Land Expansion Research Articles

Analysis of the Spatial-Temporal Characteristics and Driving Factors of Cultivated Land Fragmentation Under the Expansion of Urban and Rural Construction Land: A Case Study of Ezhou City

A systematic understanding of the spatial-temporal evolution patterns of cultivated land fragmentation (CLF), its driving factors, and its relationship with the expansion of urban and rural construction land is essential for identifying strategies to mitigate CLF in rapidly urbanizing regions. This study combined landscape fragmentation with ownership fragmentation, analyzing CLF through three dimensions: resource endowment, spatial concentration, and convenience of utilization, with eight selected indicators. By comparing village-level data from 2013 to 2022, we explored the key drivers of CLF and its conflicts with urban and rural construction land expansion. The findings indicate a clear spatial variation in village-level CLF in Ezhou, characterized by low fragmentation in the northwest and northeast, and high fragmentation in the southwest and central regions. This pattern is in contrast to Ezhou’s economic development, which decreased progressively from east to north and south. Over the study period, village-level CLF in Ezhou evolved from being primarily moderately and relatively severely fragmented to predominantly severely and relatively severely fragmented, with an overall declining trend and more pronounced polarization. At the same time, the CLF within the village region demonstrated notable spatial clustering features, with a rapid increase observed between 2013 and 2022. It was also discovered that CLF is driven by various factors, with the main influences being the proportion of construction land, land use intensity, and population density. Cultivated land is the main source of both urban construction land (UCL) and rural construction land (RCL), with average contribution rates of 46.47% and 62.62%, respectively. This research offers empirical evidence for rapid urbanization and serves as a critical reference for rural revitalization and coordinated urban–rural development, with potential guidance for future policy formulation and implementation.

Advancing Water Security and Agricultural Productivity: A Case Study of Transboundary Cooperation Opportunities in the Kabul River Basin

The Kabul River Basin (KRB) is witnessing frequent flood and drought events that influence food production and distribution. The KRB is one of the world’s poorest regions regarding food security. Food security issues in the KRB include shifts in short-term climate cycles with significant river flow variations that result in inadequate water distribution. Due to the lack of hydro-infrastructure, low irrigation efficiency, and continuing wars, the Afghanistan portion of the KRB has experienced low agricultural land expansion opportunities for food production. This research assesses the relationship between flood mitigation, flow balances, and food production and, cumulatively, assesses the social and economic well-being of the population of the KRB. SWAT modeling and climate change (CCSM4) implications are utilized to assess how these relationships impact the social and economic well-being of the population in the KRB. The intricacies of transboundary exchange and cooperation indicate that the conservation of ~38% of the water volume would nearly double the low flows in the dry season and result in the retention of ~2B m3/y of water for agricultural developmental use. Results show that the peak flood flow routing in reservoirs on the Afghanistan side of the KRB would have a substantial positive impact on agricultural products and, therefore, food security. Water volume conservation has the potential to provide ~44% more arable land with water, allowing a ~51% increase in crop yield, provided that improved irrigation efficiency techniques are utilized.

Lacustrine Wetlands Landscape Simulation and Multi-Scenario Prediction Based on the Patch-Generating Land-Use Simulation Model: A Case Study on Shengjin Lake Reserve, China

Landscape simulation and prediction are crucial for understanding the dynamic evolution and future trends of wetlands. However, only a few existing studies have focused on the applicability and limitations of commonly used land-use/cover change (LUCC) simulation models in lake wetland landscapes. Taking Shengjin Lake Reserve in China as the study area, we firstly analyzed landscape variations during 2010–2020 using multisource remote sensing images. Then, the patch-generating land-use simulation (PLUS) model was employed to simulate wetland landscapes in 2020, the accuracy and limitation of which in simulating lacustrine wetlands were also explored. Lastly, the changing trends of wetland landscapes in 2030 under different development scenarios were predicted. The results show that the landscape of Shengjin Lake Reserve has changed significantly during 2010–2020, with increases in mudflats, reservoirs/ponds, woodlands, and built-up land, and there has been decreases in lakes, grass beaches, and croplands. The PLUS model demonstrated an ideal simulation accuracy for Shengjin Lake Reserve, with the overall accuracy exceeding 80%, kappa coefficient greater than 0.75, and figure of merit (FOM) coefficient of 0.35, indicating that the model can capture the dynamic changes in wetland landscapes accurately. The simulation accuracy can be effectively improved with the adjacent initial year, shorter time interval, and the primary driver factors. Under the natural development scenario, the number of patches in the Shengjin Lake Reserve increased sharply, and landscape fragmentation intensified. Under the urban development scenario, the expansion of built-up land increased, and the average patch area increased. In the ecological protection scenario, the Shannon diversity index and Shannon evenness index of the landscape improved significantly, and the natural wetlands such as grass beaches and lakes can be protected effectively. Our study confirms the applicability of the PLUS model in simulating and predicting lacustrine wetlands landscapes, and the conclusions provide a scientific basis for formulating reasonable development strategies to realize wetland resource conservation and management.

Spatiotemporal Dynamics and Prediction of Habitat Quality Based on Land Use and Cover Change in Jiangsu, China

Analyzing the spatiotemporal evolution characteristics of urban land use and habitat quality is crucial for the sustainable development of urban ecological environments. This study utilizes the land use data of Jiangsu Province for the years 2000, 2010, and 2020, applying the FLUS model to investigate the driving force behind land expansion and to simulate a prediction for the land use of 2030. By integrating the InVEST model and landscape pattern indices, this study analyzes the spatiotemporal evolution characteristics of habitat quality in Jiangsu Province and uses geographical detector analysis to examine the synergistic effects of influencing factors. The results indicate that, from 2000 to 2020, habitat degradation in Jiangsu Province progressively increased, with the spatial distribution of degradation levels showing a gradual change. Under the ecological protection scenario in 2030, habitat fragmentation was alleviated. Conversely, under the economic development scenario, habitat quality further deteriorated, resulting in the largest area of low-quality regions. Minimal changes occurred under the natural development scenario. (2) The landscape indices in Jiangsu Province experienced significant changes from 2000 to 2020. The continuous expansion of urban land into other land use types led to a trend of fragmentation, with a clear increasing trend in dispersion, sprawl, and Shannon’s diversity index, accompanied by a decrease in cohesion. (3) The dominant interacting factors affecting habitat quality were combinations of socioeconomic factors with other factors, indicating that the economy largely determines the spatial distribution pattern of habitat quality. The findings of this study provide optimization strategies for future spatial planning of land use types in Jiangsu Province and offer references for habitat quality restoration efforts in the region.

A Study on the Spatiotemporal Dynamics of Land Cover Change and Carbon Storage in the Northern Gulf Economic Zone of Guangxi Based on the InVEST Model

In recent years, the international community has increasingly focused on the “dual carbon” issue, as human-induced land use changes significantly impact ecosystem structure and carbon cycling. This study analyzes land use changes in the economic zone of the northern Gulf of Guangxi from 1980 to 2020, utilizing the InVEST model to simulate spatiotemporal changes in carbon storage and conducting zoning studies through spatial analysis. The findings reveal that ① forest land and arable land dominate the northern Gulf of Guangxi’s land use, with notable changes observed in forest land, unused land, and construction land areas. Forest land and construction land have increased by 1761.5 km2 and 1001.19 km2, respectively, while unused land has decreased by 1881.18 km2 from 2000 to 2020. ② The total carbon storage values in the northern Gulf of Guangxi in 1980, 2000, and 2020 were, respectively, 504.91 × 106/t, 487.29 × 106/t, and 500.31 × 106/t, with the expansion of construction land and conversion of forest land being the main reasons for the decrease in carbon storage. ③ In the northern Gulf of Guangxi, there is a slight upward trend in total carbon storage values over time. Spatially, higher carbon storage values are observed in mountainous and hilly areas at high altitudes, while the central and southern coastal areas exhibit lower carbon storage values. ④ The local spatial autocorrelation results reveal that Pu Bei County exhibits high–high clustering of carbon storage, while He Pu County undergoes a transition from high–low to low–low clustering, and several other administrative areas in Beihai demonstrates low–low clustering. Due to the imperative of economic development, the expansion of urban construction land encroaches upon ecological land, resulting in a decline in carbon storage. Therefore, in the Northern Gulf of Guangxi, it is essential to implement measures such as reforestation and establish ecological protection areas such as forests, grasslands, and wetlands to develop effective carbon sequestration methods and compensate for the carbon loss caused by the expansion of construction land.

County-Level Spatiotemporal Dynamics and Driving Mechanisms of Carbon Emissions in the Pearl River Delta Urban Agglomeration, China

Encouraging cities to take the lead in achieving carbon peak and carbon neutrality holds significant global implications for addressing climate change. However, existing studies primarily focus on the urban scale, lacking more comprehensive county-level analyses, which hampers the effective implementation of differentiated carbon mitigation policies. Therefore, this study focused on the Pearl River Delta urban agglomeration in China, adopting nighttime light data and socio-economic spatial data to estimate carbon emissions at the county level. Furthermore, trend analysis, spatial autocorrelation analysis, and Geodetector were adopted to elucidate the spatiotemporal patterns and influencing factors of county-level carbon emissions. Carbon emissions were predominantly concentrated in the counties on the eastern bank of the Pearl River Estuary. Since 2010, there has been a deceleration in the growth rate of carbon emissions in the region around the Pearl River Estuary, with some counties exhibiting declining trends. Throughout the study period, construction land expansion consistently emerged as a predominant factor driving carbon emission growth. Additionally, foreign direct investment, urbanization, and fixed asset investment each significantly contributed to the increased carbon emissions during different development periods.

Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China

Research on future land cover changes and carbon emissions is essential for effective land resource management and developing feasible carbon mitigation strategies. This study focused on the Yellow River Basin and employed the Future Land Use Simulation (FLUS) and Autoregressive Integrated Moving Average (ARIMA) models to project future land cover and carbon emissions. Additionally, bivariate spatial autocorrelation was utilized to analyze the relationship between them. Key findings are as follows: 1) Historically, the Yellow River Basin has experienced an expansion in construction land, forests, grasslands, and water, while cropland and unused land have diminished. Notably, construction land displayed the most significant changes, whereas grasslands showed minimal modification. Looking ahead, both the ecological protection and inertial development scenarios exhibit consistent trends with historical patterns across the land type categories. In contrast, the economic priority development scenario forecasts an increase in construction land, cropland, and grasslands, indicating a distinct shift compared to the other scenarios. However, the ecological protection scenario proves to be more sustainable. 2) In the absence of intervention, the simulated carbon emissions from construction land throughout the basin display a linear increase across various scenarios, with provincial-level variations showing an increase from southwest to northeast. However, Henan and Sichuan are expected to experience slower reductions in carbon emissions, compared to other projections. There is a notable positive correlation between carbon emissions and the comprehensive index, indicating that regions with high emissions typically experience substantial land and economic development. 3) Energy consumption projections for 2030 and 2060 indicate that to align with China’s carbon goals, it is essential to reduce energy consumption and adjust the fossil to non-fossil fuel ratio to reduce carbon emissions. Substituting coal with clean energy and enhancing energy efficiency will be more effective for achieving low-carbon emission targets. In summary, this study provides significant guidance for China’s ecological conservation, low-carbon emission strategies, and global carbon emission control efforts.

Exploring Drivers of Land Use/Land Cover Transformations in Goang Watershed Ethiopia: Integrating Local Community Perceptions with Remote Sensing Data

Land use/land cover (LULC) changes driven by human activities are major environmental challenges in many developing regions. This study assessed local community perceptions and household-level drivers of LULC change in northwest Ethiopia. The study combined remote sensing analysis of LULC change with household surveys to understand local perspectives and the socioeconomic, biophysical, and institutional factors influencing household engagement in deforestation activities. The household survey data was collected from 384 randomly selected household heads, as well as from focus group discussions and key informant participants. The remote sensing component used ERDAS IMAGINE 2014 software to classify satellite images and assess LULC changes over time. The quantitative socio-economic data was analyzed using descriptive statistics and econometric methods of the multivariate probit (MVP) model, while the qualitative data was presented using content analysis. The study revealed that population growth, poverty, and food insecurity were the major underlying driving factors, while agricultural land expansion, settlement growth, fuelwood collection, overgrazing, and forest fires were the major underlying causes of LULC change. The MVP model result indicated that gender, off-farm income, access to training, family size, educational level, and agroecology were key determinants of households’ participation in deforestation drivers such as forestland clearing for agriculture, fuelwood collection, timber harvesting, and overgrazing. These findings highlight the need for integrated land use policies and programs that address the socioeconomic and biophysical root causes of LULC change. This study recommends supporting alternative livelihoods, promoting fuel-efficient technologies, and tailoring interventions to different social groups and agroecological contexts of sustainable land use planning and natural resource management in the study site. Future studies should compare perceptions and drivers of land use change across different regions to identify common patterns and unique challenges. This approach will enhance understanding and inform targeted interventions for sustainable land management.

Ecosystem service value in the context of urbanization: comparison among economic-social regions of Vietnam

Urbanization is one of the important features of socio-economic development and it has a major impact on the value of ecosystem services (ESV). This study aims to quantify ESV for the entire country of Vietnam with the research unit being 6 socio-economic regions. This can be considered the first study in Vietnam to quantify the ESV for the entire country. The study calculated the annual urban land growth index (AI) and the annual urban land expansion rate (AER) to determine the urbanization status in the six study areas. The study collected input data from JAXA for four years: 1990, 2000, 2010, and 2020. Research results show that urban land area tended to increase and forest land area decreased sharply. The AI and AER indicated that the period 2000–2010 was a period of rapid growth in Vietnam. Meanwhile, the ESV for all of Vietnam increased year by year. The period 2000–2010 witnessed a growth in ESV about 2.35 times higher than the period 1990–2000, and about 0.1% lower than the period 2010–2020. Overall, MKD was the region showing strong growth in ESV from 1990 to 2020. Compared to that, NMR was the region with the largest decline in the 20 years from 1990 to 2010, and CHR in the past 10 years. This research contributes to enriching reference sources for Vietnamese and world researchers to have a broader view of ESV as well as the annual urban growth rate in Vietnam from 1990 to 2020.

PEMETAAN POTENSI SUMBER DAYA AIR UNTUK PERTANIAN LAHAN PRODUKTIF (STUDI KASUS: DESA KAMBUHAPANG DAN DESA KAMBATAWUNDUT)

Desa Kambuhapang and Desa Kambatawundut are villages located in the Lewa District of East Sumba Regency. This area is characterized by arid conditions and experiences an 8-month-long dry season. Most of the population in this region is engaged in agriculture, particularly dryland farming. The main water supply for agriculture in this area comes from low rainfall, resulting in limited water availability. The purpose of this study is to assess the water discharge potential in these two villages. Secondary data, including rainfall data, was obtained from two stations: the Waingapu meteorological station and the Lewa Paku rain station. Additionally, climatological data from 2012 to 2021 was used. ArcGIS 10.7 software was employed to map the area using Digital Elevation Model (DEM) data. The Modified Penman method was used to determine evapotranspiration, while the F.J. Mock method was applied to calculate the reliable discharge. The results showed that the average annual water availability, according to the F.J. Mock method, is 16.45 m³/s for the Lay Mbeda River and 16.54 m³/s for the Wai Wei River. The villages of Kambuhapang and Kambatawundut have sufficient water availability, with a total of 74.18% across an area of 63.12 km². The adequate water availability in these two villages is evident from the minimum discharge during the dry season, ranging from 6.60 to 7.12 m³/s. This indicates that the villages have sufficient water resources to support the expansion of productive agricultural land for the local community. The utilization of these water resources could be further optimized by providing supporting infrastructure to increase runoff storage, such as water reservoirs, small ponds, or retention basins.Keywords: mapping, water potential, water availability, waingapu, lewa paku

Anthropogenic Effects on Green Infrastructure Spatial Patterns in Kisangani City and Its Urban–Rural Gradient

Urban and peri-urban expansion significantly influences the spatial pattern of cities and surrounding zones. This study examines the spatial changes in green infrastructure components, specifically focusing on mature forests, short forests, and agricultural and grass lands from 1986 to 2021, using satellite imagery. Two landscape ecology indexes, the percentage of landscape (PLAND), and the largest patch index (LPI), were applied. PLAND provides insights into the proportion of habitat types, capturing overall extent, while LPI elucidates their spatial configuration. The research is conducted in a specific context of increasing urbanization and peri-urbanization in Kisangani city, DR Congo. The findings reveal a decline in both mature and short forests, respectively, from 1986 to 2021, and from 2006 to 2021 alongside a continuous expansion of agricultural and grass lands at the landscape scale. Moreover, the spatial pattern of mature and short forests exhibited significant variations across urban, peri-urban, and rural zones. In the context of 2021, in urban and peri-urban zones, mature forests account for less than 1% of the 2.25 km2 plots, against more than 35% in certain rural plots. Similarly, larger patches of mature forest in urban and peri-urban zones cover less than 0.5% of the 2.25 km2 plots, whereas they exceed 20% in rural zones. From 1986 to 2021, both mature and short forests experienced significant decline and fragmentation, particularly in urban and peri-urban zones, while agricultural and grass lands increased significantly in peri-urban and rural zones. These results raise concerns regarding the functions, services, and opportunities provided by mature and short forests in the context of global change. They also highlight the need for urban planning in Kisangani to prioritize green infrastructure preservation, focusing on maintaining forest connectivity and preventing further fragmentation. Policies should promote sustainable land use in peri-urban zones to achieve a balance between urban expansion and the provision of essential ecosystem services, thereby enhancing long-term resilience.

Spatio-temporal variation and prediction of land use and carbon storage based on PLUS-InVEST model in Shanxi Province, China

AbstractCoal mining in Shanxi Province for many years has caused regional land-use changes, seriously affecting the local ecological environment. To promote the green and sustainable development of this area and achieve the goal of “double carbon”, the PLUS-InVEST model was used to analyze the nearly 20 year land-use types transfer and carbon storage changes in the region based on the five periods of land-use data of Shanxi Province from 2002 to 2022 in this study. Three scenarios were set up to predict the data in 2032, and the driving forces of spatial differentiation of the carbon storage were analyzed by geographical detector. The results showed that: (1) Land-use change had an important impact on carbon storage. Construction land in Shanxi Province expanded by 3068.47 km2 from 2002 to 2022, an increase of 59.33%, and the rest of the land types, except for forest, continued to decrease, resulting in a decline in total carbon storage of 228.88 × 104 t. (2) The natural development scenario shows the same transfer of land as before in 2032. Under the urban development scenario, the expansion of construction land in Shanxi Province is the largest, and carbon storage decreases instead of increasing; under the ecological protection scenario forest and grassland increase, and carbon storage increase the most, with a value of 738.67 × 104 t. (3) The dominant driving factors for the spatial differentiation of carbon storage in Shanxi Province were the land-use degree comprehensive index and night light index, with the explanatory power of 0.866 and 0.755, respectively, and the interaction of the land-use degree comprehensive index with other factors had the most significant effect on the change of carbon storage. The study suggested that the expansion of construction land into high carbon storage categories was the main reason for the loss of carbon storage, and Shanxi Province should optimize the land-use structure and adopt ecological protection works to increase carbon storage effectively.

Spatiotemporal Pattern Analysis and Prediction of Carbon Storage Based on Land Use and Cover Change: A Case Study of Jiangsu Coastal Cities in China

Accurate estimation of terrestrial ecosystem carbon storage and the scientific formulation of ecological conservation and land use policies are essential for promoting regional low-carbon sustainable development and achieving the goal of “carbon neutrality.” In this study, the FLUS–InVEST model was used to evaluate the carbon stocks of the Jiangsu coastal zone in China from 1995 to 2020 and scientifically forecast the changes in carbon stocks in 2030 under three scenarios: natural exploitation, ecological protection, and economic development. The results are as follows: (1) From 1995 to 2020, carbon storage in the coastal zone initially remained stable before declining, a trend closely linked to the accelerated urbanization and economic growth of Jiangsu Province. (2) By 2030, carbon storage under the three scenarios exhibits a pattern of “S1 decrease–S2 increase–S3 decrease,” with a more significant increase in construction land under the natural development and economic development scenarios compared to the ecological protection scenario. (3) The sensitivity of carbon storage to land use changes varies across scenarios. In the natural development scenario, carbon storage is most affected by forest reduction and construction land expansion. In the ecological protection scenario, it is more responsive to increases in non-construction land. In the economic development scenario, the expansion of construction land leads to the most significant decrease in carbon storage. Therefore, when formulating future territorial spatial planning policies and urban development strategies, it is essential to consider ecological protection and economic development scenarios comprehensively, taking into account carbon sequestration capabilities. This approach will ensure effective conservation and restoration of damaged ecosystems while safeguarding the robust development of urban economies and societies.

Evaluation of Suitability for Built-Up Land Expansion and Land Use Simulation Based on Obstacle Factor Constraints

Evaluation of Suitability for Built-Up Land Expansion and Land Use Simulation Based on Obstacle Factor Constraints

Tracking tree demography and forest dynamics at scale using remote sensing.

Capturing how tree growth and survival vary through space and time is critical to understanding the structure and dynamics of tree-dominated ecosystems. However, characterising demographic processes at scale is inherently challenging, as trees are slow-growing, long-lived and cover vast expanses of land. We used repeat airborne laser scanning data acquired across 25 km2 of semi-arid, old-growth temperate woodland in Western Australia to track the height growth, crown expansion and mortality of 42 213 individual trees over 9 yr. We found that demographic rates are constrained by a combination of tree size, competition and topography. After initially investing in height growth, trees progressively shifted to crown expansion as they grew larger, while mortality risk decreased considerably with size. Across the landscape, both tree growth and survival increased with topographic wetness, resulting in vegetation patterns that are strongly spatially structured. Moreover, biomass gains from woody growth generally outpaced losses from mortality, suggesting these old-growth woodlands remain a net carbon sink in the absence of wildfires. Our study sheds new light on the processes that shape the dynamics and spatial structure of semi-arid woody ecosystems and provides a roadmap for using emerging remote sensing technologies to track tree demography at scale.

Spatial optimization of land use and carbon storage prediction in urban agglomerations under climate change: Different scenarios and multiscale perspectives of CMIP6

Land use/land cover (LULC) structure optimization can effectively increase carbon storage/carbon sequestration (CS) and help realize carbon neutrality goals1. Studying the spatial distributions of LULC and CS under climate change conditions is highly important for realizing sustainable development goals. This study is based on different climate change models, and the coordinated development of economic, water, carbon and ecological sustainability was considered to establish a comprehensive multiscale, multiscenario and multiobjective LULC optimization model. Then, different climate change scenarios were optimized, and regional CS values were predicted. The LULC simulation model provided satisfactory simulation results at different scales. Notably, the average accuracy exceeded 0.92. The optimized land expansion results exhibited heterogeneity. Forestland change accounted for the largest proportion of the total LULC change. After optimization, the CS values under the different scenarios were similar. The northwestern part of the study area served as the main carbon sink area. The aim of this study was to respond to future complex climate change by rationally planning the LULC structure, thus achieving the sustainable development of urban agglomerations.

Assessing the Imbalances in Growth between Urban Land and Urban Population and the Influencing Factors: An Allometric Growth Perspective

Maintaining a balance between urban land (UL) expansion and urban population (UP) growth is one of the goals of sustainable development, and maintaining this balance requires more theoretical exploration and regional experience. This paper re-evaluated the imbalances in growth between urban land and urban population (IGULUP) from the perspective of allometric growth and explored its influencing mechanism, taking urban agglomerations (UAs) in China as a case. This paper reveals that the growth rate of UL in China is slightly higher than that of the UP. However, the IGULUP vary according to development stages. UAs in the primary stage and the early growth stage face the dilemma where UL grows faster than the UP. Conversely, for UAs in the later growth stage and the mature stage, the growth rate of the UP is higher than that of UL. Finally, an increase in economic development level, population agglomeration, fiscal expenditure, and urban compactness can help mitigate the gap between UL and UP. In contrast, industrial structure, urbanization level, and foreign direct investment may hinder the improvement of IGULUP by accelerating the rate of land expansion. These findings may make theoretical contributions to the formulation of more targeted land use control policies and urban population growth strategies.

Spatially Explicit Impact of Land Use Changes in the Bay Area on Anthropogenic Phosphorus Emissions and Freshwater Eutrophication Potential.

Land use changes significantly impact anthropogenic phosphorus (P) emissions, their migration to a water environment, and the formation of freshwater eutrophication potential (FEP), yet the spatiotemporally heterogeneous relationships at the regional scale have been less explored. This study combines land use classification, P-flow modeling, spatial analysis, and cause-effect chain modeling to assess P emissions and P-induced FEP at a fine spatial resolution in Guangdong-Hong Kong-Macao Greater Bay Area and reveals their dynamic responses to land use changes. We find that land conversion from cultivated land to impervious land corresponded to an increase in P emissions of 4.1, 1.8, and 0.5 Gg during 2000-2005, 2005-2010, and 2010-2015 periods, respectively, revealing its dominant but weakening role in the intensification of P emissions especially in less-developed cities. Expansion of aquacultural land gradually became the primary contributor to the increase in both the amount and intensity of P emissions. Land conversions from cultivated land to impervious land and from natural water bodies to aquacultural land led to 35.9% and 25.3% of the increase in FEP, respectively. Our study identifies hotspots for mitigating the environmental pressure from P emissions and provides tailored land management strategies at specific regional development stages and within sensitive areas.

Once Common, Long in Decline: Dynamics of Traditional Orchards in a Central European Landscape

Traditional orchards are distinctive features of cultural landscapes in Central Europe. Despite their high level of ecological importance, they are in decline, and comprehensive spatial data over broad extents, which could enable a trend analysis, are lacking. We analysed traditional orchard maps from 1952 to 1967 and a map from 2010, generated via aerial image interpretation, for the state of Hesse (ca. 21,115 km2), which has the second largest share of traditional orchards in Germany. We aimed to (1) quantify long-term orchard dynamics, (2) compare orchard characteristics in terms of topographical, ecological, and socioeconomic factors, and (3) identify key drivers of orchard loss. We found that the number and area of orchards have clearly decreased across Hesse, with varying local and regional patterns. Further, historically old orchards tended to have a larger area, higher shape complexity, and were located closer to settlements, highways, and neighbouring orchards. In contrast, newly established orchards were often found at higher elevations and on steeper slopes. Finally, the three historical orchard hotspots also experienced the most notable losses driven by different factors, namely the expansion of Artificial Surfaces, Residential Buildings, and Agricultural Land. We highlight the importance of such multitemporal spatial data for a wide range of ecological applications, and we encourage the use of novel technologies to support geospatial analyses in the future.

Urban Habitat Quality Enhancement and Optimization under Ecological Network Constraints

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning.