Land Use Change Dynamics Research Articles

Spatiotemporal dynamics of land use and land cover change around Volcanoes National Park and their implications for biodiversity conservation

ABSTRACT This study comprehensively analyses spatiotemporal land use/land cover (LULC) dynamics within a 10-km buffer zone surrounding Volcanoes National Park (VNP), Rwanda, from 2000 to 2019, integrating biophysical and socio-economic drivers. It aims to quantify LULC change extent, rate, and type around VNP and inside the park; identify socio-economic, demographic, and policy drivers of LULC change; and evaluate the impact of LULC changes on VNP’s biodiversity via habitat fragmentation, connectivity, and species diversity. Employing remote sensing, spatial modelling, and field data, we reveal profound transformations within the park’s periphery. Forests and woodlots have significantly declined, replaced by agriculture, grasslands, and built-up areas, particularly in the 5.1–10 km belt (92.29% forest loss). While reforestation efforts exist, they are outpaced by deforestation, creating a stark deforestation-to-reforestation ratio of 12:1 in the 5.1 10 km belt and 6:1 in the 0–5 km belt. This alarming trend threatens VNP’s biodiversity as resource dependent communities continue to extract firewood, construction materials, and beanpoles from the park. To mitigate these impacts, we propose integrated strategies encompassing strengthened law enforcement, sustainable land management practices, community-based conservation initiatives, and alternative livelihood development.

Assessing forest fragmentation due to land use changes from 1992 to 2023: A spatio-temporal analysis using remote sensing data

The increasing pressures of urban development and agricultural expansion have significant implications for land use and land cover (LULC) dynamics, particularly in ecologically sensitive regions like the Murree and Kotli Sattian tehsils of the Rawalpindi district in Pakistan. This study's primary objective is to assess spatial variations within each LULC category over three decades (1992–2023) using cross-tabulation in ArcGIS to identify changes in LULC and investigates into forest fragmentation analysis using the Landscape Fragmentation Tool (LFTv2.0) to classify forest into several classes such as patch, edge, perforated, small core, medium core, and large core. Utilizing remote sensing data from Landsat 5 and Landsat 9 satellites, the research focuses on the temporal dynamics in various land classes including Coniferous Forest (CF), Evergreen Forest (EF), Arable Land (AR), Buildup Area (BU), Barren Land (BA), Water (WA), and Grassland (GL). The Support Vector Machine (SVM) classifier and ArcGIS software were employed for image processing and classification, ensuring accuracy in categorizing different land types. Our results indicate a notable reduction in forested areas, with Coniferous Forest (CF) decreasing from 363.9 km2, constituting 45.0 % of the area in 1992, to 291.5 km2 (36.0 %) in 2023, representing a total decrease of 72.4 km2. Similarly, Evergreen Forests have also seen a significant reduction, from 177.9 km2 (22.0 %) in 1992 to 99.8 km2 (12.3 %) in 2023, a decrease of 78.1 km2. The study investigates into forest fragmentation analysis using the Landscape Fragmentation Tool (LFTv2.0), revealing an increase in fragmentation and a decrease in large core forests from 20.3 % of the total area in 1992 to 7.2 % in 2023. Additionally, the patch forest area increased from 2.4 % in 1992 to 5.9 % in 2023, indicating significant fragmentation. Transition matrices and a Sankey diagram illustrate the transitions between different LULC classes, providing a comprehensive view of the dynamics of land-use changes and their implications for ecosystem services. These findings highlight the critical need for robust conservation strategies and effective land management practices. The study contributes to the understanding of LULC dynamics and forest fragmentation in the Himalayan region of Pakistan, offering insights essential for future land management and policymaking in the face of rapid environmental changes.

Study on the Dynamic Change of Land Use in Megacities and Its Impact on Ecosystem Services and Modeling Prediction

Under the background of rapid urbanization, strengthening the research on the response and dynamic mechanism of ecosystem services to land use is conducive to the optimization of land space and ecological restoration and governance in megacities. Using Hefei City as a case study, we examined specific ecosystem services and analyzed how water yield, habitat quality, carbon storage, and soil conservation changed over time from 2000 to 2020. We utilized spatial information technthe value of ecosystem services per unit

Urbanization induced changes in land use dynamics and its nexus to ecosystem service values: A spatiotemporal investigation to promote sustainable urban growth

Proper knowledge regarding the spatial dependence of ecosystem service values (ESVs) on the changes in land use dynamics is essential for environmental management as well as sustainable urban development. To investigate this complex association concerning a fast-growing secondary city, this study estimated the integrated land use dynamic degree (ILUDD), uniform annual land use transition intensity (Wtn), and entropy index of land use mix (LUM), and the ESVs for Raiganj urban agglomeration (UA). The overall association between the three indices and the ESVs is explored using the spatial lag and spatial error model. For the local level association, the geographically weighted regression (GWR) is applied. The output showed that changes in ILUDD and LUM indicate over −20 unit and −2 unit changes in the ESVs of built-up with 1 unit increase in ILUDD and LUM, respectively. However, the ILUDD coefficient score concerning vegetation ESV was observed around +25. The Wtn also represented a significant loss of natural vegetation from every administrative unit of Raiganj UA. The relation between urban growth type and landscape patches is analyzed using Getis-Ord-Gi. It is found that the promotion of compact growth can be the best possible solution to preserve the environmental quality in this region.

The Dynamics of Land Use Change in Metropolitan Areas: The Impact of Urbanization and Sustainable Management Strategies

Land use change is a global phenomenon with significant impacts on the environment, society, and economy, especially in metropolitan areas experiencing rapid urbanization. This study aims to analyze the dynamics of land use change, the driving factors, and the resulting ecological and socio-economic impacts. The method used in this research is a literature review with a qualitative approach. Data were collected from various secondary literature sources, including books, journal articles, research reports, and dissertations relevant to the research topic. The findings indicate that urbanization is the primary driver of land use change, leading to the conversion of green spaces such as forests and agricultural land into urban areas. The impacts of these changes include air quality degradation, increased flood risk, soil degradation, and loss of biodiversity. Case studies in cities such as Jakarta, Bangkok, and Manila illustrate how rapid urbanization transforms urban landscapes and creates complex environmental challenges. This research emphasizes the importance of sustainable land management through the application of landscape-based models that integrate spatial and temporal data to predict future land use changes. Evidence-based policy recommendations are provided to support more sustainable and environmentally friendly development. The results of this study are expected to contribute to the development of theory and practice in land use change studies and provide a framework that can be applied in various geographical and socio-economic contexts.

Impacts of land-use change on the habitat suitability and connectivity of giant panda

Land-use changes lead to habitat loss and fragmentation, which poses a further threat to the survival of species. Therefore, it is crucial to analyze how land-use change affects its habitat. 37 counties in Sichuan Province, China, where giant pandas are distributed, were selected as the subjects. Through analyzing land-use change, habitat suitability and connectivity characteristics over the past 20 years, and establishing a correlation between them, the impacts of land-use change on the habitat suitability and connectivity of giant pandas were explained. The results showed that from 2000 to 2020, the different land-use areas in the study area showed a pattern of change with an increase in forest area, built-up area and water area, and a decrease in grassland area and cropland area. There were significant differences in the characteristics of land-use dynamics changes among counties. Changes in land-use dynamics have a significant impact on the habitat suitability and connectivity of giant pandas, which is manifested in the fact that the conversion of forestland to grassland and grassland to cultivated land significantly reduces habitat suitability, while the conversion of grassland to forestland and cultivated to forestland significantly increases the connectivity of giant panda habitats. Changes in the habitat suitability index were significantly and positively correlated with the land-use dynamics index and the land-use degree index. Our findings emphasize the importance of balancing socio-economic development, land-use, and conservation efforts to maintain giant panda habitat. Therefore, the development of rational land-use patterns in future management is key to maximizing the comprehensive social, economic and ecological benefits.

Assessing urban growth through morphological spatial pattern analysis in cloud computing platform

PurposeThis study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).Design/methodology/approachUsing the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.FindingsThe study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.Originality/valueThe novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

The relationship between landscape pattern and plant species diversity in east Dongting lake wetland based on different Eco-environment

Exploring the impact factors associated with biodiversity and the relationship between them has always been a concerned issue in recent years. However, the previous research mostly focus on theoretical layer. Accordingly, the relationship between landscape pattern and biodiversity is to be analyzed in this research. The landscape pattern determines the function and ecological process of the landscape, and affects the species flow, information flow and energy flow in the landscape. Land use patterns has inevitably left an impact on the landscape pattern. Landscape pattern determines the function and ecological process of landscape and thus plays a significant role in biodiversity. East Dongting Lake National Nature Reserve is taken as the research object of the paper, and the remote sensing image data of three different time periods are collected, including 2000, 2010 and 2020. With an interpretation of the vegetation landscape pattern changes inside the protected area to collect and analyze the vegetation coverage. By comparing landscape patterns and the dynamic changes of land use in different periods of time, the correlation between landscape pattern characteristics and regional biodiversity is to be analyzed. Research shows: (1) From 2000 to 2020, the vegetation coverage of East Dongting Lake increased, but the landscape shape, scale, diversity and uniformity index decreased to varying degrees. (2) At the class level of landscape type, the relationship between landscape index and biodiversity is different. A complex relationship between farmland landscape and biodiversity. There is a significant positive correlation between the index of grassland landscape type and the index of regional biodiversity. (3) The correlation analysis results at the landscape level show that the landscape characteristic index is positively correlated with the regional biodiversity index. The grassland landscape in the area is the main habitat of biological species. At the same time, as the main grain producing area, the impact of farmland landscape cannot be ignored. This study has certain theoretical guiding significance for the protection and management of biodiversity in the region in terms of maintaining landscape pattern in particular the grassland landscape area and increasing vegetation coverage in the process of land use.

Predictive simulation of the water-energy-food nexus for the City of Cape Town

The City of Cape Town (CoCT), South Africa faced a critical situation between 2015 and 2018 in which the municipal water supply was almost completely exhausted. This situation, commonly referred to as Day Zero in South Africa emanated from a decline in rainfall, resulting in one of the most severe droughts in history. The crisis was also aggravated by rapid population growth and urbanization. CoCT was on the verge of becoming the first city in the past decade to experience a complete cessation of water supply for urban and agricultural purposes. In addition to the effects of low rainfall and population surge, urban energy consumption and increased food demand impacted directly the available water resources. To evaluate the interlinkages between water utilization, water production, energy supply and demand, and food production and demand, this study employed a system dynamics modeling (SDM) approach. The model was developed as a stock and flow diagram utilizing Stella Architect and encompassed five interconnected nodes: water, energy, food, land, and population. The findings revealed that by the end of the 20-year modeling period, the volume of accessible and stored water in all the major dams will be approximately 459 million cubic meters, with residential use accounting for about 85 % of urban water use and agriculture accounting for approximately30.37 % of total water demand. The model illustrates the impacts of precipitation rate, runoff, and evaporation on variables such as land-use change and population dynamics. It is anticipated that the outcomes of this study will serve as valuable inputs for decision-making processes, not only within the CoCT as it aims to mitigate or prevent the recurrence of Day Zero, but also for other cities facing similar challenges.

Learning spectral-indices-fused deep models for time-series land use and land cover mapping in cloud-prone areas: The case of Pearl River Delta

Mapping of highly dynamic changes in land use and land cover (LULC) can be hindered by various cloudy conditions with optical satellite images. These conditions result in discontinuities in high-temporal-density LULC mapping. In this paper, we developed an integrated time series mapping method to enhance the LULC mapping accuracy and frequency in cloud-prone areas by incorporating spectral-indices-fused deep models and time series reconstruction techniques. The proposed method first reconstructed cloud-contaminated pixels through time series filtering, during which the cloud masks initialized by a deep model were refined and updated during the reconstruction process. Then, the reconstructed time series images were fed into a spectral-indices-fused deep model trained on samples collected worldwide for classification. Finally, post-classification processing, including spatio-temporal majority filtering and time series refinement considering land–water interactions, was conducted to enhance the LULC mapping accuracy and consistency. We applied the proposed method to the cloud- and rain-prone Pearl River Delta (i.e., Guangdong–Hong Kong–Macao Greater Bay Area, GBA) and used time series Sentinel-2 images as the experimental data. The proposed method enabled seamless LULC mapping at a temporal frequency of 2–5 days, and the production of 10 m resolution annual LULC products in the GBA. The assessment yielded a mean overall accuracy of 87.01% for annual mapping in the four consecutive years of 2019–2022 and outperformed existing mainstream LULC products, including ESA WorldCover (83.98%), Esri Land Cover (85.26%), and Google Dynamic World (85.06%). Our assessment also reveals significant variations in LULC mapping accuracies with different cloud masks, thus underscoring their critical role in time series LULC mapping. The proposed method has the potential to generate seamless and near real-time maps for other regions in the world by using deep models trained on datasets collected globally. This method can provide high-quality LULC data sets at different time intervals for various land and water dynamics in cloud- and rain-prone regions. Notwithstanding the difficulties of obtaining high-quality LULC maps in cloud-prone areas, this paper provides a novel approach for the mapping of LULC dynamics and the provision of reliable annual LULC products.

Dispossessed lands and land-use change in the Colombian armed conflict: Exploring a link through a regional case study

Land dispossession in the Colombian armed conflict is a critical form of victimization and a trigger of territorial configurations that shape the rurality of the country. The consequences of the illegal appropriation of land by means of usurpation or forced displacement result in a humanitarian drama and various socio-spatial and socio-economic transformations. This research analyzes the intricate dynamics of land use and cover changes in four municipalities within the Cesar department and its relationship with instances of land abandonment and dispossession over a 29-year period (1991–2020). Landsat satellite image time series of TM, ETM+ and OLI data were used to determine land use and land cover (LULC). The classification process was carried out using the Random Forest model. The dynamics of land dispossession and forced abandonment were identified by analyzing 195 land restitution court rulings. Geo-referenced properties were subsequently overlaid on the created LULC maps. As a result, a pattern indicating a direct relationship between both variables was found. Consequently, the phenomenon of land dispossession in the context of this internal armed conflict has contributed to the transition from the traditional agrarian model to the agro-industrial one.

Assessing the efficiency of bird habitat conservation strategies in farmland ecosystems

Land use changes negatively impact agroecosystems, where the loss of wildlife habitats is increasingly threatening global biodiversity. Ecological conservation strategies that seek to reduce habitat destruction are important and strongly rely on understanding the spatial and temporal dynamics of land use change. In recent years, an expert-based approach using the Analytic Network Process (ANP) has been applied commonly to wildlife habitat assessment, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-s) model is a well-known simulation tool used to predict land use dynamics. Although their effectiveness has been proven widely, existing studies have yet to integrate the two approaches into ecological modeling for conserving bird habitats under the influence of land use changes. Thus, there is a notable research gap regarding the potential synergies of the ANP and CLUE-s models to evaluate the spatial nonstationarity between bird habitats and land use patterns. In this study, we integrated use of the ANP to identify suitable habitats for birds on farmland with the CLUE-s model to predict future changes in habitat suitability by 2035. Our study aims to evaluate the efficiency of various conservation strategies for bird habitat in farmland ecosystems within the Zhuoshui River basin in Taiwan. We formulated conservation strategies to protect areas of farmland based on their relative suitability as bird habitats. The research findings reveal a significant reduction of farmland habitats coinciding with expanding built-up areas and forests, while designating farmland areas for conservation purposes effectively ensures the maintenance of bird habitats amidst these transformations. Conserving highly suitable farmland habitats (those whose suitability values ranked at or above the 75th percentile) presents the most effective strategy to mitigate the impacts of land use change on bird habitats. Under this strategy, changes in farmland habitats lead to a notable decrease of 16.4 % in low and very low suitability, whereas farmland habitats with moderate and high suitability significantly expand by 879.8 % and 225.9 %, respectively. Farmland habitats characterized by high suitability are concentrated in the western region of the Zhuoshui River basin, accounting for 2289 hectares. These findings underscore the magnitude of habitat loss resulting from land use changes outside conserved areas. Our research emphasizes the importance of implementing conservation strategies for bird habitats, providing policymakers with a framework to manage farmland ecosystems effectively.

Assessing the Spatiotemporal Variations in the Hydrological Response of the Qin River Basin in Loess Plateau, China

In recent decades, the hydrological processes on the Loess Plateau have undergone significant changes due to the combined effects of climate change and human activities. This study investigates the Qin River basin, the core area of the Loess Plateau. Between 1971 and 2000, the hydrometeorology of the flood season in the Qin basin on the Loess Plateau in China changed abruptly in 1982 and 1992. This study uses distributed hydrologic modeling and statistical analysis to distinguish the spatial and temporal impacts of climate change and human activities. The fastest dynamic changes in land use occurred in grassland and construction land, accounting for 0.36% and −0.1%, respectively, from 1982 to 1991. From 1992 to 2000, it was 0.29% and 0.3%, respectively. The increase in basin area where the Normalized Difference Vegetation Index increased was 95%. However, except for significant changes in runoff from 1981 to 1992, there were no significant changes in precipitation, runoff, and temperature during other flood seasons. During the two studied variation periods, from 1982 to 1991 and from 1992 to 2000, the contribution rate of climate change to flood season runoff (CClimate) decreased from 83.26% to 74.47%, while the contribution rate of human activity disturbance to flood season runoff (Chuman) increased from 16.74% to 25.53%. In terms of spatial distribution, from 1982 to 1991, areas with a Chuman > 50% were primarily concentrated in the upper reaches of the basin, while from 1992–2000, these areas shifted to the lower reaches. This study offers valuable insights for water resource planning and soil conservation measures in the Loess Plateau and similar arid regions worldwide, aiming to ensure water resource safety and sustainability in response to climate change and human interference.

Land-Use Change Dynamics in Areas Subjected to Direct Urbanization Pressure: A Case Study of the City of Olsztyn

Urbanization is one of the most visible symptoms of global changes. This process has been driven by the evolution of life on Earth, and it gradually modifies the structure of land use. Urban development is the most apparent indicator and measure of urbanization. The demand for vacant land and sustainable spatial development plans require new methods that support decision-making in the process of changing land use in suburban areas. The aim of this study was to describe a methodology for identifying and localizing urban development boundaries with the use of fuzzy set theory, to evaluate the degree of urbanization, and to analyze the dynamics of land-use changes in areas subjected to direct urbanization pressure with the use of photogrammetric data for 2005, 2010, 2017, and 2022. A case study was conducted in the Polish city of Olsztyn. The study’s results determined the degree of urbanization of the areas in the [0, 1] range, as well as the dynamics of change in each of the twenty-four adopted forms of land use. The results indicate that the proposed methods are useful for identifying the rate and direction of urbanization, and can be applied to optimize and counterbalance the development of settlements and infrastructure.

Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data.

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r = - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m2. Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events.

The Spatiotemporal Analysis of Land Take Exemplified by Poland

The research was motivated by the growing interest of scientists and practitioners in land consumption. It was assumed that the multifaceted and space–time analysis of the dynamics of land use change reveals agricultural and forest land conversion into artificial areas, and thus highlight the regions of high human pressure. To fulfill the research objective, the proprietary coefficient of admissible (maximal) land take (aLT) was used. This study, based on open, publicly available spatial and statistical data, presents agricultural and forest land losses in four periods (2005, 2010, 2015, 2020) in Polish provinces. The analysis reveals both the value and the trend of land take and indicates Mazowieckie and Małopolska as the provinces of the highest land take pace since 2005. In contrast, provinces such as Zachodnio-Pomorskie and Opolskie, located in the northwest and southwest of Poland, are characterized by small and decreasing losses of agricultural and forest land, prompting them to be classified as lower outliers. The paper concludes, in part, that admissible (maximal) land take (aLT) is a useful tool for monitoring land conversion and planning spatial development of any region in the world.

The Impacts of Land-Use Changes on Ecosystem Service Value in the Yunnan–Kweichow Plateau, China

The Yunnan–Kweichow Plateau serves as a critical ecological security barrier in southwest China. The region has witnessed substantial transformations in land use patterns due to rapid urban expansion, economic development, and population growth. These changes have significantly impacted the structure and services of regional ecosystems. Conducting a quantitative analysis of the influence of land-use changes on ecosystem service value (ESV) proves to be invaluable for guiding regional land planning and environmental conservation efforts. Utilizing land use data, we calculated ESV variations linked to dynamic land-use changes spanning the period from 1980 to 2020. This comprehensive study delved into the spatiotemporal fluctuations and regional disparities in ESV. To enhance the reliability of our evaluation, we applied a regional coefficient to adjust the equivalent factor of ecosystem service value. Over the 40 years, the total ESV exhibited a decrease from USD 122,215.03 million to USD 121,838.82 million. Notably, water supply experienced the most significant decline, while hydrological regulation witnessed the largest increase. The continuous decline in water supply service capacity raises concerns about exacerbating water resource shortages in the region. Spatially, the ESVs in the study region primarily concentrated within the medium-low to medium-high value range. However, except for regions with medium values, the area of other level regions is expanding, and is particularly evident in the increase in low-value regions. The reduction of forestland, grassland, and cultivated land, coupled with the expansion of built-up land, emerged as the primary contributors to the overall ESV decrease. In particular, the negative ecological contribution rate of built-up land reached 37.97%, and the ESV decreased by USD 866.64 million, underscoring that the expansion of water bodies could not compensate for this loss. The study highlights the increasing sensitivity of ESV to land-use changes in the region. As a response, there is a pressing need for managers to reinforce the implementation of ecological engineering and engage in rational planning for production, living, and ecological spaces. This research serves as a crucial reference for establishing an ecological security pattern system and fostering the sustainable development and utilization of land resources in the region.

Exploring the past through lynchet landscapes in the Vosges Mountains and the Lorraine Plateau (France)

AbstractLynchets are ridges formed by erosion and sediment accumulation downstream of agricultural plots and offer valuable insights into past agricultural activity. These microtopographies cover vast areas and serve as indicators of historical changes in land use. As a result, their ubiquity across Europe makes them particularly interesting. In this study, we propose a geoarchaeological approach to analyze six lynchets, four in the Vosges Mountains and two on the Lorraine Plateau (France). The lynchets can be considered soil archives with no stratigraphic organization or chronological sequence from bottom to top, making it difficult to determine the age of the lynchets and identify changes in land use over time. To this end, we propose the analysis of historical and geo‐historical archives combined with the “pedosedimentary” archives of lynchets through charcoal identification and dating combined with near‐infrared spectroscopy to determine the age, vegetation, and past land use changes associated with lynchet landscapes. By combining these multiple data sources, we are better able to show the chronological development of these ancient agricultural systems and uncover valuable information on landscape history. Charcoal dating suggests a higher frequency of fires from the Middle Ages. The dating aligns with the regional dynamics of anthropogenic fires, indicating a potential use of fire for cultural purposes. We also demonstrate the difficulty of extrapolating the dating of a lynchet to the entire lynchet system. Our results highlight the difficulties of interpreting the formation and dating of lynchets and the lynchet system on the sole basis of charcoal analysis. However, we highlight the value of applying pedoanthracology to lynchets to determine the dynamics of land use change in former fields.

Assessment of water-related ecosystem services based on multi-scenario land use changes: focusing on the Poyang Lake Basin of southern China

A scientific understanding of the trends of water-related ecosystem services (WESs) under different scenarios is crucial to improving WESs and maintaining ecological security. However, there is a lack of high-resolution land use simulation and assessment of WESs under the SSP-RCP scenarios, and the impacts of different land-use change (LUC) on WESs are not clear. This study focused on the Poyang Lake Basin (PYLB), utilizing the SSP-RCP scenarios, the PLUS model and the InVEST model to explore the dynamic changes of land use and WESs historically and in the future, and to reveal the impacts of specific LUC on WESs from 2000 to 2020. The results demonstrated that: (1) The forest land increased under both SSP1-2.6 and SSP2-4.5 scenarios but increased first and then decreased under SSP5-8.5 scenarios; Cropland increased significantly under SSP5-8.5 scenarios, and the construction land showed an expansion trend under the three scenarios. (2) From 2000 to 2020, only the water purification capacity decreased, while the rest of the WESs increased. Under the SSP1-2.6 scenario, the overall benefits of the WESs in the PYLB were the highest. (3) Between 2000 and 2020, deforestation in the PYLB brought about the greatest increase in the water yield (+9.06 × 108 m3). The increase in the construction land brought about the most water conservation loss (−18.19 × 108 m3). Additionally, the forest expansion and cropland reduction brought about the largest increase in soil retention (+3.94 × 105 t and +4.79 × 105 t) and enhanced water purification, and the opposite was true for deforestation. The conclusions can provide an important basis for the ecological protection and high-quality development of the PYLB.

Comprehensive Analysis of Land Use and Land Cover Shifts from A Redd Perspective: A Case Study of Banepa Municipality, Nepal

This paper examines the dynamic changes in land use and cover in Banepa Municipality over three decades, from 1991 to 2021, using the remote sensing method within the REDD perspective. It uncovers an 11% surge in built-up areas and a 5% decline in forest cover, with minimal agricultural fluctuations (1%) and a substantial 7% decrease in barren land. Urgent concerns about ecological balance prompt a call for immediate REDD implementation.
 To address these issues, the study advocates for employing monitoring methods, including remote sensing, to evaluate forest and land resources. This data can inform comprehensive studies on the drivers of deforestation and forest degradation, alongside feasibility and sectorial analyses, including cost-benefit assessments for effective land-use planning. The conclusion stresses the imperative need for planned urban development in Banepa to preserve open spaces, forests, and agriculture. This study provides vital insights into the intricate relationship between land-use changes and climate impact, emphasizing the urgency of sustainable development actions.