aceh have become favorable areas for Robusta coffee and Arabica coffee, respectively. One significant opportunity identified for coffee development in Central Aceh is that 86% of existing coffee farms already adhere to EUDR. Furthermore, 94% of existing coffee farms in Tanggamus meet EUDR standards, opening doors for more farmers to access the European market.

Forest cover lessens hurricane impacts on peak streamflow

AbstractCyclonic storms (i.e., hurricanes) are powerful disturbance events that often cause widespread forest damage. Storm‐related canopy damage reduces rainfall interception and evapotranspiration, but impacts on streamflow regimes are poorly understood. We quantify streamflow changes in Puerto Rico following Hurricane Maria in September 2017, and evaluate whether forest cover and storm‐related canopy damage account for the differences. Streams are particularly vulnerable to flooding in early post‐disturbance stages during hurricane season, so we focus on 3 months (Oct–Dec) following the hurricane. To discern changes in rainfall responses, we partitioned streamflow into baseflow and quickflow using a digital filter. We collected 2010–2017 streamflow and rainfall data from 18 watersheds and compared the relative magnitude of post‐ to pre‐hurricane double mass curve slopes of baseflow and quickflow volumes against rainfall. Several watersheds displayed higher post‐hurricane quickflow and baseflow, however, the response was variable. The magnitude of quickflow increase was greater in watersheds with high forest damage. Under the same level of relative damage, watersheds with low initial forest cover had greater quickflow increases than highly forested ones. Conversely, baseflow generally increased, but increases were greater in highly forested watersheds and smaller in highly damaged watersheds. These results suggest that post‐storm baseflow increases were due to recharge of hurricane‐related rainfall, as well as forest transpiration interruption and soil disturbance enhancing recharge of post‐hurricane rainfall, while increases to quickflow are related to loss of canopy rainfall interception and higher soil saturation decreasing infiltration. Our research demonstrates that forest damage from disturbance lowers quickflow and elevates baseflow in highly forested watersheds, and elevates quickflow and lowers baseflow in less‐forested watersheds. Less‐forested watersheds may be closer to the forest cover loss threshold needed to elicit a streamflow response following disturbance, suggesting higher flooding potential downstream, and a lower storm‐related forest disturbance threshold than in heavily forested watersheds.

Climate change impacts of forest conversion (Study on forest conversion for food estate/ national food granary program in Central Kalimantan)

Background: The Food Estate policy or national food granary program is a food development concept that is integrated with agriculture, plantations and animal husbandry, one of which is in the area of openings in natural forests covering an area of 156,000 ha in Central Kalimantan. This program is designed to prepare national food security in order to respond to the Food and Agriculture (FAO) Report on the threat of a global food crisis due to the impact of the Covid 19 pandemic. Changes in forest cover from previously green land to agricultural land will cause loss of forest cover in the form of vegetation or trees that have ecosystem services as carbon dioxide absorbers from the air. Methods: The impact of forest conversion is analyzed by conducting spatial analysis of land cover and calculating potential carbon stocks lost, as well as providing suggestions or solutions to problems or gaps from an economic, social, and political environmental perspective. Findings: From the results of literature studies, the government must learn from the experience of food estate projects on peatlands in the past where peatlands became thin and when the dry season arrived, the land would be flammable due to lack of attention to the biophysical aspects of the soil. Conclusion: In addition, economic and social aspects involve and assist the community in carrying out food security programs and agricultural technology sophistication. Novelty/Originality of this Study: This analysis provides a unique perspective on the climate change impacts of forest conversion for food estate programs, bridging the gap between national food security policies and environmental conservation imperatives.

Impact of deforestation and climate on spatio-temporal spread of dengue fever in Mexico

Dengue prevalence results from the interaction of multiple socio-environmental variables which influence its spread. This study investigates the impact of forest loss, precipitation, and temperature on dengue incidence in Mexico from 2010 to 2020 using a Bayesian hierarchical spatial model. Three temporal structures—AR1, RW1, and RW2—were compared, with RW2 showing superior performance. Findings indicate that a 1 % loss of municipal forest cover correlates with a 16.9 % increase in dengue risk. Temperature also significantly affects the vectors' ability to initiate and maintain outbreaks, highlighting the significant role of environmental factors. The research emphasizes the importance of multilevel modeling, finer temporal data resolution, and understanding deforestation causes to enhance the predictability and effectiveness of public health interventions. As dengue continues affecting global populations, particularly in tropical and subtropical regions, this study contributes insights, advocating for an integrated approach to health and environmental policy to mitigate the impact of vector-borne diseases.

Investigating of Spatial Urban Growth Pattern and Associated Landscape Dynamics in Congolese Mining Cities Bordering Zambia from 1990 to 2023

This study investigates the spatial urban growth patterns of cities along the Democratic Republic of the Congo (DRC) and Zambia border, a region of significant economic importance characterized by cross-border trade. This activity has led to rapid but unplanned urban growth. The objective is to quantify the spatial expansion of Congolese cities (Kipushi, Kasumbalesa, Mokambo, and Sakania) bordering Zambia and to evaluate associated landscape changes. The methodology of this study includes the supervised classification of Landsat images with a spatial resolution of 30 m for the years 1990, 2000, 2010, and 2023. This classification was validated using field data. Subsequently, landscape metrics such as class area, patch number, Shannon diversity index, disturbance index, urban expansion intensity index, largest patch index, and mean Euclidean distance were calculated for each city and each date. The results reveal substantial landscape transformations in the border cities between 1990 and 2023. These changes are primarily driven by rapid urban expansion, particularly pronounced in Kasumbalesa. Between 1990 and 2023, forest cover declined from 70% to less than 15% in Kipushi, from 80% to 10% in Kasumbalesa, from 90% to 30% in Mokambo, and from 80% to 15% in Sakania. This forest cover loss is accompanied by an increase in landscape element diversity, as indicated by the Shannon diversity index, except in Kipushi, suggesting a transition towards more heterogeneous landscapes. In these border cities, landscape dynamics are also characterized by the expansion of agriculture and savannas, highlighted by an increase in the disturbance index. Analysis of spatial pattern changes shows that built-up areas, agriculture, and savannas exhibit trends of patch creation or aggregation, whereas forests are undergoing processes of dissection and patch attrition. Congolese cities bordering Zambia are undergoing substantial spatial changes propelled by intricate interactions between economic, demographic, and infrastructural factors. Our results underscore the need for sustainable development strategies to address urban sprawl through smart growth policies and mixed-use developments, mitigate deforestation via stricter land use regulations and reforestation projects, and enhance cross-border cooperation through joint environmental management and collaborative research initiatives.

Monitoring deforestation, forest health, and environmental criticality in a protected area periphery using Geospatial Techniques.

Protected areas in South Asia face significant challenges due to human disturbance and deforestation. The ongoing debate surrounds the recent surge in illegal encroachment of forest buffer zones in the Musali divisional secretariat division (DSD), which has led to a significant loss of forest cover over the past three decades. In this context, detecting changes in forest cover, assessing forest health, and evaluating environmental quality are crucial for sustainable forest management. As such, our efforts focused on assessing forest cover dynamics, forest health, and environmental conditions in the DSD from 1988 to 2022. We employed standardized image processing techniques, utilizing Landsat-5 (TM) and Landsat-8 (OLI) images. However, the forest area in the DSD has shown minimal changes, and environmental conditions and forest health have illustrated considerable spatial-temporal variations over the 34 years. The results indicated that 8.5 km2 (1.9%) of forest cover in the DSD has been converted to other land use classes. Overall, the Normalized Difference Vegetation Index (NDVI) has declined over time, while Land Surface Temperature (LST) exhibits an increasing trend. The regression results demonstrated a robust inverse relationship between LST and NDVI. The declining vegetation conditions and the increasing LST contribute to an increase in environmental criticality. The derived maps and indices will be beneficial for forest authorities in identifying highly sensitive locations. Additionally, they could enable land use planners to develop sustainable land management strategies.

Typhoon-Induced Forest Damage Mapping in the Philippines Using Landsat and PlanetScope Images

Forests provide valuable resources for households in the Philippines, particularly in poor and upland communities. This makes forests an integral part of building resilient communities. This relationship became complex during extreme events such as typhoon occurrence as forests can be a contributor to the intensity and impact of disasters. However, little attention has been paid to forest cover losses due to typhoons during disaster assessments. In this study, forest damage caused by typhoons was measured using harmonic analysis of time series (HANTS) with Landsat-8 Operation Land Imager (OLI) images. The ΔHarmonic Vegetation Index was computed by calculating the difference between HANTS and the actual observed vegetation index value. This was used to identify damaged areas in the forest regions and create a damage map. To validate the reliability of the results, the resulting maps produced using ΔHarmonic VI were compared with the damage mapped from PlanetScope’s high-resolution pre- and post-typhoon images. The method achieved an overall accuracy of 69.20%. The accuracy of the results was comparable to the traditional remote sensing techniques used in forest damage assessment, such as ΔVI and land cover change detection. To further the understanding of the relationship between forest and typhoon occurrence, the presence of time lag in the observations was investigated. Additionally, different contributing factors in forest damage were identified. Most of the forest damage observed was in forest areas with slopes facing the typhoon direction and in vulnerable areas such as near the coast and hill tops. This study will help the government and forest management sectors preserve forests, which will ultimately result in the development of a more resilient community, by making it easier to identify forest areas that are vulnerable to typhoon damage.

Quantifying Forest Cover Loss during the COVID-19 Pandemic in the Lubumbashi Charcoal Production Basin (DR Congo) through Remote Sensing and Landscape Analysis

In the context of the Lubumbashi Charcoal Production Basin (LCPB), the socio-economic repercussions of the COVID-19 pandemic have exacerbated pressures on populations dependent on forest resources for their subsistence. This study employs a comprehensive methodological approach, integrating advanced remote sensing techniques, including image classification, mapping, and detailed landscape analysis, to quantify alterations in forest cover within the LCPB during the pandemic period. Our findings reveal a consistent trend of declining forested area, characterized by processes of attrition and dissection observed throughout various study phases, spanning from May 2019 to November 2023. This reduction in forest cover, notably more pronounced in the vicinity of Lubumbashi city and the northern zone of the LCPB, proved to be less pronounced between November 2019 and September 2020, underscoring the influence of COVID-19 pandemic-induced confinement measures on forest management practices in the region. However, subsequent to this period of restriction, deforestation activity intensified, leading to significant landscape transformations within the LCPB, primarily attributable to expanded human activities, consequently resulting in a notable decrease in the proportion of land occupied by these natural ecosystems. Consequently, the size of the largest forest patch declined substantially, decreasing from 14.62% to 8.20% between May 2019 and November 2023, thereby fostering a heightened density of forest edges over time. Our findings provide a significant contribution to understanding the complex interactions between the COVID-19 pandemic and deforestation phenomena, emphasizing the urgent need to adopt adaptive management strategies and appropriate conservation measures in response to current economic challenges.

Fertilizer prices and deforestation in Africa

This study explores the impact of fertilizer (urea) prices on local deforestation by exploiting the exogenous variation in the world price of urea inclusive of trade costs from the world market to the local market. The empirical analysis relies on a unique geo-coded dataset on the market price of urea across 158 subnational hub markets in 21 African countries and satellite-derived forest loss estimates over the period 2003 – 2012. The results suggest that fertilizer prices positively affect deforestation rate and forest cover loss. On average, a 1 % increase in local urea prices corresponds to 97.65 Ha of forest loss within a particular local market catchment. Specifically, the results reveal a price elasticity of approximatively 1 between urea prices and forest loss. The heterogeneity analysis suggests that the effects of urea prices on forest loss tend to be concentrated in markets with subtropical and tropical ecological features. Furthermore, I provide evidence for the land-conversion mechanism, implying that urea prices are positively associated with the expansion of agricultural land. Estimating an event study around exposure to a sustained jump in urea prices reveals a persistent response of deforestation and forest cover loss to fertilizer prices.