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Context: Decades of intensifying human activities have led to drastic changes in land use and land cover (LULC) in the Poyang Lake Basin (PLB), resulting in significant changes in landscape pattern and ecosystem service value (ESV), thereby affecting regional sustainability. Objectives: We focused on understanding the impact of LULC changes on the landscape pattern and ESV of the PLB and used the Patch-generating Land Use Simulation model (PLUS) to predict LULC changes in 2050. Methods: We evaluated landscape patterns using landscape metrics and calculated ESV using the ecosystem service equivalent factor method. The Pearson correlation coefficient was used to analyze the correlation between landscape patterns and ESV from 1990 to 2020. Then, we combined the PLUS model and the ecosystem service equivalent factor method to calculate the ESV under multiple scenarios from 2020 to 2050. Results: From 1990 to 2020, the LULC of the PLB changed to varying degrees. The PLB has undergone a rapid process of landscape fragmentation, and the total ESV of the PLB has decreased. The total ESV was positively correlated with the CONTAG index and negatively correlated with the SHDI index. Between 2020 and 2050, the ESV of the PLB is projected to decrease under the NDS (nature development scenario) and EDS (economic development scenario) and increase under the EPS (ecological protection scenario). Conclusions: ESV responded to changes in landscape pattern. We recommend that the PLB should increase patch connectivity. Additionally, future development in the PLB should prioritize ecological protection to prevent further declines in ESV. [ABSTRACT FROM AUTHOR]

[Objective] To analyze the impact of land use changes on habitat quality in Jingzhou City from 1980 to 2018. [Method] Using methods such as landscape index, habitat quality index and geographic detector, the landscape index and habitat quality index were calculated to evaluate the level and change trend of habitat quality in Jingzhou City, and to explore the degree and direction of the impact of natural and socio-economic factors on habitat quality. [Result] The land use type of Jingzhou City had undergone obvious changes, mainly manifested as the rapid expansion of construction land and the substantial reduction of cultivated land, leading to the shortage of land resources and the deterioration of ecological environment. The changes of land use spread outward from the urban circle, more in the north than in the south and more in the east than in the west. The overall habitat quality in Jingzhou was high, but showed a decreasing trend, and the decline rate slowed down after 2010. The characteristics of habitat quality patches were fragmentation, diversification and uniformity. The overall habitat quality decreased from west to east. Affected by the nature of shoreline and reclamation, the habitat quality decreased significantly in the areas along rivers and lakes. The main factors affecting the distribution of habitat quality in Jingzhou City were the construction land area, elevation, night light brightness, soil type, slope, etc. The leading factors changed from elevation to construction land area. Natural factors determined the basic pattern of habitat quality, and the location and intensity of human activities lead to the change of habitat quality. [Conclusion] It is suggested that priority should be given to ecological restoration in areas along rivers and lakes where the quality of habitat has been reduced, control and standardize urban construction land, strengthen the construction of urban green space, and build sponge cities. [ABSTRACT FROM AUTHOR]

The study presents an analysis of changes in the landscape of the Ostrava-Karviná Mining District (in the Czech Republic) covering the period of more than 170 years. In the area of interest affected by underground coal mining, both areas affected by changes and land cover preserving areas were identified in the study. A detailed assessment of the landscape changes was enabled by using landscape metrics and indices, namely the development index and total landscape change index. The underlying data were obtained from maps of stable cadastre (from the year 1836) and aerial images of the years 1947, 1971, and 2009. Visual photointerpretation of aerial images and interpretation of the maps of stable cadastre made it possible to create land cover maps according to CORINE Land Cover categories. Obtained information on the representation of individual land cover categories were used to identify and to analyze changes in the landscape affected by hard coal mining. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ecology & Rural Environment is the property of Journal of Ecology & Rural Environment Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The present study employed remote sensing images of the Fen River Basin from 2005, 2010, 2015, and 2020 as the primary data source. The software ENVI, ArcGIS, and Fragstats 4.2 were utilized to measure the landscape pattern index of the Fen River Basin. A collinearity test was conducted to remove any redundant landscape pattern indices. Based on the selected landscape indices, the landscape pattern index values were ascertained as follows. Using the shifting window method, the landscape pattern index of the Fen River Basin was obtained. Second, the habitat quality in the Fen River Basin was assessed using the InVEST model, and the spatial autocorrelation approach was employed to confirm that the habitat quality was spatially autocorrelated. Finally, the spatial impacts of landscape pattern indices on habitat quality were examined using the MGWR model. The results show that (1) the Fen River Basin's overall habitat quality declined between 2005 and 2020; however, the deterioration slowed with time and had a typical "poor in the middle and high around the margins" spatial distribution. The habitat quality of the low-value area continued to increase, the habitat quality of the lower-value area decreased annually, the habitat quality of the middle-value area decreased and then increased, the habitat quality of the higher-quality area tended to increase, decrease, and then increase again, and the habitat quality of the high-quality area decreased annually. (2) The fit of the MGWR model was greater than those of the OLS and traditional GWR models, and it was able to more clearly illustrate the various roles that landscape pattern indices and habitat quality play in one another. (3) Changes in landscape patterns had a major impact on habitat quality; habitat quality was positively impacted by PD and AI, negatively impacted by MESH, and had positive and negative bidirectional effects from CONTAG and AI.

Determining an appropriate grain size is crucial in landscape pattern analysis and ecological research. In order gain deeper insights into the spatial diversity and dynamic characteristics of landscape pattern, based on the survey data of the 12 hm² large plot in Jiangxi Guanshan National Nature Reserve in 2015 and 2020, the grain size effect of landscape indices in eight different landscape types within the range of 5-50 meters were analyzed; the variation coefficients were used to reveal the changing characteristics of different landscape pattern indices as the grain size increased, and the optimal grain size was selected based on the inflection points of changes in various landscape indices. The results were as follows: (1) Based on the importance value analysis, eight different landscape types were identified in the arbor layer of the plot, including forest gap, bamboo forest, Cunninghamia lanceolata forest, Pinus massoniana forest, broad-leaved forest, bamboo and Cunninghamia lanceolata mixed forest, bamboo and Pinus massoniana mixed forest, Cunninghamia lanceolata and Pinus massoniana mixed forest. (2) The overall distribution of patches in the landscape was relatively balanced, and the distribution pattern remained relatively stable. At larger spatial grain size, the aggregation of each landscape type increased, leading to a higher probability of landscape merging. In contrast, at smaller granularity, there was a noticeable trend of fragmentation in landscape types, providing a more comprehensive display of the quantity, density, and shape of each landscape type. Patch density (PD), number of patches (NP), edge density (ED), landscape shape index (LSI), mean fractal dimension index (FRAC_MN), contagion index (CONTAG) exhibited significant negative correlations with increasing grain size, while mean patch area (AREA_MN), Shannon's diversity index (SHDI), Shannon's evenness index (SHEI) exhibited significant positive correlations with increasing grain size. (3) The coefficients of variation for landscape indices PD, NP, ED, LSI, and AREA_MN were the highest, combining landscape structural stability and diversity, the changes in different landscape indices were primarily concentrated around the inflection point at 5 meters. These results illustrate the diversity of landscape types, with the coefficient of variation reflecting the most sensitive characteristics of landscape pattern changes. This study suggests that a grain size of 5 meters is optimal for studying the landscape pattern of subtropical evergreen broad-leaved forests in Guanshan, Jiangxi. This study provides favorable evidence for the restoration of forest resources and stand stucture. [ABSTRACT FROM AUTHOR]

Since the 21st century, rice–crayfish fields have been widely distributed in the Yangtze River Basin in China. However, the spontaneous construction of these fields by farmers has given rise to the issue of rice–crayfish field fragmentation (RCFF) in certain areas. This study introduced a novel method for evaluating RCFF using township-level administrative regions as the evaluation units. Three key evaluation elements, including five landscape indices, were employed: area and edge metrics (rice–crayfish area ratio), shape metrics (perimeter–area ratio distribution), and aggregation metrics (rice–crayfish patch density, percentage of like adjacencies, and rice–crayfish contagion index). The RCFF was quantified and its spatial distribution pattern was analyzed through the entropy method and GIS spatial analysis. Empirical studies conducted in Qianjiang city yielded insightful results: (1) The contribution of evaluation elements to the RCFF was ranked in descending order as follows: aggregation metrics > shape metrics > area and edge metrics. (2) The RCFF of Yunlianghu farm was the lowest at 0.06, while the RCFF of Yangshi subdistrict 2 was the highest at 0.94. The spatial distribution of the RCFF exhibited a distinct trend, showing a gradual decrease from the northeast to the southwest in Qianjiang, and a low-RCFF area in the southwest. This evaluation system enables local government decisionmakers to comprehend the current status of rice–crayfish field management and construction. It facilitates the scientific planning of rice–crayfish field layouts and provides guidance for farmers in their expansion strategies. This method can be promoted in counties (cities) where rice–crayfish fields are primarily distributed in the Yangtze River Basin, promoting the transition of traditional agriculture to environmentally friendly agriculture in China. [ABSTRACT FROM AUTHOR]

The present study employed remote sensing images of the Fen River Basin from 2005, 2010, 2015, and 2020 as the primary data source. The software ENVI, ArcGIS, and Fragstats 4.2 were utilized to measure the landscape pattern index of the Fen River Basin. A collinearity test was conducted to remove any redundant landscape pattern indices. Based on the selected landscape indices, the landscape pattern index values were ascertained as follows. Using the shifting window method, the landscape pattern index of the Fen River Basin was obtained. Second, the habitat quality in the Fen River Basin was assessed using the InVEST model, and the spatial autocorrelation approach was employed to confirm that the habitat quality was spatially autocorrelated. Finally, the spatial impacts of landscape pattern indices on habitat quality were examined using the MGWR model. The results show that (1) the Fen River Basin's overall habitat quality declined between 2005 and 2020; however, the deterioration slowed with time and had a typical "poor in the middle and high around the margins" spatial distribution. The habitat quality of the low-value area continued to increase, the habitat quality of the lower-value area decreased annually, the habitat quality of the middle-value area decreased and then increased, the habitat quality of the higher-quality area tended to increase, decrease, and then increase again, and the habitat quality of the high-quality area decreased annually. (2) The fit of the MGWR model was greater than those of the OLS and traditional GWR models, and it was able to more clearly illustrate the various roles that landscape pattern indices and habitat quality play in one another. (3) Changes in landscape patterns had a major impact on habitat quality; habitat quality was positively impacted by PD and AI, negatively impacted by MESH, and had positive and negative bidirectional effects from CONTAG and AI. [ABSTRACT FROM AUTHOR]

Urban green space is the fundamental component of urban ecosystems, but the processes and mechanisms underlying the influence of green space structure and quality on human social and economic activities are still unclear. Plant diversity in the green space may have an impact on socioeconomic activities, which can be characterized by the spatial distribution of points of interest (POIs). To test this hypothesis, 16 green spaces on Xiamen Island were taken as the research object to analyze the relationships among five plant diversity indices, three landscape indices, and seven POIs of green spaces. Principal component analysis and the partial least-squares regression model were used to study the distribution of the seven types of POIs and the influence of green space on POI distribution. The results showed that the closer to the green space, the greater the weight of the principal components of medical institutions. The effects of green space on the seven POIs were represented with spatial relationships within the buffers. With the change in buffer gradient, there are influence trends such as the '∪' or '∩' type on various POIs. POIs are more impacted by the internal plant diversity index than by the landscape index of the green space. There was a scale effect of the diversity and landscape indices on the number of POI changes. The effect of the relationship between plant diversity and the spatial pattern of urban green spaces on socioeconomic activities is not direct but rather indirect. [ABSTRACT FROM AUTHOR]

Examining the Saihanba Mechanical Forest Farm, this study utilized Landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the Support Vector Machine (SVM) method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units. Employing landscape pattern indices and a method of spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. The results indicate that since 1987, there have been significant changes in land use types, especially in forest landscapes, their proportion increasing from 23.19% to 74.55%. In 1987, the proportion of high-risk areas was 72.30%, but in 2020, high-risk areas had significantly decreased and clustered in specific locations. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. After comprehensive exploration using a geographic detector, we found that landscape type, temperature, and vegetation coverage are the main risk factors. Among them, landscape type has the greatest impact on the landscape and works together with slope, aspect, and precipitation. In forest farm management, only the adaptation and adjustment of single factors are often paid attention to, while the compound effects of multiple factors are ignored. The results of this study bring important reference value to the operation and development of forest farms. [ABSTRACT FROM AUTHOR]

We explored the characteristics of landscape pattern (LP) changes in the Nandu River Basin (NRB) and its dynamic response mechanism to anthropogenic disturbance (AD). This is important for ecological protection and for land use decision-making in the basin in the context of the construction of a free trade port. Land use and land cover change (LULCC) data of 1990, 2000, 2010, and 2020 were analyzed with the help of the LP index, moving window method, hemeroby index, geo-information atlas, and geographic information system (GIS) spatial analysis to reveal the dynamic changes in LP characteristics in the NRB. Furthermore, this paper discusses into the correlation between LP and AD. The results indicate that over the past three decades, the NRB showed a staggered LP, dominated by forestland and cropland, whose total area has decreased by 25.27 km2 and 62.75 km2, respectively. On the other hand, the built-up land increased by 91.37%. The overall landscape fragmentation, landscape patch homogeneity, and landscape diversity have increased in the NRB. AD is the main reason for the dramatic changes in the LP of urban agglomerations centered in Haikou city. The area of minor disturbance (over 34%) occupies the largest proportion of the land, followed by higher (about 13~25%) and moderate disturbances (about 17~22%). The area of minor and strong disturbances has increased significantly, whereas those of moderate and higher disturbances have significantly decreased. The spatial distribution pattern of AD is gradually increasing from the southwest (natural landscape) to the northeast (human landscape). A transition in areas of low disturbance levels to higher levels is obvious. The area of the atlas that has transitioned from "minor → lighter disturbance (12)" and "higher → minor disturbance (41)" changed changed most significantly during 2000 to 2010 and from 2010 to 2020, occupying 26.79% and 11.99% of the transfer atlas, respectively. All regions encountering disturbances were significantly correlated with the largest patch index (LPI) from 1990 to 2020. The overall AD in the NRB has increased, especially in Haikou. Urbanization is the main factor for an increase in AD. The ecological and environmental management and monitoring in the basin need to be strengthened. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Blue-green infrastructure (BGI) plays a crucial role in regulating urban carbon cycles. Nonetheless, the spatiotemporal effect of BGI on carbon emissions has not received extensive attention. This study used the Yangtze River Delta (YRD) region as the study area and quantified the landscape patterns of BGI. Using a spatiotemporal geographically weighted regression model, we analyzed the impact of evolving spatiotemporal characteristics of BGI on carbon emissions. Additionally, we constructed a spatiotemporal weight matrix using the Moran index ratio to examine the spillover effects of BGI among different regions. Our results show that the aggregation effect of carbon emissions in the YRD region is gradually increasing while BGI has a dynamic impact on carbon emissions. In terms of spatial and temporal spillovers, under the influence of economic connections between regions, patch fragmentation and distance exert a persistent positive influence on carbon emissions, while shape complexity has a negative impact, with area and layout characteristics showing no significant effects. However, area and patch distance have a persistent positive influence on carbon emissions in adjacent areas, while shape complexity exhibits a negative impact. Therefore, optimizing urban BGI through a regional synergistic governance system is important to promote low-carbon urban development. [ABSTRACT FROM AUTHOR]

Climate change and human activities have brought greater risks to desertification of fragile desert steppe, as a result of which its landscape evolution has received attentions from many scholars. With the Landsat imaging data during 1990-2019 as the information source, the GIS spatial analysis and grid method were adopted to research temporal and spatial variation of landscape in Sonid Right Banner through calculating landscape index. The results are as follopws. (1) The grassland was the theme landscape in the researched area, where natural grassland landscape was as the dominant landscape. During 1990-2005, there was mainly a mutual transformation between natural grass landscape and the sandy and saline-alkali landscape; during 2005-2019, there was a considerable transformation of natural grassland into enclosed grassland landscape. (2) During 1990-2019, there was greater fragmentation of landscape, where the proportion of matrix landscape was constantly decreasing with more complex patches, increased abundance, enhanced heterogeneity and reduced aggregate contiguity. (3) During 1990-2005, the northern Hunshandak Sandland of the researched area suffered serious desertification with greater fragmentation. During 2005-2019, the dominance of matrix landscape of dry denuded high plain was decreased, with greater fragmentation of landscape and enhanced spatial heterogeneity which was substantially due to human activities. Except the southeast farming landscape, the southern low mountains and hills were constantly segmented, while the integrity and continuity of the entire southern landscape were maintained. The research result will provide scientific and reasonable references and basis for protection, utilization and management of resources and environment in Sonid Right Banner. [ABSTRACT FROM AUTHOR]

In recent years, Fenhe River Basin (FRB) wetlands have been facing severe challenges due to climate change and human activities. It was of great significance to understand the dynamic changes of FRB wetlands and their driving factors for ecological protection. Based on the land use data, runoff, rainfall and GDP data of FRB from 1980 to 2020, the evolution characteristics and driving factors of wetland pattern in FRB were analyzed. The results showed that the wetland types in FRB mainly included paddy, reservoir, river, beach and marsh. Among them, natural wetlands accounted for 72.46 %, and constructed wetlands accounted for 27.53 %. The main types of wetlands in FRB were river, reservoirs and beach, which account for 92.26 % of the whole wetland area. However, the dominant position of reservoir patch was more obvious than the others during 1980–2020. Landscape index showed that the shape of landscape tended to be regular and became more fragmentation. The transfer between wetlands and other land use types mainly occurred in the northern and southern parts of the FRB, and the main conversion types were occurred between dry land and wetlands, grassland and wetlands. Both natural and human factors drove the evolution pattern of wetlands, but the emphases were different. Runoff had a significant effect on wetland pattern at landscape level, while rainfall had a more significant effect on wetland evolution at class level. Urbanization rate and GDP had important effects on the evolution of wetland pattern at both class and landscape levels.

Urban landscape forms can be effective in reducing increasing PM2.5 concentrations due to urbanization in China, making it crucially important to accurately quantify the spatiotemporal impact of urban landscape forms on PM2.5 variations. Three landscape indices and six control variables were selected to assess these impacts in 362 Chinese cities during different time scales from 2001 to 2020, using a spatiotemporal geographically weighted regression model, random forest models and partial dependence plots. The results show that there are spatiotemporal differences in the impacts of landscape indices on PM2.5. the proportion of urban green infrastructure (PLAND-UGI) and the fractal dimension of urban green infrastructure (FRACT-UGI) exacerbate PM2.5 concentrations in the northwest, the proportion of impervious surfaces (PLAND-Impervious) mitigates air pollution in northwest and southwest China, and shannon’s diversity index (SHDI) has seasonal differences in the northwest. PLAND-UGI is the landscape index with the largest contribution (30%) and interpretable range. The relationship between FRACT and PM2.5 was more complex than for other landscape indices. The results of this study contribute to a deeper understanding of the spatial and temporal differences in the impact of urban landscape patterns on PM2.5, contributing to clean urban development and sustainable development.

This study considered Shilin World Geopark as the research object and constructed a landscape ecological risk assessment model based on the landscape pattern index by using remote sensing image data during five periods between 2000 and 2020. In addition, it analyzed the spatial and temporal changes of landscape ecological risk in the region. Spatial autocorrelation analysis was utilized to study spatial differences in the landscape ecological risk in the park. The results showed that during the study period, (1) cultivated land, forest land, and rocky desertification land were the main landscape types, different landscape types differed, and the area of rocky desertification land and building land increased by 37.47 km2 and 14.29 km2, respectively, while the area of cultivated land and grassland decreased significantly, with changes of 34.11 km2 and 18.67 km2; (2) landscape ecological risk of the park showed significant spatial differences, the 'highhigh' risk areas have been concentrated mainly in the central and northern parts of the park, the 'low-low' risk areas have been concentrated in the central part and the southwest-southeast area of the park; and (3) landscape ecological risk of the geopark has been increasing, with the degree of landscape ecological risk being spatially positively correlated. The results of the study are of great significance for maintaining ecosystem health of the Shilin World Geopark and optimizing the ecological risk management of the park. [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modeling and scenario analysis are the core elements of land use change research, and in the face of the increasingly serious ecological and environmental problems in urbanization, it is important to carry out land use simulation studies under different protection constraints for scientific planning and policy formulation. Taking Changchun City, the capital of Jilin Province, a pilot national eco-province, as an example, a CLUE-S model with coupled landscape ecological security patterns was constructed to predict and simulate the land use structure and layout under multi-objective optimization scenarios in the planning target year (2030), and the results were analyzed based on landscape index evaluation. The study found the following: (i) the proportion of ecological land area under low, medium, and high security levels in the study area was 8.7%, 64.8%, and 26.5%, respectively; (ii) under the current development trend scenario, the trend of increasing fragmentation of cultivated land patches in Changchun in 2030 will remain unchanged, with construction land spreading along the periphery in a compact and continuous pattern, while ecological land will be seriously encroached upon; and (iii) in the 2030 multi-objective optimization scenario, land use patches of all types will begin to show a tendency to cluster, with less landscape fragmentation and more connectivity, while cultivated land and construction land will also begin to converge and do not deteriorate as a result of spatial conflicts over ecological land. [ABSTRACT FROM AUTHOR]

The central Yunnan urban agglomeration represents a typical urban cluster in the southwestern region of China. The swift urbanization and land use changes in this region pose a severe threat to the ecosystem. A thorough assessment of the landscape ecological risk in the central Yunnan urban agglomeration holds paramount importance for devising effective risk management strategies and sustainable, high-quality development plans. This study utilizes long-term land-use raster data for six time periods (1995, 2000, 2005, 2010, 2015, and 2020) in the Central Yunnan urban agglomeration. Using GIS technology, a landscape risk index model is constructed, and a comprehensive assessment of landscape ecological risks in the Central Yunnan urban agglomeration is conducted using the 5 km × 5 km grid analysis method and Kriging interpolation. The results indicate that, between 1995 and 2020, the Central Yunnan urban agglomeration was dominated by forest land, grassland, and cultivated land as the primary land-use types. Forest land covered over 48% of the total area, while grassland and cultivated land accounted for more than 26% and 18%, respectively. Notably, construction land underwent a significant increase, mainly due to conversions from cultivated land, forest land, and grassland. Over a span of 25 years, the study area has experienced a continual rise in landscape ecological risk. The landscape ecological risk was mainly characterized by medium, higher, and high ecological risk. Grassland predominated in areas with medium levels of ecological risk, while cultivated land and construction land were predominant in regions with higher and high levels of ecological risk. Spatially, regions with lower ecological risk were primarily distributed in the Chuxiong Yi Autonomous Prefecture, whereas areas with higher and high levels of ecological risk were concentrated in Qujing City and Kunming City. The spatial aggregation patterns of landscape ecological risk in the Central Yunnan urban agglomeration featured "high–high" (H–H) and "low–low" (L–L) clusters, both displaying an initial increase followed by a decrease. The primary factors contributing to the rise in the landscape ecological risk index were identified as urban expansion, population growth, ecological fragmentation, and vegetation destruction. The study's outcomes can offer valuable insights for optimizing land resources and promoting sustainable development in the Central Yunnan urban agglomeration. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenyang Agricultural University is the property of Journal of Shenyang Agricultural University Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research aims to identify new landscape indicators assessing the physical characteristics and structure of the "slow cities" identified by the Slow City (Cittaslow) Movement. The movement currently includes about 300 (297 in 2023) cities from all around the world, and agrees to work on a set of goals/criteria. Although these criteria mostly highlight the unique values of the cities, they are not enough to provide an accurate evaluation of the space/land. This situation puts slow cities, once they receive the designation, in a redundant position to compete with large cities in terms of their recognition, and tourism potential, and as a result of this it poses a threat to the cities' original values. The paper proposes new criteria based on landscape indicators (critical parameters to evaluate the physical conditions of the landscape) to assess the spatial characteristics of nominated cities in Turkey, using comprehensive surveys. The surveys were conducted both in Turkey and the US states of Washington and Oregon, with samples of expert studies in the spatial planning area. According to the surveys' strengths in the statistical power test, the index value of landscape indicators was determined, when the relevant landscape indicators were reviewed. As a result, new criteria at two different scales (macro and micro) were proposed to be included in the assessment system of the Cittaslow Movement. [ABSTRACT FROM AUTHOR]

Riverine wetland is one of the important cityscapes along rivers, featuring powerful eco-hydrological regulations in safeguarding urban security and serving its quality. Over the past several decades, intensified climate change, together with the upgraded human activities, have deeply disturbed riverine wetland worldwide and caused variations in the amount and pattern, which might lead to negative effects on wetland ecosystem health (WEH), thus threaten the sustainability of the riverine urban agglomerations. To better understand the mechanism of the above effectiveness, the Riverine Urban Agglomerations along the Yellow River in China’s Ningxia Hui Autonomous Region (RUAN) was taken as an example in the present study. First, by establishing an object-oriented remote sensing image classification system based on Classification and Regression Tree (CART), riverine wetland distribution in years of 2000, 2009 and 2018 were determined for a two-Stage (ST-I: 2000–2009, ST-II: 2009–2018) comparative research. Second, the transition matrix and landscape index were used to measure the spatiotemporal dynamics of the riverine wetland in the two stages. Third, a Pressure-State-Response (P-S-R) model, together with its index system, was constructed to comprehensively assess the WEH in there. Results revealed that: (1) Wetlands in RUAN are dominated by the artificial ones, presenting an overall increase in area during the statistical period, varying with different trends in the two stages. Conversion between the wetlands and the non-wetlands were found frequent during the urbanization, leading to remarkable changes in wetland patterns in space. (2) Rivers are important and basic in forming riverine landscape in RUAN, the natural wetlands increased during the statistical period. In general, wetland patches and diversity increased, shapes of that became homogenized. Accordingly, the aggregation of wetlands decreased and the fragmentation of that worsened. (3) Riverine wetlands in most of RUAN experienced an increase of external pressure and a deterioration of state, showing an overall degradation. Meanwhile, the WEH was determined more by the fundamental state of itself, the external disturbance seemed function less. Above findings confirmed the vulnerability of riverine wetlands during urbanization in an arid circumstance. It is worthy of strengthening the protection of existing wetlands and minimizing or eliminating the conversion, to ensure the WEH and serve the sustainability of riverine urban agglomerations.

Since the 21st century, rice–crayfish fields have been widely distributed in the Yangtze River Basin in China. However, the spontaneous construction of these fields by farmers has given rise to the issue of rice–crayfish field fragmentation (RCFF) in certain areas. This study introduced a novel method for evaluating RCFF using township-level administrative regions as the evaluation units. Three key evaluation elements, including five landscape indices, were employed: area and edge metrics (rice–crayfish area ratio), shape metrics (perimeter–area ratio distribution), and aggregation metrics (rice–crayfish patch density, percentage of like adjacencies, and rice–crayfish contagion index). The RCFF was quantified and its spatial distribution pattern was analyzed through the entropy method and GIS spatial analysis. Empirical studies conducted in Qianjiang city yielded insightful results: (1) The contribution of evaluation elements to the RCFF was ranked in descending order as follows: aggregation metrics > shape metrics > area and edge metrics. (2) The RCFF of Yunlianghu farm was the lowest at 0.06, while the RCFF of Yangshi subdistrict 2 was the highest at 0.94. The spatial distribution of the RCFF exhibited a distinct trend, showing a gradual decrease from the northeast to the southwest in Qianjiang, and a low-RCFF area in the southwest. This evaluation system enables local government decisionmakers to comprehend the current status of rice–crayfish field management and construction. It facilitates the scientific planning of rice–crayfish field layouts and provides guidance for farmers in their expansion strategies. This method can be promoted in counties (cities) where rice–crayfish fields are primarily distributed in the Yangtze River Basin, promoting the transition of traditional agriculture to environmentally friendly agriculture in China.

This study considered Shilin World Geopark as the research object and constructed a landscape ecological risk assessment model based on the landscape pattern index by using remote sensing image data during five periods between 2000 and 2020. In addition, it analyzed the spatial and temporal changes of landscape ecological risk in the region. Spatial autocorrelation analysis was utilized to study spatial differences in the landscape ecological risk in the park. The results showed that during the study period, (1) cultivated land, forest land, and rocky desertification land were the main landscape types, different landscape types differed, and the area of rocky desertification land and building land increased by 37.47 km2 and 14.29 km2, respectively, while the area of cultivated land and grassland decreased significantly, with changes of 34.11 km2 and 18.67 km2; (2) landscape ecological risk of the park showed significant spatial differences, the ‘high–high’ risk areas have been concentrated mainly in the central and northern parts of the park, the ‘low–low’ risk areas have been concentrated in the central part and the southwest-southeast area of the park; and (3) landscape ecological risk of the geopark has been increasing, with the degree of landscape ecological risk being spatially positively correlated. The results of the study are of great significance for maintaining ecosystem health of the Shilin World Geopark and optimizing the ecological risk management of the park.

As the countryside continues to expand and develop, ecological issues are becoming increasingly complex and critical. The creation of environmental networks plays a vital role in ensuring ecological protection and promoting sustainable development in these areas. This study selects the Putian countryside as the focal area for research, utilizing remote sensing technology to collect pertinent data. By integrating geospatial analysis methods, we constructed a landscape ecological network. The methodology involved several key steps: employing a landscape index to delineate the spatial pattern of the rural landscape, evaluating the service function value of the established ecological network, and applying the Minimum Cumulative Resistance (MCR) model to formulate the security pattern of the network. This approach underscores the importance of structured ecological planning in rural development initiatives. The analysis found that among the four types of rural green landscapes in the study area, the regional green space occupies a dominant position, with an LSI value of 116.1734, mainly large patches with uneven spatial distribution, and based on the Putian Rural Minimum Cumulative Resistance Surface Model = 0.41*Land Use + 0.33*Slope + 0.26*Distance from Water Bodies, the Putian Rural Landscape Ecological Network with a nucleus, a belt, five axes, and multiple points has been formed. The research in this paper provides a reference basis for the development of the Putian countryside and helps revitalize the Putian countryside.

To provide the theoretical basis for regional land use and ecological environment protection, the spatial-temporal evolution and driving factors of land use landscape pattern in Yanan City were analyzed. Based on the three-phase land use data of Yanan City from 2000 to 2020, this paper analyzed the characteristics of land use and landscape temporal and spatial pattern change in Yanan City from the aspects of land use area change, area transfer characteristics, and landscape index, and analyzed the driving factors of the change. The results showed that:(1) From 2000 to 2020, the land use in Yanan City was dominated by forest land and grassland; the area of cultivated land, water area, and unused land were decreased; construction land continued to increase and changed the most. The increase of construction land was mainly distributed near the river and relatively flat areas. The main inflow types were cultivated land, forest land, and grassland. At the same time, mutual transformation was among cultivated land, forest land, and grassland. (2) The land use types were mainly concentrated in the range of 500-1500 m altitude and 5-25° slope. (3) Grassland was the dominant landscape type; the fragmentation degree of forest land and grassland was higher; the connectivity of construction land was enhanced and tended to be concentrated. On the whole, the irregular degree of patches increased, the heterogeneity of landscape increased, and the composition of landscape structure tended to be complicated. (4) Natural factors such as annual precipitation and elevation had great influence on the change of landscape pattern index, while the influence of land use and vegetation change dominated by human activities on the landscape pattern index was gradually increasing. [ABSTRACT FROM AUTHOR]

Ecological resilience is one of the most compelling issues in the current research field, which aims to explore how to address environmental challenges such as climate change, natural disasters and ecological risks. As the main carrier of ecological development, it is of great significance to improve the ecological resilience of river basin for regional green high quality development. From the perspective of spatial-temporal characteristics of landscape ecological resilience, the changing mechanism of ecological resilience level in Jinghe river basin was explored. Based on SWAT model, CASA model and InVEST model, the ecosystem services and trade-offs(EST)model evaluated the basin ecosystem services, and considered the landscape pattern characteristics; the basin ecological resilience assessment model was constructed and the spatial-temporal characteristics of ecological resilience in Jinghe river basin were revealed. The results show that from 2000 to 2020, the ecological resilience of all sub-basins in Jinghe river basin continues to increase. Compared with the situation in 2000, all sub-basins exceed the low resilience level in 2020, and 44.55% of the area in Jinghe river basin is transferred from the low resilience level, and 12.59% of the area is converted to the high resilience level. Ecological resilience is fluid and can have beneficial effects in other regions. The improvement of ecological resilience is based on the ecological resilience hotspots of Liupanshan and Ziwuling forest areas, radiating to the entire river basin. The ecological resilience pattern gradually decreases from the south to the north of the basin, and similar “high→low→high” pattern appears from the southern part of the basin to the east and west, and the ecological resilience level of the basin shows a significant upward trend. Although the southern part of the basin maintains high ecosystem services, it has low ecological stability due to the expansion of building land and unreasonable landscape structure. In general, the grain for green in Jinghe river basin in the past 20 years is beneficial to the improvement of ecosystem services and has a positive impact on the ecological resilience of the river basin. [ABSTRACT FROM AUTHOR]

To solve grid-scale problems and evaluation indicator selection in landscape ecological risk index (LERI) evaluation, this paper takes the Bailong River Basin in Gansu Province (BLRB) as an example. The LERI evaluation formulae and optimal grid scales were determined by screening landscape indices and area changes in the LERI at different grid scales. The evaluation indices were finally obtained according to the landscape characteristics and the correlation analysis of the landscape index value. Through the statistical analysis of the area of the LERI at the grid scale of 1–6 km, the optimal grid scale was determined to be 5 km. There was little change in land use patterns, with the most significant increases in artificial surfaces at 3.29% and 3.58%, respectively. Cultivated land was the only land use type to decrease by 184.3 km2. The LERI drops with the reduced cultivated land area; the landscape ecological medium risk area and cultivated land keep the same spatial distribution. Due to the limitation of the topography, cultivated land is generally distributed below 2500 m altitude, so 2500 m becomes the turning point in the spatial distribution of the LERI. The medium risk below 2500 m dominates the LERI type. Reduced cultivated land was the leading cause of reduced ecological risk according to an overlay analysis. The study of LERI evaluations provides a theoretical basis for sustainable and ecological environmental protection in the BLRB. [ABSTRACT FROM AUTHOR]

Watershed ecosystems are crucial to the overall sustainable development of a region, and a scientific and effective grasp of the characteristics of land-use change in a watershed, and the factors affecting land change, is an important prerequisite for the high-quality construction of watershed ecology, which needs to be emphasized. As the second largest inland river in the arid zone of Western China, the Heihe River Basin (HRB) has been affected by human and natural factors in recent years, and the ecological environment is relatively fragile, and there is an urgent need to analyze the ecological characteristics of the basin and to explore the relevant influencing factors in order to provide a basis for subsequent ecological management. Therefore, this article applies the landscape index, the landscape ecological risk index (ERI) model and the geodetector tools to analyze the land-use data from 2000 to 2020 in the Zhangye area of the HRB to study the characteristics of the ecological risk evolution and the driving forces affecting the ecological risk differentiation. The results show the following: (1) the area of the regional land-use change accounts for 4.99% of the total area, and the landscape pattern as a whole shows an increasing degree of fragmentation and a decreasing trend of aggregation; (2) the distribution of the ERI in the region shows a trend of being low in the center and high in the periphery, with an increase of 2.11% in the area of the lowest and lower risk and a decrease of 1.77% in the highest and higher, and the temporal change shows an increase followed by a significant decrease; (3) the human interference degree is the dominant factor influencing the spatial differentiation of the ERI in the basin area. There are significant differences between social factors, climate factors and land factors. [ABSTRACT FROM AUTHOR]

Land use change has serious impacts on the structure, function, and layout of the landscape pattern, which significantly affects ecosystem service values (ESVs). Based on land use data over a 10-year interval from 1980 to 2020, this study analyzed the evolution characteristics of ESVs and landscape ecological security in the Huaihe River Eco-Economic Belt using the equivalent factor method (EFM) and landscape pattern indices. The results show that the following: (1) The ESVs of the Huaihe River Eco-Economic Belt has increased by approximately 4% in the past 40 years, primarily characterized by increases in the values of services associated with the water environment (water supply, purifying environment, and hydrological regulation) and decreases in the values of services not associated with the water environment (food production, raw material production, gas conditioning, climate control, soil conservation, nutrient cycle maintenance, and biodiversity). (2) The landscape indices of landscape division index, edge density, marginal entropy, fractal dimension index, and Shannon's diversity index have shown increasing trends, and human activities in the study area are more widespread and fragmented. (3) Landscape fragmentation significantly reduced the values of non-water services, but the increase in the values of water-related services masked the impact of landscape fragmentation on the total ESVs. The EFM overestimated the ESVs of the water environment, such as hydrological regulation in areas with a large expansion of the water area, which may introduce uncertainties in the results. [ABSTRACT FROM AUTHOR]

The landscape pattern of the Black‐necked Crane (Grus nigricollis) habitat in China changed at different spatial scales and long‐term periods due to natural factors and human activities, and habitat reduction and fragmentation threatened the survival of Black‐necked Cranes. The factors driving the habitat landscape pattern and individual population changes of Black‐necked Cranes remain to be studied. In this paper, based on remote sensing data of land use from 1980 to 2020, the changes in landscape pattern and fragmentation of the Black‐necked Crane habitat in China over 40 years were analyzed from two different spatial scales using the land cover transfer matrix and landscape index. The correlation between landscape and Black‐necked Crane individual population was analyzed. The most obvious observations were as follows: (1) Although transformation between landscapes occurred to varying degrees, the area of wetlands and arable land in the breeding and the wintering areas (net) increased significantly from 1980 to 2020. (2) Habitat fragmentation existed in the breeding and the wintering area and was more obvious in the wintering area. (3) The number of individuals of Black‐necked Cranes increased period by period, and habitat fragmentation did not inhibit their population growth. (4) The number of individuals of Black‐necked Crane was closely related to the wetland and arable land. The increasing area of wetlands and arable and the increasing landscape shape complexity all contributed to the growth of the individual population. The results also suggested that the number of individuals of Black‐necked Crane was not threatened by the expanding arable land in China, and they might benefit from arable landscapes. The conservation of Black‐necked Cranes should focus on the relationship between individual Black‐necked Cranes and arable landscapes, and the conservation of other waterbirds should also focus on the relationship between individual waterbirds and other landscapes. [ABSTRACT FROM AUTHOR]

The protection system for urban historical and cultural heritage is well-established, while the safeguarding of rural cultural heritage lags behind. Consequently, the historical landscape space of the Great Wall village has been overlooked for an extended period. Drawing on the principles of landscape ecology, this study presents the "patch-corridor-matrix" model. By utilizing the Great Wall village in the Chicheng region as a case study, the historical landscape of the village is analyzed through three distinct structural levels: 'multi-type historical landscape patch', 'multi-type historical landscape corridor', and 'historical landscape matrix within the county'. In addition, a spatial quantitative model is created using the landscape index analysis approach, and the landscape index is utilized for analyzed the specific defensive qualities of the Great Wall village's historical landscape space. The optimization of the historic landscape space of the Great Wall villages is suggested for consideration in conjunction with the existing state of the landscape space along the Great Wall in the Chicheng area. From the three aspects of patches, corridor and matrix, spatial optimization thinking is carried out. For patch space, it is proposed to enhance the difference of patch space by improving the proportion of historical landscape patch space, emphasizing its historical and cultural connotation. For the corridor space, the cultural connotation of artificial, natural and sight corridors is explored and the physical space is improved, and the three corridor types are integrated to realize the win-win situation of rural development and historical landscape space protection. For the matrix space, the historical landscape network within the county is constructed to ensure the stable and dynamic development of the Great Wall village patches and corridor space and promote the harmonious coexistence of the Great Wall village economy and the historical landscape area. [ABSTRACT FROM AUTHOR]

The analysis of wetland patterns and their driving mechanisms is the research focus of discussion in wetland ecology. In this study, we tried to analyse the spatial differentiation patterns of community and landscape levels dominated by hydro‐ecological processes. The spatial differentiation patterns of landscape patterns and their driving mechanisms were explored in focus. This study was based on 30‐year land cover data of Baiyangdian Wetland Nature Reserve in North China Plain, China, constructing an ecological response relationship matrix between inundation frequency and vegetation cover frequency for the spatial divide at the community and landscape level. By constructing a landscape index set and analysing the index set using clustering, non‐metric multidimensional scale analysis, discriminant and redundancy analysis, we finally obtained the differentiation characteristics of wetland landscape patterns and their driving mechanisms. The spatial differentiation of community levels along the water level gradient showed a banded distribution pattern of submerged‐floating‐emerge to meadow shrubs, but the stability of the hydrological regime dominated the spatial differentiation of landscape levels. Wetland landscapes along the stability gradient of the hydrological regime were divided into stable and fluctuating zones. The stable zone had the landscape pattern characteristics of low fragmentation, simple and regular shape and high numbers of different patch types; the landscape pattern of the fluctuating zone was characterized by a high fragmentation and complex shape, with a small number of different patch types and a non‐uniform distribution. The analysis of the driving mechanism showed that the stability of the hydrological regime was the only reason for the formation of the landscape pattern of the stable zone. The combined effect of human‐dominated and natural‐supplemented effects jointly drove the formation of the landscape pattern of the fluctuating zone. The influence of human on the landscape pattern of the fluctuating zone showed a trend of spatial expansion from high areas to shallow water areas. The combination of traditional landscape indices and aquatic ecological processes characterized the spatial differentiation of wetland landscape patterns, and also verified the feasibility of this method. This study was a successful example of conducting ecological process‐oriented landscape level spatial differentiation analysis. The results of the study are intended to provide recommendations for the rational and effective use and precise conservation of wetland plant and animal resources and the restoration of wetland ecosystems. [ABSTRACT FROM AUTHOR]

The research aims to identify new landscape indicators assessing the physical characteristics and structure of the “slow cities” identified by the Slow City (Cittaslow) Movement. The movement currently includes about 300 (297 in 2023) cities from all around the world, and agrees to work on a set of goals/criteria. Although these criteria mostly highlight the unique values of the cities, they are not enough to provide an accurate evaluation of the space/land. This situation puts slow cities, once they receive the designation, in a redundant position to compete with large cities in terms of their recognition, and tourism potential, and as a result of this it poses a threat to the cities’ original values. The paper proposes new criteria based on landscape indicators (critical parameters to evaluate the physical conditions of the landscape) to assess the spatial characteristics of nominated cities in Turkey, using comprehensive surveys. The surveys were conducted both in Turkey and the US states of Washington and Oregon, with samples of expert studies in the spatial planning area. According to the surveys’ strengths in the statistical power test, the index value of landscape indicators was determined, when the relevant landscape indicators were reviewed. As a result, new criteria at two different scales (macro and micro) were proposed to be included in the assessment system of the Cittaslow Movement.

Shangri-La is located in the eastern part of the Qinghai-Tibet Plateau, which has a fragile ecology. The plateau grassland has suffered from irreversible degradation under the influence of human activities. To address this issue, the Sentinel-2A data obtained is used in this study to calculate the RVI and build an inversion model of grassland degradation grade with GDI data, which was used to obtain the area and proportion of grassland degradation. Landscape indexes were then calculated for different degradation grades of grassland to examine the correlation between roads and degraded grassland in spatial distance and the spatial distribution characteristics of different degradation grades of grassland. The results show that the grassland area in Shangri-La was 2207.94 km2, of which the heavily degraded area reaches 824.03 km2, exceeding the undegraded grassland area by 172.62 km2, indicating that the grassland degradation is severe. From south to north, the proportion of heavily degraded and moderately degraded grassland in townships gradually decreased, while the proportion of lightly degraded and undegraded grassland gradually increased. The townships with high percentages of degraded grassland were predominantly located in the southern area, where there was a dense road network and well-developed transport networks, particularly along National Highway 214, which is the main road in Shangri-La. Conversely, townships with low percentages are generally located in the north with dispersed roads and sparse transport lines. The study's outcomes are significant in providing a better understanding of the current status of grassland degradation and promoting the sustainable utilization of grassland resources in Shangri-La. [ABSTRACT FROM AUTHOR]

The spatial scaling of patterns and processes is a hot topic of research in landscape ecology, and different scales may yield completely inconsistent results. Therefore, to understand the impact of the scale effect on urban heat island effect, this study analyzes the correlation between surface temperature and landscape index at different spatial scales over Nanjing. The scale effect is calculated thorough curve fitting of the Pearson's correlation coefficient between ten landscape indices and land surface temperature at different window sizes, and the optimal one is determined. We have found that landscape indices can be divided into exponential and Gaussian landscape indices whose correlation with land surface temperature at different windows conforms to binomial exponential or multi-Gaussian functions, respectively. The optimal window size is approximately 4000–5100 m for exponential landscape indices, 1000–2000 m for aggregation index (AI) and percentage of like adjacencies (PLADJ), 6330 m for contagion (CONTAG) and 4380 m for total edge contrast index (TECI). Moreover, CONTAG and TECI have a high correlation coefficient plateau where the Pearson correlation coefficient is high and changes by less than 0.03 as the window size changes by more than 3000 m, which makes it possible to decrease the window size in order to save the calculation time without an obvious decrease in the Pearson correlation coefficient. To achieve this, we proposed a suitable window selection function so that the window size becomes 4260 m and 2070 m, respectively. The window sizes obtained in this study are just suitable in Nanjing, but the window sizes in other cities can also be obtained by the method in this study. This study provides a reference for future research on the relationship between landscape pattern and land surface temperature and its driving mechanisms, as well as for the impact of urban land use planning on the heat island effect. [ABSTRACT FROM AUTHOR]

Research on carbon emission is an important basis for solving global climate problems, and it is also one of the ways to quantitatively assess the impact of human activities. Cities are one of the main bearing spaces of human activities, and reasonable urban form is conducive to reducing energy consumption in human activities. This paper takes 50 clusters within Zhuhai, China, as the research object, quantifies the landscape spatial form index and social spatial form index of each cluster and establishes the index set of urban spatial form, so as to analyze the influence of different urban spatial form index on carbon emission. The main conclusions are as follows: (1) From the spatial distribution of each index, the urban cluster size and residential building area of each cluster in Zhuhai are generally large, and the distribution is basically consistent with that of densely populated areas. The urban clusters with high dominance are mainly located in the main urban area of Xiangzhou District, and the urban compactness, dispersion and industrial building area are generally high in the west and low in the east. (2) The size of urban clusters, industrial building area and residential building area have a strong promoting effect on carbon emission, while the compactness, dispersion and dominance of urban clusters have a strong inhibiting effect on carbon emission. (3) Based on the above conclusions, the low-carbon urban spatial form optimization strategy should be proposed from three aspects: urban development boundary control, promoting industrial structure transformation and compact urban development. [ABSTRACT FROM AUTHOR]

The accurate analysis of landscape pattern and ecological process characteristics in rapidly urbanized areas is crucial for formulating policies related to differentiated urban development and landscape management measures. However, there are no convincing set of overall indices suitable and the optimal scale in karst mountainous regions. This study determined optimal landscape indices and scales and analysed the temporal and spatial variation characteristics of landscape patterns in the karst mountainous city of central Guizhou Province by taking Guiyang City as a case study area using Principal component analysis and inflection point analysis. The results show that: (1) the nine landscape indices (i.e., edge density (ED), mean radius of gyration (GYRATE_MN), mean contiguity index (CONTIG_MN), mean shape index (SHAPE_MN), contagion index (CONTAG), interspersion and juxtaposition index (IJI), Shannon's diversity index (SHDI), proportion of urban area (UI), Gibbs-Martin diversity index(GM)) were optimal indices of landscape pattern analysis in karst mountainous cities, with optimal landscape grain and extent of 90 m and 1000 m, respectively; (2) from 1995 to 2019, the landscape pattern in karst mountainous region has changed dramatically under the impact of rapid urbanization, and urbanization and ecologization were main trends of landscape pattern changes; and (3) the landscape fragmentation was intensified with the regularity tendency of patch shape, which is still facing severe challenges to the protection of regional ecological environment. This study makes important contributions to exploring the response between landscape pattern changes and ecological processes and promoting ecological sustainable development in karst mountain cities.

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban landscape forms can be effective in reducing increasing PM2.5 concentrations due to urbanization in China, making it crucially important to accurately quantify the spatiotemporal impact of urban landscape forms on PM2.5 variations. Three landscape indices and six control variables were selected to assess these impacts in 362 Chinese cities during different time scales from 2001 to 2020, using a spatiotemporal geographically weighted regression model, random forest models and partial dependence plots. The results show that there are spatiotemporal differences in the impacts of landscape indices on PM2.5. the proportion of urban green infrastructure (PLAND-UGI) and the fractal dimension of urban green infrastructure (FRACT-UGI) exacerbate PM2.5 concentrations in the northwest, the proportion of impervious surfaces (PLAND-Impervious) mitigates air pollution in northwest and southwest China, and shannon's diversity index (SHDI) has seasonal differences in the northwest. PLAND-UGI is the landscape index with the largest contribution (30%) and interpretable range. The relationship between FRACT and PM2.5 was more complex than for other landscape indices. The results of this study contribute to a deeper understanding of the spatial and temporal differences in the impact of urban landscape patterns on PM2.5, contributing to clean urban development and sustainable development. [ABSTRACT FROM AUTHOR]

Ecosystem services (ES) can mitigate ecological risks (ER), yet these services can also be affected by ER. Based on land use data, socioeconomic data, landscape index, and spatial analysis techniques such as spatial autocorrelation, we study the spatial and temporal characteristics of ES and ER in the Yangtze River Delta from 2000 to 2019. The conclusions are as follows: (1) During the study period, construction land has been growing rapidly, and the depth, complexity, and intensity of land use have been increasing. The reserve land resources in the Yangtze River Delta are scarce. (2) From 2000 to 2019, the ecosystem service value (ESV) has been declining, with a total loss of 107.562 billion RMB. The area of low ESV continues to grow rapidly, while the area of high ESV continues to shrink. High ecological risk potential exists in rivers, lakes, and coastal areas. (3) Although the ecological environment in economically developed areas is more fragile, the ecological risk potential can be reduced in two ways: strengthening urban clusters, thus improving cooperation and communication among them; and protecting ecosystems with high ES such as water area and forestland. When formulating regional development plans, in addition to socioeconomic benefits, managers and policy makers need to focus on natural benefits as well. [ABSTRACT FROM AUTHOR]

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the 2000–2020 land cover data, the landscape dynamics and landscape pattern index are used to study the landscape pattern changes of the Yangtze River Delta. The results show that with the growth of built-in land area, the dominance of natural landscape in the Yangtze River Delta is gradually weakened. From the perspective of the overall landscape pattern, the degree of landscape fragmentation in this area is increasing, and the degree of landscape connectivity and aggregation are decreasing in varying degrees. The regional landscape is developing toward homogeneous distribution and increasing complexity. At the same time, from the perspective of classified landscape, the spatial distribution of various landscapes shows a strong correlation between climate and landform. Through comparative analysis, this study puts forward that the development of the Yangtze River Delta needs to pay attention to maintaining the integrity of the regional dominant landscape and paying attention to the diversity and connectivity of the natural landscape with high ecological service value. HIGHLIGHTS From the perspective of overall landscape pattern, this paper studies landscape fragmentation, connectivity, and aggregation.; The study found that the spatial distribution of various landscapes showed a strong correlation between climate and landform.; The study found that the change degree of landscape structure such as forest land and wetland with high ecological service value.;

Urban green spaces (UGS) significantly influence the distribution of surface heat and play a crucial role in regulating surface temperature. However, the quantitative relationship between UGS and surface temperature remains unclear, necessitating further research. This study aims to predict surface temperature based on green space information from GaoFen-2 satellite data. To achieve this, GaoFen-2 data were utilized to obtain spatial distribution and vegetation growth status in Urumqi, Xinjiang. Three machine learning models such as Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Regression Tree (GBRT) were constructed to predict surface temperature. Results indicated that UGS information extracted from GaoFen-2 data using the U-Net semantic segmentation model successfully predicted surface temperature. Among the three machine learning models, GBRT exhibited the highest predictive accuracy with an R adj 2 of 0.81, RMSE of 0.44, and RPD of 2.29, followed by RF (R adj 2 of 0.80, RMSE of 0.45, and RPD of 2.22), and SVM (R adj 2 of 0.79, RMSE of 0.47, and RPD of 2.15), In addition, a variable importance assessment reduced the original 44 variables to 28, maintaining predictive accuracy with the GBRT model achieving an R adj 2 of 0.81, RMSE of 0.43, and RPD of 2.3. Our study demonstrates the effectiveness of using vegetation information derived from GaoFen-2 to predict surface temperature. This approach provides valuable recommendations for the layout of UGS in urban areas and serves as a comprehensive reference for urban planning and real estate development. [Display omitted] • Using a semantic segmentation model on GF-2 data has yielded excellent results in extracting green space information. • Three machine learning models indicate that urban green space information can predict surface temperature quite effectively. • Streamlining green space feature information still ensures the accuracy of temperature predictions. [ABSTRACT FROM AUTHOR]

To solve grid-scale problems and evaluation indicator selection in landscape ecological risk index (LERI) evaluation, this paper takes the Bailong River Basin in Gansu Province (BLRB) as an example. The LERI evaluation formulae and optimal grid scales were determined by screening landscape indices and area changes in the LERI at different grid scales. The evaluation indices were finally obtained according to the landscape characteristics and the correlation analysis of the landscape index value. Through the statistical analysis of the area of the LERI at the grid scale of 1–6 km, the optimal grid scale was determined to be 5 km. There was little change in land use patterns, with the most significant increases in artificial surfaces at 3.29% and 3.58%, respectively. Cultivated land was the only land use type to decrease by 184.3 km2. The LERI drops with the reduced cultivated land area; the landscape ecological medium risk area and cultivated land keep the same spatial distribution. Due to the limitation of the topography, cultivated land is generally distributed below 2500 m altitude, so 2500 m becomes the turning point in the spatial distribution of the LERI. The medium risk below 2500 m dominates the LERI type. Reduced cultivated land was the leading cause of reduced ecological risk according to an overlay analysis. The study of LERI evaluations provides a theoretical basis for sustainable and ecological environmental protection in the BLRB.

Watershed ecosystems are crucial to the overall sustainable development of a region, and a scientific and effective grasp of the characteristics of land-use change in a watershed, and the factors affecting land change, is an important prerequisite for the high-quality construction of watershed ecology, which needs to be emphasized. As the second largest inland river in the arid zone of Western China, the Heihe River Basin (HRB) has been affected by human and natural factors in recent years, and the ecological environment is relatively fragile, and there is an urgent need to analyze the ecological characteristics of the basin and to explore the relevant influencing factors in order to provide a basis for subsequent ecological management. Therefore, this article applies the landscape index, the landscape ecological risk index (ERI) model and the geodetector tools to analyze the land-use data from 2000 to 2020 in the Zhangye area of the HRB to study the characteristics of the ecological risk evolution and the driving forces affecting the ecological risk differentiation. The results show the following: (1) the area of the regional land-use change accounts for 4.99% of the total area, and the landscape pattern as a whole shows an increasing degree of fragmentation and a decreasing trend of aggregation; (2) the distribution of the ERI in the region shows a trend of being low in the center and high in the periphery, with an increase of 2.11% in the area of the lowest and lower risk and a decrease of 1.77% in the highest and higher, and the temporal change shows an increase followed by a significant decrease; (3) the human interference degree is the dominant factor influencing the spatial differentiation of the ERI in the basin area. There are significant differences between social factors, climate factors and land factors.