Land Use Patterns Research Articles

Spatial–Temporal Pattern Analysis and Development Forecasting of Carbon Stock Based on Land Use Change Simulation: A Case Study of the Xiamen–Zhangzhou–Quanzhou Urban Agglomeration, China

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence of land use changes are crucial to the scientific management of environmental resources and the optimization of land spatial layout. Taking the Xiamen–Zhangzhou–Quanzhou urban agglomeration in the southeastern coastal region of China as an example, based on seven land use types from 1990 to 2020, including cultivated land, woodland, and construction land, we quantitatively investigate the spatial–temporal patterns of carbon stock development and the spatial correlation of carbon stock distribution. Additionally, two scenarios for the development of urban and ecological priorities in 2060 are established to investigate the effects of land use changes on carbon stock. The results indicate that (1) the research area has formed a land use spatial pattern centered around urban construction in the eastern bay area, with the western forest area and coastal forest belt serving as ecological barriers. Carbon stock is influenced by land use type, and the distribution of total carbon stock exhibits a spatial aggregation phenomenon characterized by “low in the southeast, high in the north, and medium in the center”. (2) Distance of trunk and secondary roads, elevation, slope, watershed borders, population size, and gross domestic product (GDP) factors are the main drivers of the growth of land use types. The primary causes of the reduction in carbon stock are the widespread conversion of cultivated land, woodland, and grassland into construction land, as well as water and unused land. (3) In 2060, there will be a decrease of 41,712,443.35 Mg in the urban priority development scenario compared to 2020, and a decrease of 29,577,580.48 Mg in the ecological priority development scenario. The estimated carbon stock under the two scenarios varies by 12,134,862.88 Mg. The average carbon storage of Zhangpu County, Quangang County, and Jimei County is expected to rise by one level under the ecological protection scenario, indicating that the vast forest area can become a potential area to maintain carbon stock. It is crucial to encourage the coordinated development of peri-urban agroforestry and ecological barriers, as well as to establish a harmonious spatial pattern of land use and carbon stock at the scale of urban agglomerations.

Spatial and Temporal Distribution of the Ecosystem Provisioning Service and Its Correlation with Food Production in the Songhua River Basin, Northeastern China

Provisioning services are essential components of ecosystem services. Food production is usually a driver of land use change, which has the effect on altering the provisioning services of ecosystems. As one of the main areas of food production in China, the provisioning services of the Songhua River Basin (SHRB) should be taken seriously. In view of this, it is urgent to carry out a study on the assessment of provisioning services in the SHRB to provide data support and scientific reference for the optimization of the spatial pattern of land use in the basin, the sustainable development of agriculture, and the formulation of differentiated protection policies. In this study, based on the equivalent factor method for the unit area value and spatial autocorrelation with the Moran’s I, we assessed the provisioning services values (PSV) of the SHRB every ten years during the period of 2000–2020 under different land use types and analyzed the relationships between different PSV and the production of four different food types, including rice, wheat, corn, and soja. The main conclusions are as follows: (1) From 2000 to 2020, the area of paddy fields in the SHRB increased and then decreased, while the area of dry lands continued to increase. The land use transfer matrix showed a significant expansion of paddy fields (+0.55 × 104 km2), shrinkage of grassland (−0.72 × 104 km2), and loss of water body (−0.43 × 104 km2) in the SHRB from 2000 to 2020; (2) The PSV in the SHRB showed an increasing trend from 2000 to 2020, growing by 16.73 × 1010 RMB, with the growth in 2010–2020 being greater than in 2000–2010. The order of increase in each type of PSV was: water supply > food supply > raw material supply; (3) Spatially, the increase in PSV per unit and total PSV in the SHRB was lesser in the center and greater in the east and west. Meanwhile, the spatial distribution of various PSV showed that the value of unit area food supply was higher in the central and eastern plains, while the raw material supply and water supply were higher in the western and eastern hilly areas. (4) In terms of spatial correlation, the distribution of soja production with the total PSV, food supply, raw materials supply, and water supply services values were positively spatially correlated. However, the production of rice, wheat, and corn with the total PSV, food supply, and raw materials supply services values were negatively spatially correlated. Cluster analysis revealed that changing the crop cultivation structure could protect the ecosystem and increase the value of ecosystem services.

National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data.

As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe's observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. The research findings also revealed new critical information about the spatiotemporal fire patterns in various terrestrial ecoregions, land cover, land use, precipitation and topography and highlighted potential areas for effective fire management strategies.

Spatial and Temporal Changes in Ecological Resilience in the Shanxi–Shaanxi–Inner Mongolia Energy Zone with Multi-Scenario Simulation

The energy-driven expansion of artificial surfaces has resulted in severe ecological problems. Scientific evaluation of regional ecological resilience under different scenarios is crucial for promoting ecological restoration. This study chose the Shanxi–Shaanxi–Inner Mongolia Energy Zone (SEZ) and modeled an ecological resilience evaluation based on resistance, adaptability, and recovery. Land-use change and ecological resilience from 1980 to 2020 were then analyzed. Moreover, the SEZ land-use patterns and ecological resilience in 2030 were simulated under business as usual (BAU), energy and mineral development (EMD), and ecological conservation and restoration (ECR) scenarios. The results showed that (1) the SEZ was dominated by cultivated land, grassland, and unused land. (2) Ecological resilience showed a changing trend of decreasing and then increasing, with high ecological resilience areas mainly located in the Yellow River Basin, whereas low ecological resilience areas spread outward from the central urban areas. (3) The ecological resilience level was the lowest under the EMD scenario and the highest under the ECR scenario. This study not only expands the analysis framework of ecological resilience research but also provides scientific support for ecological conservation in ecologically fragile areas with intensive human activity worldwide.

Land-use simulation for synergistic pollution and carbon reduction: Scenario analysis and policy implications

Simulations of sustainable land use and management are required to achieve targets to reduce pollution and carbon emissions. Limited research has been conducted on synergistic pollution and carbon reduction (SPCR) in land-use simulations. This study proposed a framework for land-use simulation focused on SPCR. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) and the entropy weight-based technique for order of preference by similarity to an ideal solution (TOPSIS) were used to optimize the land-use structure according to minimum net carbon, nitrogen, and phosphorus emissions. The cellular automata (CA) Markov model was then utilized to simulate the land-use spatial pattern according to the optimal conditions. The proposed framework was applied to the Dongjiang River Basin, South China, and three other scenarios (natural development (ND), carbon minimization (CM), and pollution minimization (PM)) were designed to validate the effectiveness of pollution and carbon emissions reduction under the SPCR scenario. The land-use structure and the pollution and carbon emissions in the scenarios were compared. The results showed the following. (1) The proportions of cultivated land, woodland, grassland, water, and construction land In the SPCR scenario accounted for 14%, 72%, 4%, 3%, and 7% of the total area, respectively. The carbon, nitrogen, and phosphorus emissions were 42.4%, 6.6%, and 7.8% lower, respectively, in the SPCR scenario than in the ND scenario, demonstrating the advantages of simultaneous pollution and carbon reduction. (2) The kappa coefficient of the CA-Markov model was 0.8729, indicating high simulation accuracy. (3) The simulated land-use spatial patterns exhibited low spatial heterogeneity under the CM, PM, and SPCR scenarios. However, there were significant disparities between the ND and SPCR scenarios. The cultivated and construction land areas were significantly smaller in the SPCR scenario than in the ND scenario. In contrast, the woodland and grassland areas were larger, with most differences in the central and southwestern regions of the Dongjiang River Basin. The results of the current study can be used to formulate effective land use policies and strategies in the Dongjiang Basin and similar areas to achieve the Coupling coordination between pollution reduction and carbon reduction. Policy recommendations include increasing the proportion of woodland and grassland, implementing reasonable constraints on expanding cultivated and construction lands, and establishing farmland red lines to promote synergistic pollution and carbon reduction.

Characteristics Analysis and Prediction of Land Use Evolution in the Source Region of the Yangtze River and Yellow River Based on Improved FLUS Model

Climate change profoundly alters land use in alpine regions, and delving into the evolutionary characteristics of these changes is crucial for the sustainable development of regional land resources and the gradual enhancement of the ecological environment. Taking the source region of the Yangtze and Yellow River (SRYAYE) as a case study, we integrate permafrost and snowfall data into the Future Land Use Simulation model (FLUS). Analyzing historical land use, we predict and simulate the land use scenarios for 2030, 2035, and 2060 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climates, and conduct a detailed analysis of the scale, composition, and pattern of land use in this area. Scale. The results showed that ① the Kappa coefficient of the improved FLUS model was higher than 0.927, and that the overall accuracy of the simulation was increased by 2.64%; ② the area of forest land and the high-coverage grassland will increase in the future and the center of gravity will migrate to the west, and that the area of moderate and low-coverage grassland will slightly decrease but tend to become green to the west; and ③ the fragmentation degree of the SRYAYE is decreasing, and the influence of human activities on the landscape pattern is weaker than in the past.

Shopping trips and deliveries then and now: How the behavioral shift differs by income level and urban size

Online shopping has significantly increased for the past decade. As e-commerce grows and evolves since its first appearance, consumers’ shopping behaviors also change, leading to the co-evolution of people’s shopping trips and urban freight deliveries. This co-evolution has important impacts on traffic, vehicle-miles-traveled (VMT) and parking demand in the short term, and is expected to influence residential choice and land-use patterns in the long term. However, the existing studies have not examined how the relationship among shopping channels changed over time. To address this knowledge gap, this research investigated how the complex relationship between delivery and in-store shopping trips changed from when e-commerce was relatively small to a stabilized stage, i.e., from 2009 to 2017, using the National Household Travel Survey (NHTS) data. The results from path analyses showed that the relationships among delivery, non-motorized shopping trip, and motorized shopping trip significantly shifted during an eight-year period. Not only the relationship among shopping channels but also the impacts of socio-demographic factors on shopping had changed over time. Furthermore, the behavioral shift varied by income level and urban size. This research is the first attempt investigating a heterogeneous historical trend from the transportation perspective. An understanding of how the relationship has been shifted and affected by income and urban environments will provide valuable insights into proactively planning and establishing freight demand management as well as addressing the inequality issue. The lessons learned will also be of assistance to better understand how consumers will respond to the emerging freight delivery service forms (e.g., prepared meals and grocery delivery) and their impacts on both passenger and freight transportation systems.

Evaluating water‐quality trends in agricultural watersheds prioritized for management‐practice implementation

AbstractMany agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water‐quality effects of MPs are uncertain. We interpreted water‐quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek (Virginia), Upper Chester River (Maryland), and Conewago Creek (Pennsylvania) watersheds. We synthesized patterns in MPs, climate, land use, and nutrient inputs to better understand factors affecting nutrient and sediment loads. Relations between MPs and expected water‐quality improvements were not consistently identifiable. The number of MPs increased in all watersheds since the early 2010s, but most monitored nutrient and sediment loads did not decrease. Nutrient and sediment loads increased or remained stable in Smith Creek and the Upper Chester River. Sediment loads and some nutrient loads decreased in Conewago Creek. In Smith Creek, a 36‐year time‐series model suggests that changes in manure affected flow‐normalized total nitrogen loads. We hypothesize that increases in nutrient applications may overshadow some expected MP effects. MPs might have stemmed further water‐quality degradation, but improvements in nutrient loads may rely on reducing manure and fertilizer applications. Our results highlight the importance of assessing MP performance with long‐term monitoring‐based studies.

Spatial Planning Policy Analysis and Participation Support Society Towards Environmental Sustainability

The research is purpose to find out implementation spatial planning policies on Bekasi city for stainable environmental management? Analytical methods used are: 1) Geo-physics analysis of land suitability analysis, 2) physical analysis; 3) Analysis of environmental management, 4) Analysis of socio-economic conditions, and 5) Analysis of Geographic Information System (GIS). The results obtained that spatial planning and environmental carrying capacity can be concluded that to meet the needs of diverse development needs to develop a spatial pattern of land use, coordinate, procedures for water and other resources in a unified a dynamic environment. To meet the needs of diverse development needs to develop a spatial pattern coordinate system guana land, procedures for water and other resources in a unified order dynamic environment. For that layout needs to be managed by an integrated pattern through a regional approach with respect to site natural environment, socio-cultural environment, and the artificial environment in accordance with its development. Good city spatial structure with more increased public participation in city layout is expected to be better. The parties involved in these activities the city department of administration, the whole society. There is a direct influence on the city hall community participation in maintaining a healthy environment, so if you want to increase public participation in maintaining a healthy environment can be done by increasing the city spatial planning. Knowledge to community environmental management in maintaining a healthy environment, can be done by improving environmental management Knowledge community.

Land-use patterns and fungal bioaerosols in the Brazilian Atlantic Forest biome

Whilst the importance of fungal primary biological aerosol particles (PBAPs) has been recognised, few studies have empirically assessed how land-use patterns influence them. Here, we show the impacts of different land-use patterns on fungal PBAPs within the Brazilian Atlantic Forest biodiversity hotspot. Spanning a distance of ca. 600 km within this biome, we collected fungal bioaerosols in the following land-use patterns: a 25-year-old coffee plantation, a 2.5-year-old Eucalyptus plantation, a 3-months-old maize crop, a 2-year-old and another 7-year-old native forest reforestation area, and a native forest fragment. Using the portable Burkard air sampler, a total of 14 morphotype-species were found. Cladosporium sp. comprised as much as about 95% of all fungal spores collected, being present in all samples (frequency of 100%). Forest systems had as much as 5-to-19-fold more fungal spores in the air than maize crops. Sampling height and time (morning vs. afternoon) did not influence fungal concentration and number of species. In addition, using data derived from an eddy covariance tower in the Eucalyptus site, we estimated the emission rate to be 6649 spores m−2 s−1. Our study confirms that land-use patterns affect fungal PBAPs, and that replacing large areas of native Atlantic Forest by monospecific stands, a homogenisation of airborne fungi is occurring, with unknown consequences for climate regulation.

Effects of land use patterns on soil properties and nitrous oxide flux on a semi-arid environmental conditions of Loess Plateau China

Ecosystems and agroecosystems strongly influences the global warming by nitrogen oxide (N2O) emission. In a recent climate change scenario, nitrogen and carbon sequestration is obligatory under different land-use patterns. However, soil nitrogen elements and carbon content in the recover process of degraded environmental conditions on the Dingxi Loess Plateau has not been clearly understood. Thus, in this current study, we selected four representative land use patterns, including picea asperata (PA), which is based on forest land; Medicago sativa (MS), which is based on grassland; abandoned bare land (AL), which is based on abandoned land; and wheat field (WF), which is based on farmland, to study soil quality indicators and N2O greenhouse gas and relationships amongst environmental factors and N2O flux. Our results depicted that PA and MS significantly increased organic carbon (SOC), total phosphorous (TP), gravimetric water content (SWC), soil bulk density (BD), total nitrogen (TN), ammonium nitrogen (NH4+-N), and microbial biomass nitrogen (MBN) whist decreased soil nitrate nitrogen (NO3--N) content and soil pH value over AL land-use pattern. However, WF land-use pattern showed reduced trend of above mention studied parameters than AL. Additionally, compared to AL, PA and MS significantly reduced the total soil N2O emissions, with reductions of 24.91% and 14.77% in 2021 and 29.08% and 17.53% in 2022, respectively. The WF significantly increased the total N2O emissions, increasing by 53.18% and 40.37% in 2021 and 2022, respectively. Moreover, environmental variables for instance aerial temperature, precipitation had significant correlation with soil N2O based on linear regression analysis, soil NO3--N and soil temperature had significant positive correlation with soil N2O flux while NH4+-N, BD, and SWC were negatively correlated with N2O flux. The Partial Least Squares Path Model (PLS-PM) indicates that soil temperature and soil moisture was the dominant factor for controlling soil N2O emissions followed by soil nutrients and land use patterns. Accordingly, in the context of vegetation restoration process of the study area, the proportion of forest land and grassland should be increase to cope with future climate change scenario. This research result can provide theoretical basis and technical support for scientific understanding and evaluation of soil N2O emission mechanisms and nitrogen sink functions under different land-use patterns in semi-arid region of China.

Analysis and Simulation of Land Use Changes and Their Impact on Carbon Stocks in the Haihe River Basin by Combining LSTM with the InVEST Model

The quantitative analysis and prediction of spatiotemporal patterns of land use in Haihe River Basin are of great significance for land use and ecological planning management. To reveal the changes in land use and carbon stock, the spatial–temporal pattern of land use data in the Haihe River Basin from 2000 to 2020 was studied via Mann–Kendall (MK) trend analysis, the transfer matrix, and land use dynamic attitude. Through integrating the models of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and the Long Short-Term Memory (LSTM), the results of the spatial distribution of land use and carbon stock were obtained and compared with Cellular Automation (CA-Markov), and then applied to predict the spatial distribution in 2025. The results show the following: (1) The land use and land cover (LULC) changes in the Haihe River Basin primarily involve an exchange between cultivated land, forest, and grassland, as well as the conversion of cultivated land to built-up land. This transformation contributes to the overall decrease in carbon storage in the basin, which declined by approximately 1.20% from 2000 to 2020. (2) The LULC prediction accuracy of LSTM is nearly 2.00% higher than that of CA-Markov, reaching 95.01%. (3) In 2025, the area of grassland in Haihe River Basin will increase the most, while the area of cultivated land will decrease the most. The spatial distribution of carbon stocks is higher in the northwest and lower in the southeast, and the changing areas are scattered throughout the study area. However, due to the substantial growth of grassland and forest, the carbon stocks in the Haihe River Basin in 2025 will increase by about 10 times compared with 2020. The research results can provide a theoretical basis and reference for watershed land use planning, ecological restoration, and management.

Assessing the scale effect of urban vertical patterns on urban waterlogging: An empirical study in Shenzhen

Waterlogging disasters seriously affect residents' lives. Investigating the factors affecting waterlogging is crucial for mitigating waterlogging. Although waterlogging is closely related to land-use patterns, most of the previous studies have analyzed only the impact of urban horizontal patterns on waterlogging at a single scale. Few studies have focused on the role of urban vertical patterns from a multiscale perspective. Therefore, this study investigated the influence of various factors on the density of waterlogging points at grid scales of 1–5 km using Pearson correlation analysis and the random forest model. We conducted a case study for Shenzhen City, and the results show that the building coverage ratio, building crowding degree, building density, proportion of impervious surfaces, proportion of green space, and population density are the most important factors. Moreover, the urban horizontal and vertical patterns have significant scale effects on waterlogging. The influence of horizontal patterns on waterlogging is maximum at a scale of 3 km, while the influence and dominance of the vertical patterns increase with scale. Therefore, controlling building congestion is necessary for alleviating waterlogging, and the rational planning of urban horizontal and vertical patterns is important for the construction of sponge cities. Our results provide decision support for urban land-use optimization and waterlogging mitigation, thereby facilitating sustainable environmental management.

Anthropogenic impacts and quantitative sources of nitrate in a rural-urban canal using a combined PMF, δ15N/δ18O–NO3-, and MixSIAR approach

Nitrate (NO3−) pollution in irrigation canals is of great concern because it threatens canal water use; however, little is known about it at present. Herein, a combination of positive matrix factorization (PMF), isotope tracers, and Mixing Stable Isotope Analysis in R (MixSIAR) was developed to identify anthropogenic impacts and quantitative sources of NO3− in a rural-urban canal in China. The NO3− concentration (0.99–1.93 mg/L) of canal water increased along the flow direction and was higher than the internationally recognized eutrophication risk value in autumn and spring. The inputs of the Fuhe River, NH4+ fertilizer, soil nitrogen, manure & sewage, and rainfall were the main driving factors of canal water NO3− based on principal component analysis and PMF, which was supported by evidence from δ15N/δ18O–NO3-. According to the chemical and isotopic analyses, nitrogen transformation was weak, highlighting the potential of δ15N/δ18O–NO3- to trace NO3− sources in canal water. The MixSIAR and PMF results with a <15% divergence emphasized the predominance of the Fuhe River (contributing >50%) and anthropogenic impacts (NH4+ fertilizer plus manure & sewage, >37%) on NO3− in the entire canal, reflecting the effectiveness of the model analysis. According to the MixSIAR model, (1) higher NO3− concentration in canal water was caused by the general enhancement of human activities in spring and (2) NO3− source contributions were associated with land-use patterns. The high contributions of NH4+ fertilizer and manure & sewage showed inverse spatial variations, suggesting the necessity of reducing excessive fertilizer use in the agricultural area and controlling blind wastewater release in the urban area. These findings provide valuable insights into NO3− dynamics and fate for sustainable management of canal water resources. Nevertheless, long-term chemical and isotopic monitoring with alternative modeling should be strengthened for the accurate evaluation of canal NO3− pollution in future studies.

Mapping and Monitoring of Land Use/Land Cover Transformation Using Geospatial Techniques in Varanasi City Development Region, India

Assessing the dynamics and patterns of Land Use and Land Cover (LULC) and its transformation is an important practice of urban planners and environmentalists for a variety of applications, including land management, urban climate modeling, and sustainability of any urban region. Monitoring changes in LULC using geospatial techniques can help to identify areas at risk for indefensible land use, low-grade environment, and especially for sustainable urban planning. This study aims to analyze the changing pattern, dynamics, and alteration of LULC using Google Earth Engine (GEE) and Machine Learning Applications for the years 1991, 2001, 2011, and 2022 in the Varanasi City Development Region (VCDR). The LULC classification was divided into seven classes using random forest classification, and Landsat-5(TM) and 9(OLI-2) satellite data were used. Saga GIS has been utilized for the detection of LULC change during the 1991-2022 period. For validation of classification results, accuracy assessment was estimated using error matrices and through user, producer, and overall accuracy estimation. The Kappa statistics were applied for the reliability of the accuracy assessment result. As a result, the built-up area increased by 507.8 percent, and other classes like agricultural, barren, fallow land, and vegetation cover rapidly declined and altered into concrete areas over the period. Water bodies and river sand classes have been slightly converted into different classes. The finding explains that 114.8 km2 of fertile agricultural land, 14.81 km2 barren land, and 12.93 km2 of vegetation cover transformed into impervious surface, which is unsustainable and causes various problems like food scarcity, environmental degradation, and low quality of urban life. This study can be a useful guide for urban planners, academicians, and policymakers by providing a scientific background for sustainable urban planning and management of VCDR and other cities as well.

Effects of land-use patterns on soil microbial diversity and composition in the Loess Plateau, China

Effects of land-use patterns on soil microbial diversity and composition in the Loess Plateau, China

Spatio-Temporal Patterns of Land Use and Cover Change in the Lancang–Mekong River Basin during 2000–2020

Exploring the mechanisms that drive land use and cover change (LUCC) is essential for informing the formulation and implementation of effective policies aimed at optimizing land use patterns. In this study, we examined the spatial and temporal patterns of LUCC within the Lancang–Mekong River Basin (LMRB) using Globeland30 data for the years 2000, 2010, and 2020. Firstly, we analyzed the quantitative characteristics of LUCC within the LMRB in terms of the value of change and rate of change. Additionally, we investigated the converting characteristics of LUCC within the LMRB by employing land use transition matrices and land use transition probability matrices. Furthermore, we depicted the spatial distribution of LUCC within the LMRB through land use mapping and statistical analysis. The results indicate a substantial decline in forests, coupled with a notable expansion in cultivated land. Given the vital role of forests as carbon sinks, reforestation can enhance ecological services and address challenges related to climate change. Converting cultivated land to forests is an effective human intervention promoting forest transition. This study applies binary logistic models to explore the mechanisms that influence the conversion from cultivated land to forests. The results reveal that slopes ranging from 5° to 15° have the lowest probability of conversion, whereas distances between the cultivated land and the nearest tourist attraction ranging from 9 km to 18 km have the highest probability. Moreover, the conversion process is positively associated with traffic conditions and significantly influenced by human interventions. Within the study area, China, Laos, and Myanmar show a tendency to convert cultivated land into natural LULC types, while Cambodia, Thailand, and Vietnam tend to encroach on cultivated land and expand artificial surfaces. Promoting ecological restoration in the LMRB requires cooperation among these countries.

Participatory and Spatially Explicit Assessment to Envision the Future of Land-Use/Land-Cover Change Scenarios on Selected Ecosystem Services in Southwestern Ghana

Settlement expansion and commercial agriculture affect landscape sustainability and ecosystem service provision. Integrated landscape approaches are promoted to negotiate trade-offs between competing land uses and their reconciliation. Incorporating local perceptions of landscape dynamics as basis for such negotiations is particularly relevant for sub-Saharan Africa, where most people depend on natural ecosystems for livelihoods and well-being. This study applied participatory scenario building and spatially explicit simulation to unravel perceptions of the potential impact of rubber and settlement expansion on the provision of selected ecosystem services in southwestern Ghana under a business-as-usual scenario. We collected data in workshops and expert surveys on locally relevant ecosystem services, their indicator values, and the probable land-use transitions. The data was translated into an assessment matrix and integrated into a spatially explicit modeling platform, allowing visualization and comparison of the impact on ecosystem service provision of land-use scenarios under rubber plantation and settlement expansion. The results show the capacity of current (2020) and future land-use patterns to provide locally relevant ecosystem services, indicating a decline in capacity of ecosystem service provisioning in the future compared to the 2020 land-use patterns, a threat to the benefits humans derive from ecosystems. This highlights urgent need for policies and measures to control the drivers of land-use/land-cover change. Furthermore, the results emphasize the importance of diversifying land-use/land-cover types for sustainable landscape development. The paper contributes new insights into how spatially explicit and semi-quantitative methods can make stakeholder perceptions of landscape dynamics explicit as a basis for implementing integrated landscape approaches.

Change in Bhutan’s Land Use and Land Cover from 1930 - 2020

The land is a fundamental component of Bhutan's geographical makeup, characterized by natural features and human activities. Bhutan's land can be divided into land use and land cover (LULC), where human activities contribute to land use, and natural elements define land cover. This paper analyzes Bhutan's LULC patterns, emphasizing the evolving trends in major LULC types, strengths and challenges of sustainable land use management, and envisioning its future trajectory. In recent years, Bhutan's land-use pattern has displayed a predominant forest cover, encompassing a significant portion of the total land area. Similarly, the built-up area in Bhutan is gradually increasing, reflecting the country's ongoing urbanization and development activities. A long-term analysis reveals dynamic shifts in agricultural land in Bhutan. While there has been a historical expansion of agricultural areas, recent trends may suggest a potential slowdown or decline, influenced by factors such as urban growth and changing economic landscapes. Like community forestry practices in Bhutan, successful conservation efforts may also influence land-use changes. In the eastern Himalayas, Bhutan faces challenges related to snow/glacial cover impacted by climate change. Increasing temperatures in the region contribute to alterations in snow/glacial patterns, necessitating a focus on environmental conservation and sustainable practices to preserve these vital resources. The land tenure system and land use policies in Bhutan have evolved and been shaped by socioeconomic and political dynamics. Bhutan needs to adapt and formulate effective policies to address contemporary challenges and promote sustainable LULC management. Implementing specific LULC zones, as outlined in Bhutan's land use policies, is crucial for ensuring sustainable land management practices.

Measurement of 2D and 3D Fractal Features of Urban Morphology from an Architectural View and Its Influencing Factors

Urban morphology has been empirically demonstrated to be self-organized and can be quantified by fractal dimension. However, the spatial variation rule of fractal features at the sub-zone scale has yet to be uncovered, as well as the relationship between fractal dimension values and road network or land-use patterns. In this study, the urban area is partitioned into 158 grid units, with subsequent calculations conducted to determine the fractal dimensions (using 2D box-counting and 3D voxel-counting methods), road network characteristics, and land-use patterns within each individual unit. The pattern of how architectures fill into the 2D or 3D embedding space at the grid level is revealed. Moreover, the spatial relationship between the road network, land-use, and their impacts on the local architectural layout is elucidated by employing MGWR, a model that incorporates the principles of fitting localized spatial regression. The results are as follows: (1) urban morphology follows fractal laws at a sub-zone scale, both in a 2D plane and 3D volume; (2) the filling degree of architecture is high in the urban center but low in the periphery areas; (3) the selected variables fit well with the regression models; (4) there is spatial heterogeneity regarding the influence of each factor. The research findings provide valuable insights into the theoretical relationship between urban morphology and the composite structure of road networks and land use. This facilitates identifying crucial areas and priority directions for urban renewal construction, as well as optimizing architectural design to improve efficiency and functionality.