Search Results (144)

Land-use and land-cover change (LULCC) is a crucial indicator of environmental transformation and has significant implications for biodiversity, ecosystem services, and climate change. This study investigates land-cover changes between 2017 and 2023 in three distinct mountain regions: the Bucegi Mountains, the Allgäu High Alps, and Mount Olympus. Using remote-sensing data from Sentinel 2 and Geographic Information System (GIS) tools, we analyzed temporal shifts in land-cover types across these regions. The analysis highlights the varying rates and patterns of land-cover transformation in response to environmental and anthropogenic factors. Additionally, the MOLUSCE model was employed to predict future land-cover changes for the year 2029. The findings emphasize the dynamic nature of land-cover in these mountainous areas and offer insights into the potential environmental implications of predicted changes. The Bucegi and the Olympus regions experienced minor land-use changes, while the Allgäu High Alps have the most dynamic changes. The study contributes to a deeper understanding of land-cover dynamics and the applicability of remote sensing and GIS-based predictive models in ecological monitoring. Full article

Urban Flooding is one of the most prevalent natural hazards worldwide, leading to substantial human and economic losses. Therefore, the assessment and mapping of flood hazard levels are essential for reducing the impact of future flood disasters. This study develops and integrates a methodology to evaluate urban flood susceptibility in Nangarhar Province, Afghanistan, a semi-arid region with limited prior research. Landsat imagery from 2004 to 2024 was used to analyze land use land cover change (LULCC), indicating that built-up areas increased from 124 to 180 km² in 2004 to 2024, respectively, while agricultural land decreased from 1978 km² to 1883 km² during the same period. Climate data exhibit increases in temperatures and intensifying rainfall, exacerbating flood hazards. Geospatial analysis of elevation, slope, drainage density, and proximity to water bodies highlights the high susceptibility of low-lying areas. The Analytical Hierarchy Process (AHP) was employed to integrate diverse flood risk factors and produce accurate flood hazard maps. The findings show that very-high flood susceptibility zones expanded from 1537 to 1699 km² in 2004 to 2024, whereas low-susceptibility zones declined from 131 km² to 110 km². Socioeconomic indicators such as population density, built-up density, and education accessibility were also incorporated into the assessment. This study underscores the need for adaptive land use planning, resilient drainage systems, and community-based flood risk reduction strategies. The findings provide actionable insights for sustainable flood management and demonstrate the value of combining GIS, remote sensing, and multi-criteria analysis in data-scarce, conflict-affected regions. Full article

Under the context of global climate change and China’s dual carbon strategy (DCS), the impact of land use/land cover change (LULCC) on regional carbon stocks has garnered increasing attention. As a key economic and ecological hub in Southwest China, Chengdu has undergone significant urbanization over the past two decades, and it is necessary to quantitatively assess how shifts in land use affect its carbon stock function. This study integrates multi-period remote sensing data from 2000 to 2020, combining socioeconomic and natural environmental drivers. The PLUS model was employed to simulate land use in 2030 under four scenarios: Natural Development Scenario (NDS), Urban Development Scenario (UDS), Conservation of Cropland Scenario (CPS), and Ecological Protection Scenario (EPS). The InVEST model was then used to calculate changes in carbon stocks and their spatial distribution characteristics. The results indicate the following: (1) From 2000 to 2020, Chengdu’s cropland decreased by 1188.6174 km², while built-up land increased by 1006.5465 km², resulting in a net carbon stock decrease of approximately 3.25 × 10⁶ t, with carbon gains from forest restoration offsetting part of the cropland-to-built-up loss; (2) Under all scenarios, built-up land exhibited an expansion trend, with the UDS showing the most significant increase, reaching 1919.2455 km². In the EPS, the forest increased to 4035.258 km², achieving the largest carbon stock increase of 8.5853 × 10⁶ t. (3) Chengdu’s carbon stock exhibits a spatial distribution pattern characterized by “high in the northwest, low in the center”. High-value areas are concentrated in the ecologically sound Longmen Mountains and Longquan Mountains, while low-value areas are primarily located in urban built-up zones and their peripheries. The study indicates that rationally controlling the expansion of Built-up land, strengthening ecological restoration, and protecting forests can effectively enhance Chengdu’s carbon sink capacity and achieve regional low-carbon and sustainable development. This study aims to address the gap in carbon stock assessments under different development scenarios at the urban scale in Southwest China, and to provide a scientific basis for Chengdu’s regional spatial planning, ecological conservation, low-carbon development, and sustainable land management. Full article

Protected areas (PAs) are increasingly exposed to anthropogenic pressures under global change scenarios, with surrounding land subdivision and land use/land cover change (LULCC) dynamics often undermining their conservation goals and intensifying demand for basic services such as water availability. This study analyzed the buffer zone around Cerro Castillo National Park in Chilean Patagonia to assess the evolution of rural private properties, considering their subdivision, LULCC, and legal water demand dynamics. Using cadastral records, Landsat 8 imagery, and official water rights databases, we quantified property subdivision and analyzed LULCC and water rights distribution patterns through spatial overlap analysis. Results indicate a nearly fourfold increase in subdivisions between 2011 and 2023, with 304 properties divided into 3237 units occupying 43.7% of the private land area. LULCC analysis revealed a net recovery of native forest (+10%) alongside notable increases in urban coverage (+152%) and exotic plantations (+245%). Legal water demand almost doubled, with 68% of consumptive rights concentrated in subdivided properties. These findings highlight property subdivision as an important factor influencing socioecological change in the territories that surround PAs. We argue that subdivision dynamics can serve as an early indicator for anticipating land use pressures and can complement integrated landscape-scale planning, consistent with the transformative change approaches advocated by international biodiversity frameworks. Full article

Avocado orchards are among the most profitable and fastest-growing commodity crops in Mexico, especially in the area known as the “Avocado Belt”. Several efforts have been made to monitor their expansion; however, there is currently no method that can be easily updated to track this expansion. The main objective of this study was to monitor the expansion of avocado orchards from 1993 to 2024, using the Continuous Change Detection and Classification (CCDC) algorithm and Landsat 5, 7, 8, and 9 imagery. Presence/absence maps of avocado orchards corresponding to 1 January of each year were used to perform a trajectory analysis, identifying eight possible change trajectories. Finally, maps from 2020 to 2023 were verified using reference data and very-high-resolution images. The maps showed a level of agreement = 0.97, while the intersection over union for the avocado orchard class was 0.62. The main results indicate that the area occupied by avocado orchards more than tripled from 1993 to 2024, from 64,304.28 ha to 200,938.32 ha, with the highest expansion occurring between 2014 and 2024. The trajectory analysis confirmed that land conversion to avocado orchards is generally permanent and happens only once (i.e., gain without alternation). The method proved to be a robust approach for monitoring avocado orchard expansion and could be an attractive alternative for regularly updating this information. Full article

The Euphrates–Tigris Basin is experiencing significant environmental transformations due to climate change, Land Use and Land Cover Change (LULCC), and anthropogenic pressures. This study employs Earth Map, an open-access remote sensing platform, to comprehensively assess climate trends, vegetation dynamics, water resource variability, and land degradation across the basin. Key findings reveal a geographic shift toward aridity, with declining precipitation in high-altitude headwater regions and rising temperatures exacerbating water scarcity. While cropland expansion and localized improvements in land productivity were observed, large areas—particularly in hyperarid and steppe zones—show early signs of degradation, increasing the risk of dust source expansion. LULCC analysis highlights substantial wetland loss, irreversible urban growth, and agricultural encroachment into fragile ecosystems, with Iraq experiencing the most pronounced transformations. Climate projections under the SSP245 and SSP585 scenarios indicate intensified warming and aridity, threatening hydrological stability. This study underscores the urgent need for integrated water management, Land Degradation Neutrality (LDN), and climate-resilient policies to safeguard the basin’s ecological and socioeconomic resilience. Earth Map is a vital tool for monitoring environmental changes, offering rapid insights for policymakers and stakeholders in this data-scarce region. Future research should include higher-resolution datasets and localized socioeconomic data to improve adaptive strategies. Full article

African hydrological systems are incredibly complex and highly sensitive to climate variability. This review synthesizes observational data, remote sensing, and climate modeling to understand the interactions between fluvial processes, water cycle dynamics, and anthropogenic pressures. Currently, these systems are experiencing accelerating warming (+0.3 °C/decade), leading to more intense hydrological extremes and regionally varied responses. For example, East Africa has shown reversed temperature–moisture correlations since the Holocene onset, while West African rivers demonstrate nonlinear runoff sensitivity (a threefold reduction per unit decline in rainfall). Land-use and land-cover changes (LULCC) are as impactful as climate change, with analysis from 1959–2014 revealing extensive conversion of primary non-forest land and a more than sixfold increase in the intensity of pastureland expansion by the early 21st century. Future projections, exemplified by studies in basins like Ethiopia’s Gilgel Gibe and Ghana’s Vea, indicate escalating aridity with significant reductions in surface runoff and groundwater recharge, increasing aquifer stress. These findings underscore the need for integrated adaptation strategies that leverage remote sensing, nature-based solutions, and transboundary governance to build resilient water futures across Africa’s diverse basins. Full article

Understanding forest-cover change and its drivers is vital for global forest management and policy development. This study analyzed perceptions of historical drivers behind land-use/land-cover change (LULCC) and forest change in gazetted forests from 1966 to 2022 to evaluate the impact of human activities around the gazetted forest reserves, comparing three forests in Nasarawa State, North Central Nigeria. Data were collected through questionnaires, interviews, and focus group discussions. Three gazetted forests (Doma, Risha, and Odu) were sampled to represent the three geopolitical zones of the state. SPSS IBM version 29, NVivo 1.7, and Python 3 were used for data analyses to generate statistics and identify coherent themes across the forests. Results show that changes were perceived to be triggered by sixteen drivers (direct and indirect) related to social, economic, environmental, policy/institutional, and technological elements. Agricultural expansion, lumbering, and charcoal production were the most reported direct drivers, while population growth, poverty, and government policies were the most perceived indirect drivers. The results showed variations in human activities across forest sites. For example, agricultural expansion, lumbering, and grazing were more widespread, while construction and settlement activities differed between forests. The Risha forest community saw agriculture expansion ahead of other drivers, Doma forest people saw population growth above other drivers, and the Odu forest community saw lumbering aiding other drivers that led to change. Implementation of policies focusing on these key drivers must match local perceptions and priorities to engage people in forest conservation. These efforts could ensure effective forest protection that is vital for achieving global biodiversity and climate targets and safeguarding local livelihoods. The specific drivers of changes in each forest need to be targeted in conservation efforts. Full article

Carbon emissions from land use account for a significant portion of anthropogenic carbon emissions. As an important policy instrument for regulating land use, spatial planning can shape future land patterns, thereby influencing human activities and associated carbon emissions. This review presents a scientometric analysis of important articles between 2000 and 2024 on the impacts of land use and spatial planning on carbon emissions, and it summarizes the key research topics, methods, and main consensus. Scientometric and qualitative analysis methods were used. The results showed the following: (1) The number of articles published reveals an increasing trend, especially after 2009, with China, the USA, and England paying more attention to it. (2) Studies mainly focus on four key research topics: the impacts of land use and land cover change (LULCC) on carbon stocks, the relationship between land use structure/spatial form and carbon emissions, and the paths and schemes for low-carbon spatial planning. (3) Studies usually use upscale, homoscale, and downscale routes to correlate carbon emissions to land and then use comparative analysis, regression analysis, spatial analysis, and scenario simulation methods to conduct further analyses. (4) Studies have yielded some consensus: human land use can influence carbon emissions through LULCC, land use structure and spatial form, and spatial planning can reduce carbon emissions. In conclusion, this paper proposes that future research could be deepened in the following aspects: introducing land property rights and spatial planning management systems as research preconditions; exploring the sensitivity of carbon emissions from human activities to land space; strengthening research on low-carbon planning at medium- and long-term time scales and micro- and meso-spatial scales. Full article

Increasing forest destruction from land use and land cover change (LULCC) has altered catchment hydrological processes worldwide. This trend is also endemic to the Belize River Watershed (BRW), a significant source of land and water resources for Belize. This study aims to understand LULCC impacts on BRW hydrological responses from 2000 to 2020 by applying the widely used Soil and Water Assessment Tool (SWAT). This study identified historical trends in LULCC in the BRW and explored an alternative 2020 land cover scenario to elucidate the role of protected forests for hydrological response regulation. A SWAT model for the BRW was developed at the monthly timescale and calibrated on in situ streamflow using SWAT Calibrations and Uncertainty Programs (SWAT-CUP). The results showed that the BRW SWAT model performed satisfactorily for streamflow simulation at the Benque Viejo (BV) gauge station but performed variably at the Double Run (DR) gauge station. Overall, the findings revealed watershed-level increases in monthly average sediment yield (34.40%), surface runoff (24.95%), streamflow (16.86%), water yield (16.02%), baseflow (11.58%), and percolation (3.40%), and decreases in monthly average evapotranspiration (ET) (3.52%). In conclusion, the BRW SWAT model is promising for uncovering the hydrological impacts of LULCCs with opportunities for further model improvement. Full article

Land use and land cover change (LULCC) can influence giant panda distributions by altering landscape structure and configuration. However, the spatial impacts and potential time lag effects of landscape pattern changes on giant pandas remain underexplored. In this study, we applied a random forest classification method to analyze LULCC in 1990, 2000, and 2010, alongside calculating a set of landscape metrics to assess changes in landscape fragmentation, connectivity, and diversity. Random forest regression models were then used to evaluate the spatial relationships between landscape metrics and giant panda density, with the aim of identifying whether a time lag effect exists. The results revealed the following: (1) The random forest classification achieved high land use classification accuracy. Forests remained the dominant land cover, occupying approximately 97% of the study area throughout the period, with only minor fluctuations observed among other land use types. (2) Landscape metrics indicated increasing landscape fragmentation, connectivity, and diversity. While increased landscape fragmentation can negatively impact giant panda habitat, improvements in landscape connectivity and diversity could mitigate these effects by preserving movement corridors and enhancing habitat accessibility. (3) The strongest correlations between giant panda density and landscape metrics were observed when the time points aligned. Landscape metrics from 2010 showed the highest correlation with the 4th NGPS (around 2010), and landscape metrics from 2000 had the highest correlation with the 3rd NGPS (around 2000). The results revealed that giant panda density responded most strongly to contemporary landscape pattern changes, suggesting an immediate response. However, correlations with earlier landscape metrics also suggest that a relatively weak time lag effect may be present. All landscape metrics were derived from remote sensing data, enabling scalable and repeatable GIS-based analysis. These findings highlight the utility of spatial landscape indicators for monitoring species distribution patterns and underscore the importance of maintaining and enhancing habitat connectivity within giant panda conservation efforts. Full article

Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced. Full article

Land use and land cover change (LULCC) is a key driver of carbon storage changes, especially in complex coastal ecosystems such as the Yellow River Delta (YRD), which is jointly influenced by climate change and resource development. The compounded effects of sea-level rise (SLR) and land subsidence (LS) are particularly prominent. This study is the first to integrate the dual impacts of SLR and LS into a unified framework, using three climate scenarios (SSP1–26, SSP2–45, SSP5–85) provided in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with LS monitoring data, to comprehensively assess future inundation risks. Building on this, and taking into account land use and ecological protection policies in the YRD, three strategic scenarios—Ecological Protection Scenario (EPS), Natural Development Scenario (NDS), and Economic Growth Scenario (EGS)—are established. The PLUS and InVEST models are used to jointly simulate LULCC and carbon storage changes across these scenarios. Unlike previous studies focusing on single driving factors, this research innovatively develops a dynamic simulation system for LULCC and carbon storage driven by the SLR-LS compound effects, providing scientific guidance for land space development and coastal zone planning in vulnerable coastal areas, while enhancing carbon sink potential. The results of the study show the following: (1) Over the past 30 years, the land use pattern of the YRD has generally extended toward the sea, with land use transitions mainly from grasslands (the largest reduction: 1096.20 km²), wetlands, reservoirs and ponds, and paddy fields to drylands, culture areas, construction lands, salt pans, and tidal flats. (2) Carbon storage in the YRD exhibits significant spatial heterogeneity. Low-carbon storage areas are primarily concentrated in the coastal regions, while high-carbon storage areas are mainly found in grasslands, paddy fields, and woodlands. LULCC, especially the conversion of high carbon storage ecosystems to low carbon storage uses, has resulted in an overall net regional carbon loss of 2.22 × 10⁶ t since 1990. (3) The risk of seawater inundation in the YRD is closely related to LS, particularly under low sea-level scenarios, with LS playing a dominant role in exacerbating this risk. Under the EGS, the region is projected to face severe seawater inundation and carbon storage losses by 2030 and 2060. Full article

Farmland covers present diverse characteristics, methods, and techniques to monitor and evaluate crops in other geographic areas. This study systematically reviews Land Use/Land Cover Change (LULCC) in agricultural land in Chile through a systematic review of the scientific literature. Using the PRISMA 2020 method, the Web of Science (WOS) database was consulted using the keywords “Landuse”, “Landcover”, “Agriculture”, and “Chile”. We applied six exclusions criteria and constructed a matrix to select relevant aspects, such as title, year of publication, study area and period, methods used, and principal results. In our review, we identified four studies that focused specifically on agricultural land dynamics, mainly in south-central Chile. Chile was selected as the study area due to its geographical diversity, which poses significant challenges for decision-making in land use regulation. These results underscore the need for more spatially informed data on farmland dynamics to inform decision-making, particularly during the alternatives evaluation stage. In this phase, it is essential to assess the impacts on and potential of the territory in order to define suitable economic activities. Although there are numerous studies on LULCC, most emphasize changes in native forests, underscoring the need to address LULCC more comprehensively by considering other land categories, such as agricultural land, shrublands, grasslands, and others. This evidence is crucial for designing practical land management tools and identifying areas that have been extensively studied but lack sufficient research. Full article

Free trade zones are key regions experiencing rapid economic growth, urbanization, and a sharp increase in population density. During the development of free trade zones, these areas undergo drastic transformations in landscape types, large-scale urban construction, heightened resource consumption, and other associated challenges. These factors have led to severe landscape ecological risk (LER). Therefore, conducting comprehensive assessments and implementing effective management strategies for LER is crucial in advancing ecological civilization and ensuring high-quality development. This study takes Hainan Island (HI), China, as a case study and utilizes multi-source data to quantitatively evaluate land use and land cover change (LULCC) and the evolution of the LER in the study area from 2015 to 2023. Additionally, it examines the spatial patterns of LER under three future scenarios projected for 2033: a natural development scenario (NDS), an economic priority scenario (EPS), and an ecological conservation scenario (ECS). Adopting a spatiotemporal dynamic perspective framed by the “historical–present–future” approach, this research constructs a zoning framework for LER management to examine the temporal and spatial processes of risk evolution, its characteristics, future trends, and corresponding management strategies. The results indicate that, over an eight-year period, the area of built-up land expanded by 40.31% (504.85 km²). Specifically, between 2015 and 2018, built-up land increased by 95.85 km², while, from 2018 to 2023, the growth was significantly larger at 409.00 km², highlighting the widespread conversion of cropland into built-up land. From 2015 to 2023, the spatial distribution of LER in the study area exhibited a pattern of high-risk peripheries (central mountainous areas) and low-risk central regions (coastal areas). Compared to 2023, projections for 2033 under different scenarios indicate a decline in cropland (by approximately 17.8–19.45%) and grassland (by approximately 24.06–24.22%), alongside an increase in forestland (by approximately 4.5–5.35%) and built-up land (by approximately 23.5–41.35%). Under all three projected scenarios, high-risk areas expand notably, accounting for 4.52% (NDS), 3.33% (ECS), and 5.75% (EPS) of the total area. The LER maintenance area (65.25%) accounts for the largest proportion, primarily distributed in coastal economic development areas and urban–rural transition areas. In contrast, the LER mitigation area (7.57%) has the smallest proportion. Among the driving factors, the GDP (q = 0.1245) and year-end resident population (q = 0.123) were identified as the dominant factors regarding the spatial differentiation of LER. Furthermore, the interaction between economic factors and energy consumption further amplifies LER. This study proposes a policy-driven dynamic risk assessment framework, providing decision-making support and scientific guidance for LER management in tropical islands and the optimization of regional land spatial planning. Full article