Landscape Pattern Changes Research Articles

Landscape Analysis and Ecological Risk Assessment during 1995–2020 Based on Land Utilization/Land Coverage (LULC) and Random Forest: A Case Study of the Fushun Open-Pit Coal Area in Liaoning, China

China’s Fushun open-pit mine is the largest century-old coal mine in Asia. Large-scale mining and the use of coal has caused dramatic changes in the regional urban landscape pattern, seriously affecting the ecological function and ecosystem stability of its surrounding landscape. Evaluating the ecological risks of the landscape in the urban areas of open-pit mines contributes to the risk management of regional ecosystems and the sustainable development of society. This study selected six-phase Landsat ETM/OLI remote sensing images from 1995 to 2020 and combined them with the random forest model to carry out an LULC classification of the open-pit mine and its surrounding areas and, on this basis, discusses the evolution of its landscape pattern and evaluates the ecological risks. It fills the gap in the research on the evolution of regional landscape patterns and ecological risks in the study area and improves the automatic classification efficiency of LULC for use in open-pit mines. The results show that the classification accuracy of LULC regarding open-pit mines based on image pixels and the random forest model can reach 30 m, and the rate of accuracy can reach 92–97%. From 1995 to 2020, the coverage area of forest land and building land in the study area has increased and is mainly composed of grassland and undeveloped land. The use of land was transferred to the mining area, the water body area maintained a relative dynamic balance, and the overall vegetation coverage of the mining area was greatly improved; the forest land began to expand from the surrounding area to the mining area in 2010, and the construction land began to move from the areas surrounding the mining area to the surrounding valleys in 2015. The landforms have extended radially, and the landscape sprawl index has increased, indicating the optimization of the ecological environment; the high- and medium-risk areas decreased by 75.51 km2, the low-risk areas expanded by 461.48 km2, and the overall ecological risk index decreased. From this, it is possible to conclude that the landscape restoration project adopted in the study area has achieved great results, and the improvement of the ecological environment also directly affects the increase of construction land. These research results can provide scientific guidance for the rational utilization and sustainable development of land resources in urban areas of open-pit mines.

Artificial afforestation increased the distribution area and landscape complexity of planted forests in Tibet over the past 30 years

Afforestation plays an important role in improving the ecological environment and promoting local economic development in countries around the world. Although the artificial afforestation project in Tibet has been conducted for more than 30 years since in 1990 s, few studies have examined the dynamic changes in landscape patterns of planted forests in this region since the implementation of the project. This study used Google Earth Engine (GEE) and Landsat data from 1990, 2000, 2010 and 2020 to construct a Normalized Difference Vegetation Index (NDVI) time series curves and an optimal classification model based on the Jeffries-Matusita (J-M) distance. Then, the changes in landscape indices of planted forests in the Tibet Autonomous Region over the past 30 years were examined. The results showed that the area of planted forests increased from 9889.20 ha to 165,879.36 ha by artificial planting, with an average annualized growth rate of about 9.86%. In terms of the landscape pattern, the connectivity and aggregation degree of planted forests increased; the Cohesion (COH) and Aggregation Index (AI) increased by 44.60% and 26.03%, respectively. However, the fragmentation indices also increased to a certain extent due to the increased area and discontinuous planting; the Number of Patches (NP), Patch Density (PD) and Landscape Shape Index (LSI) increased by 32,262, 0.03 and 138.88, respectively. Among the seven regions of Tibet, these changes were most obvious in Lhasa, Qamdo and Shannan regions. Our results indicate that the planted forest area has significantly increased over the past 30 years although the landscape complexity has also increased because of discontinuous planting. These findings highlight the remarkable achievements of the Tibetan afforestation project over the past 30 years.

Spatial planning constraints will mitigate the fragmentation trajectory of natural and semi-natural landscapes: a case of Lushan City, China

ContextThe biodiversity faces an underlying threat from landscape fragmentation resulting from rapid urbanization. Examining the future trajectory of landscape fragmentation is imperative to understanding the impact of current spatial planning constraints on natural and semi-natural habitat preservation, ecosystem services, and sustainability.MethodsWe employed a Patch-generating Land Use Simulation (PLUS) model to simulate and predict the land use and landscape pattern changes in Lushan City under two distinct scenarios: “Planning Constraints (PC)” and “Natural Development (ND)”. We then identified an appropriate landscape fragmentation index (LFI) that effectively captured the fragmentation essence. To determine the optimal scale, we adopted an experimental approach using both the moving window (MW) method and the semi-variance function. By constructing a LFI spatiotemporal sequence and conducting trend analysis, we identified the potential fragmentation areas (PFA) with significant fragmentation tendencies.ResultsThe spatial planning constraints will (1) prevent the encroachment of construction land into 2.14 km2 of cropland, 0.21 km2 of forest, and 0.13 km2 of grassland; (2) shift the highly fragmented area from the northeastern portion of Lushan to the planned area defined by the development boundary; (3) mitigate and decelerate the trend of landscape fragmentation in natural and semi-natural landscapes, decrease PFA by 7.74 km2 and preserve 15.61 km2 of natural landscapes. (4) still leave 29.42% of forest and 22.82% of grassland at risk of fragmentation.ConclusionsSpatial planning constraints will effectively control the potential fragmentation in natural and semi-natural landscapes by changing the spatial distribution of LFI and PFA. This control mechanism will greatly exclude the anthropogenic impact and ensure the conservation of habitats. The habitats remaining within PFA should be focused in future eco-management optimization.

Agrivoltaics and landscape change: First evidence from built cases in the Netherlands

The need to advance energy transition has arisen from the global challenge of climate change. Shifts to renewable energy sources, such as solar energy, are crucial for reducing carbon emissions and mitigating climate change. The use of agrivoltaics—the combination of food and renewable energy production with photovoltaic technology—is gaining scientific attention. Agrivoltaics is a type of multifunctional energy landscape and thus reduces land use conflicts between energy and food production. However, while agrivoltaics has begun to proliferate at a global scale, the associated landscape changes have so far received little attention. This knowledge gap is critical, as there is clear evidence that landscape change often contributes to low levels of acceptance of solar power installations. To address this gap, this study examines landscape changes brought by agrivoltaic installations in the Netherlands. Four representative built cases were examined making use of key landscape change indicators extracted from the literature and fieldwork. The study revealed varying degrees of landscape change across the examined cases. Changes in the agricultural landscape pattern and openness emerged as prominent landscape changes. Changes in crop type and in historical linear landscape structures—often associated with the implementation of conventional solar power plants—were not identified. Policy attention to the siting and design of agrivoltaic systems in the landscape is needed to positively influence social acceptance of this relatively novel solution and thereby advance energy transition.

Dynamic simulation of landscape ecological security and analysis of coupling coordination degree: A case study of Bole.

The ecological security of oasis cities in arid and semi-arid regions is highly susceptible to changes in regional landscape patterns and the degree of coordination between human activities and the environment. At the same time, the ecological security of urban landscapes also profoundly affects the success of regional economic and environmental coordination and development. This study is based on land use data from 1990, 2000, 2010, and 2020, as well as land use data from the natural development scenario (NLD), economic development scenario (ECD), ecological development scenario (ELD) and ecological-economic development scenario (EED) simulated by the patch-generating land use simulation (PLUS) model in 2030. From the perspective of production-living-ecological land (PLEL), it analyzes the changes in the past and future landscape ecological security and coupling coordination characteristics of Bole. The results show that from 1990 to 2020, Bole was mainly dominated by grassland ecological land (GEL) and other ecological land (OEL), accounting for a total proportion of 69.51%, with a large increase in production and living land area; the average value of landscape ecological risk is decreasing, and the landscape ecological security of Bole is developing towards benignity; the area of highly coupled coordination zone is decreasing continuously, while that of basic coordination zone and moderate coordination zone is increasing continuously. Under the 2030 EED scenario, the overall changes in various types of land use are not significant, and the average value of landscape ecological risk is the smallest, but it is higher than that in 2020 as a whole; under EED scenario, the area of highly coordinated zone and moderate coordinated zone is the largest among four scenarios, and the best coupling coordination level among the four scenarios. Landscape ecological security and its coupling coordination will be affected by land use patterns. Optimizing regional land use patterns is of great significance for improving urban landscape ecological security and sustainable high-quality development.

Multiscale effects and drivers of landscape heterogeneity for water‐related ecosystem services in urban agglomerations

AbstractUnderstanding the multiscale impacts and drivers of urban agglomeration landscape patterns for ecosystem services (ESs), especially water‐related ecosystem services (WESs), is essential for the development of regional ecological management. However, the multiscale impacts and driving mechanisms of urban agglomeration landscape patterns for ESs have not been adequately explained. In this study, multivariate data were employed, and the InVEST model, trend test method, coupled GeoDetector and geographically and temporally weighted regression (GTWR) method were utilized to comprehensively explore the spatial and temporal changes in landscape patterns and WESs in the Pearl River Delta urban agglomeration (PRDUA) at various grid and administrative scales from 1990 to 2020 and to determine the driving mechanisms affecting WESs. The results indicated that the variation characteristics of landscape patterns and WESs in the PRDUA were consistent, forming a binary spatial structure of core and peripheral areas in an inverted “U” shape around the estuary of the Pearl River. The relationship between landscape patterns and WESs weakened with the increase of scale, and the correlation coefficient decreased by approximately 0.10 from 5 km to 10 km grid scale. Additionally, precipitation (PRE) was the main factor controlling WESs changes in the PRDUA, explaining more than 50% of the changes in WESs, and the regression coefficients ranged from 0.0825 to 0.1584. Changes in WESs were the result of the combined effects of natural factors, including PRE, landscape pattern, elevation, slope, and socioeconomic factors, such as population and gross domestic product (GDP). Overall, these findings could contribute to optimizing regional landscape patterns and fostering sustainable development of the ecological environment in urban agglomerations.

Water cycle evolution in the Haihe River Basin and its relationship with landscape pattern changes

Landscape patterns and water cycle processes have changed significantly in recent decades as a result of intensive interference from human activities. Although the intensification of the global water cycle is well illustrated from a climate change perspective, using landscape index to characterize the evolution of water cycle have been less explored. This study aimed to investigate the water cycle status and its evolution from the perspective of landscape patterns. A water cycle intensity (WCI) evaluation model based on the landscape index was developed. Defined as the ratio of the water resource circulation to the natural circulation, the WCI was used to analyze the water cycle evolution trend in each region of the Haihe River Basin. Through correlation and dynamic change trend analyses, the patch density (PD) of the urban areas and runoff landscape index (RLI) were identified as synchronizing with the WCI changes. The mathematical relationships between the landscape indicators (PD and RLI) and WCI were explored. Thereafter, according to the WCI development and its impact on the ecological environment, three categories of water cycle statuses (WCSs) were proposed: the natural circulation status (NCS), moderately developed status (MDS), and overdeveloped status (ODS). The WCS evolution trend in the Haihe River Basin was evaluated and the results showed all regions have evolved into a state of ODS with WCIs above 35% in 2010 and five of the plain regions greater than 80%. The proposed approach can be effectively applied to evaluating and predicting WCS in ungauged basins or future landcover scenarios, thereby providing a new perspective and effective tools for water resource management.

Comparative study and effects of urban green scape on the land surface temperature of a large metropolis and green city

Previous studies have provided valuable insights into the impact of green space (GS) on land surface temperature (LST). However, there is a need for in-depth comparative research on changing landscape patterns in cities and their effects on the urban thermal environment. This study investigates the spatial arrangement of GS and the influence of impervious surfaces on LST in urban areas, examining their cooling and warming effects in the urban landscapes of Beijing and Islamabad. The study aims to assess the impact of the spatial arrangement of GS on LST using a moving window of 1 km2 to analyze the overall effect of landscape patterns on the urban environment. Using Gaofen (GF–2) and Landsat–8 satellite data, we examined the biophysical surface properties of core urban areas. The results indicate a significant difference in the mean LST of 5.44 °C and 3.31 °C between impervious surfaces and GS in Beijing and Islamabad, respectively. The barren land and GS in Islamabad experience a higher LST of 3.39 °C compared to Beijing, which accounts for 1.39 °C. In Beijing, configuration metrics show no significant effect on urban LST, while edge density (ED) exhibits a slightly negative trend. In contrast, in the city of Islamabad, the landscape shape index (LSI), patch density (PD), and number of patches (NP) metrics have a significant influence on LST. The cooling effect of GS patches (0.1–0.5 ha) is more pronounced, while that of GS patches of 15–20 ha shows no significant effect on LST. The temperature difference (TD) of 5.01 °C was observed from the edge of GS in Beijing and 3.3 °C in Islamabad. Considering Islamabad's lush green scape compared to Beijing, this study suggests that Islamabad may experience an increase in LST in the future due to urbanization. This study's findings may assist urban policy-makers in designing sustainable green city layouts that effectively address future planning considerations.

Exploring the landscape pattern change analysis for the transboundary Nyungwe-Kibira Forest (2000–2019): a spatially explicit assessment

Introduction and aimEnsuring the protection and restoration of forest ecosystems is vital to maintaining and restoring ecological balance in deforested or degraded landscapes. However, sustainable development faces challenges from high human impacts on natural forest ecosystems, insufficient advanced conservation measures, and limited engagement of local communities in developing nations. The aim of this study was to explore the utility of spatial remote sensing datasets in examining the landscape pattern changes within the transboundary Nyungwe-Kibira Forest from 2000 to 2019. This aimed to emphasize the necessity of understanding the intricate dynamics of this ecosystem and its susceptibility to human activities in order to bolster diverse restoration initiatives throughout the region.MethodsThe landscape pattern change in the Nyungwe-Kibira between 2000 and 2019 was analysed using high-resolution Landsat data. This analysis encompassed an evaluation of the dynamics of changes in built-up, cropland, and forest areas within the region. Especially, primary data derived from the Landsat dataset and secondary data from reports such as the Outlook Report were employed to elucidate the ongoing landscape transformation within and surrounding the transboundary forest.Results and discussionThe analysis revealed a net change of +62.3% and +18.07% in built-up and cropland areas, resulting in a gross change of 14,133 ha and 6,322 ha in built-up and cropland areas, respectively. Furthermore, the forest experienced an overall gain of 9.11%, corresponding to a net loss of 6.92% due to deforestation, estimated at -14,764 ha. The analysis also indicated that built-up areas accounted for approximately 33.02% of the net forest loss, primarily affecting the northern edge of the Rwanda region, while cropland expansion contributed to a net loss of forest (-9.48%), predominantly impacting the southeast portion of the forest in Burundi. Additionally, the forest is predicted to decrease by 0.74% by 2030, with current findings showing aggregated forest and cropland at 66% and 7%, dissected rangeland at 24%, and created built-up areas at 3%. The findings indicate that the Nyungwe-Kibira Forest is undergoing notable transformations, highlighting the necessity of land-based projects and mitigation plans to facilitate the restoration of the forest from its historical changes. Without proactive measures, an ongoing decrease in forest area by 2030 is anticipated.

Synergistic impacts of Landscape, Soil, and environmental factors on the spatial distribution of soil aggregates stability in the Danjiangkou reservoir area

Soil aggregate stability (SAS) plays a crucial role in determining the soil's resistance to erosion. Conducting a spatial variability analysis of SAS in the reservoir area, which is highly susceptible to soil degradation and erosion, can yield valuable insights for agricultural practices, landscape planning, and environmental management in this region. Nevertheless, existing research remains constrained in its capacity to accurately map and forecast soil aggregates at a spatial level. This study aims to investigate the spatial distribution of SAS in the Danjiangkou reservoir area, as well as to explore the intrinsic linkage mechanisms between changes in soil properties, environmental factors and landscape patterns and SAS. Results revealed significant spatial variations in SAS within the vicinity of the Danjiangkou reservoir area. Notably, soil properties (including clay, available potassium, soil organic matter, and available phosphorus), environmental factors (such as digital elevation model, slope, land surface temperature difference between seasons (ΔLST)), and landscape pattern (largest patch index (LPI), shannon’s diversity index (SHDI), edge density (ED)) significantly affected the spatial variability of SAS, explaining 18.91%, 8.22%, and 8.17% of the total variability of soil SAS, respectively. Structural equation modeling results indicated that altering soil properties serves as the primary approach to enhance SAS. Furthermore, interventions targeting landscape factors such as LPI, SHDI, and ED, alongside environmental factors like ΔLST and slope, exert direct influences on SAS, while also indirectly impacting it through their effects on soil properties. These findings contribute to the design of land planning and soil and water conservation measures in the reservoir watershed, promoting its protection of soil structure and its ecological service function.

How changes in landscape patterns affect the carbon emission: a case study in the Chengdu-Chongqing Economic Circle, China.

The construction of low-carbon cities is an optimal means to balance the competing interests of economic growth and carbon emission reduction. This study focuses on the optimization of land use patterns with a low carbon orientation, taking the Chengdu-Chongqing Economic Circle (CCEC), the fourth-largest economic growth pole in China, as an example. The panel data regression analysis is carried out to identify the dynamic correlations between the landscape changes and the carbon emission induced by land use and land cover change (LICE) of each city, each year, for the last 20 years. The results show that the CCEC has witnessed a 142.85% increase in carbon emissions during the period studied, with the growth of built-up land contributing 94% of total carbon emissions from 2000 to 2020. By constructing the panel regression model, this study finds that the intensity of carbon emissions increases significantly as the urban built-up land area and the agglomeration of artificial structures increase. The conversion of cropland, which dominates the landscape pattern, to built-up land has led to further fragmentation of the landscape pattern and a reduction in LPI, thus increasing carbon emissions. And a more complex regional landscape pattern will have a positive impact on carbon emission reduction. Based on the above findings, suggestions are articulated for carbon emission reduction.

The spatial response of carbon storage to territorial space composition and landscape pattern changes: A case study of the Fujian Delta urban agglomeration, China.

Understanding the impact mechanisms of territorial space composition and landscape pattern changes on carbon storage is critical to balance the development and utilization of territorial space and the conservation of the ecosystem. Thus, taking the Fujian Delta urban agglomeration (FDUA) of China as an example, this paper analyzed the impact of the transference in territorial space composition and the change in the coupling coordination degree (CCD) of landscape patterns on carbon storage based on the urban-rural gradient and grid scales. Results illustrated that the areas of agricultural, green, and blue spaces continued to decline, while the intensity of economic space expansion increased from 20.86 to 42.45% during 2000-2020. The grids with CCD change of landscape patterns declined mainly (accounting for 64.31%) in the first decade and rose mainly (accounting for 76.79%) in the second decade. The carbon loss of each under rural gradient was gradually serious. The percentage of grids with moderate and significant decrease in carbon storage escalated from 27.83 to 70.21%. Additionally, grids experiencing high carbon loss moved from the northeast coast to the southwest inland. The response of carbon storage change showed that the expansion of agricultural space occupied by economic space played a crucial role in the carbon loss in each urban-rural gradient. The carbon loss caused by supplementing agricultural space with green space increased from the urban to the field. Enhancing the CCD of landscape patterns can boost carbon storage, and the scattering expansion of economic space needs to be avoided. This paper provides a novel perspective to explore the spatial response of carbon storage change to the territorial space composition and landscape pattern evolution, which is important to optimize the territorial space pattern and improve the regional carbon sink capacity.

Spatio-temporal characteristics of traditional village landscape pattern and its influencing factors from the perspective of tourism development: a case study of Huangcheng Village, China

ABSTRACT Tourism development promotes economic income and cultural protection of traditional villages, but it also disturbs their landscape pattern and ecosystem. This study is aim to explore the process characteristics and mechanisms of the impact of tourism development on the landscape pattern of traditional villages. Taking Huangcheng Village, a typical tourism-oriented traditional village as a case, this research selects four remote sensing images from 1995 to 2020 according to its key time nodes of tourism development, analyzes its landscape expansion and pattern change, and uses Geodetector to explore influencing factors. The results show that: (1) The landscape change mainly presents the non-natural landscape continuously occupying the natural landscape, and expands continuously around tourist resources in edge-expansion and leapfrog-expansion manner, among which the expansion from 2003 to 2011 is the most significant; (2) The dominance and connectivity of non-natural landscape are enhanced, and the overall landscape pattern experiences a “relatively complete – tending to fragmentation – tending to completeness” change process; (3) The dominant factors affecting landscape pattern have stage characteristics. The results emphasize the role of tourism-related socio-economic and policy factors in influencing landscape pattern, which is significant for the landscape pattern optimization and sustainable development of tourist-type traditional villages.

Landscape pattern changes in coal resource-based cities: A case study of Huainan City in China

Currently, coal resource-based cities (CRBCs) are facing challenges such as ecological destruction, resource exhaustion, and disordered urban development. By analyzing the landscape pattern, the understanding of urban land use can be clarified, and optimization strategies can be proposed for urban transformation and sustainable development. In this study, based on the interpretation of remote sensing data for three dates, the landscape pattern changes in the urban area of Huainan City, a typical coal resource-based city in Anhui Province, China were empirically investigated. The results indicate that: (1) There is a significant spatial-temporal transformation of land use, with construction land gradually replacing arable land as the dominant land use type in the region. (2) Landscape indices are helpful to reveal the characteristics of land transfer and distribution of human activities during a process. At the landscape type level, construction land, grassland, and water bodies are increasingly affected by human activities. At the landscape composition level, the number of landscape types increases, and the distribution of different types of patches becomes more balanced. In addition, to address the problems caused by the coal mining subsidence areas in Huainan city, three landscape pattern optimization strategies are proposed at both macro and micro levels. The research findings contribute to a better understanding of land use changes and their driving forces, and offer valuable alternatives for ecological environment optimization.

Analyzing the dynamic changes and causes of greenspace landscape patterns in Beijing plains

Beijing Plain is an important region for ecological planning and management. In the past decade, human activities have dramatically changed the spatial and landscape patterns of greenspaces in Beijing Plains. However, very few studies have assessed the main causative factors of these changes. Herein, we analyzed the spatial patterns of greenspaces in the Beijing Plains between 2015 and 2020 using multi-source remote sensing data, geographical information system, and the landscape pattern index. Additionally, we utilized gray correlation analysis to quantitatively analyze the main factors contributing to dynamic changes in the greenspace landscape patterns. We found that the greenspaces in Beijing showed a gradual increase annually from 2015 to 2020. Further, the conversion of greenspace types throughout the study period mainly included the interconversion of woodland and cropland, water, and impervious surfaces. The transfer out of woodlands has been decreasing annually while the transfer in has been increasing. Grassland and shrubs were almost entirely converted into woodlands and other land use types. The fragmentation of the overall greenspace reduced, aggregation increased, and landscape patches tended to be fully distributed, connected, simpler, concentrated, and regular. The advantages of woodland landscapes were gradually becoming more evident. Population urbanization, rapid economic growth, and policies were important factors affecting changes in greenspace landscape patterns. The study findings provide a scientific reference to adjust the greenspace structure, transform and upgrade the existing greenspaces, and ensure sustainable development of cities.

Study on Changes of Landscape Pattern in Changbaishan Nature Reserve Based on Remote Sensing Images

Study on Changes of Landscape Pattern in Changbaishan Nature Reserve Based on Remote Sensing Images

Impacts of urban landscape pattern changes on land surface temperature in Southeast Brazil

Urban sprawl is a global concern, considering the current climate change scenario. The conversion of natural habitats or other land uses to urban areas increases the Land Surface Temperature (LST), impacting people mainly in tropical regions, such as Brazil, where the temperature is aggravated by high air humidity. In this context, we assessed the seasonal variation of LST in response to the land-use/land-cover (LULC) changes over a large city in southwest Brazil during the last 36 years (1985–2020). We used Mapbiomas LULC data and LST retrieved from the Landsat series with the Google Earth Engine platform. The methodology involved the change detection analysis from 1985 to 2020 for all LULC types, a non-parametric Dwass-Steel-Critchlow-Fligner test to estimate the LST spatio-temporal variability over different LULC types, and a non-parametric Sperman's rho test and scatter plots to relate LST changes to the LULC patterns. The results presented areas exchanging under an intense urbanization process, wherein nearly 13% of the transitions were from agricultural to urban areas. These transitions occurred jointly with an increase in temperature for all LULC types. Forest formation registered the lowest LST and a moderate to strong negative correlation with LST in both seasons. On the other hand, urban areas showed the highest temperatures and a moderate to strong positive correlation with LST in summer. From 1985 to 2020, the mean temperature in urban (built-up) areas during the summer increased by 7 °C. In 2020, the mean temperature in urban areas was 32.5 °C and 27.8 °C in forested areas during the summer. The main contribution of this study is to provide evidence-based support for establishing LULC governance at the city scale. It offers essential scientific information about the detrimental impact of urban sprawl against the climate benefits of green infrastructure on the city scale, even in tropical regions with high forest fragmentation, temperatures, and long periods with high air humidity.

The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization.

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.

Identifying the Relationships between Landscape Pattern and Ecosystem Service Value from a Spatiotemporal Variation Perspective in a Mountain–Hill–Plain Region

Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.

Assessing landscape fragmentation and its implications for biodiversity conservation in the Greater Accra Metropolitan Area (GAMA) of Ghana

ContextThis paper discusses the impact of urban expansion on the environment, including its effects on biodiversity conservation. As urban areas develop, natural habitats such as forests and agricultural lands are transformed into industrial, commercial, and residential uses, which alters landscape patterns and can lead to fragmentation. Fragmentation can have negative impacts on biodiversity, such as deforestation, alteration of watercourses leading to flooding, reduced availability of food, and increased pollution. The objective of this paper is to provide a comprehensive and data-driven analysis of the urban expansion of Greater Accra Metropolitan Area (GAMA) over time, and its effects on biodiversity. The idea is to capture the changes in land cover and landscape patterns in GAMA from 1991 to 2022 and predict the region’s landscape patterns for 2030. This was achieved by performing a land cover change analysis of GAMA from 1991 to 2022; capturing the evolution of landscape patterns by calculating landscape metrics; and using multiradial fractal dimension as a transition variable to model and predict the land cover and landscape pattern of GAMA for 2030. The landscape metrics revealed extensive fragmentation of the Vegetation land cover type of GAMA, indicating a negative impact on biodiversity conservation, species movements, ecosystem functioning, and long-term ecological resilience. The trends highlight the importance of considering landscape connectivity, habitat fragmentation and spatial arrangement of land cover types for assessing ecological processes and urban development impacts on the environment. Additionally, multiradial fractal dimension of built-up areas is recommended as an explanatory variable for urban growth modelling.