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Despite the increasing volume of research exploring the impact of various characteristics of urban green spaces (UGS) on land surface temperature (LST), findings remain inconsistent, particularly in arid climatic zones. In this research, we examined UGS change and their temperature and analyzed the relationship between pertinent variables of vegetation biomass, area, and shape of green patches and LST in Karaj city, an Iranian semi-arid urban area in 2000 and 2020. Linear regressions were used to model the relationship between green patches' variables and LST. The results showed that vegetation biomass of green patches was more effective in reducing temperature in comparison with area and shape complexity. Moreover, larger patches with more vegetation biomass and higher shape complexity showed lower temperatures. These results can guide urban landscape optimization by providing a clear understanding of which factors contribute most significantly to temperature mitigation in arid and semi-arid urban areas. For instance, areas identified as green but thermally not significantly cold need to be prioritized for improvements such as planting denser vegetation or introducing more heat resilient species. [ABSTRACT FROM AUTHOR]

Context: Landscape metrics can effectively quantify urban landscape dynamics and their ecological stress, but incorrect metric, scale and zoning choices may lead to inaccurate result and biased land use planning. Objectives: This study aims to explore how the scale and zoning affected the magnitude and spatial pattern of ecological stress delineated by two related landscape metrics- Eco-erosion index(EEI) and percent of built-up area (PB). Methods: We quantified ecological stress from urban expansion using EEI and PB across different scales and zoning patterns, based on 30 m land use and land cover (LULC) data of Shanghai, China. Descriptive and non-parametric statistics were used to analyze the sensitivity and spatial heterogeneity of EEI and PB in response to variations in grain size, extent, and zoning. Results: Our findings indicate that EEI and PB are more sensitive to changes in extent than in grain size. EEI is better at capturing spatial heterogeneity of ecological stress in detail compared to PB at the same zoning pattern. Statistically, zoning patterns don't affect the ranking of ecological stress levels among study units. However, EEI using fine-scale zoning is more appropriate for highlighting discrepancies within the city than using broad-scale zoning at the same grain size. It is also recommended that the minimum study unit for EEI estimated with 30 m LULC grain size should be no smaller than a 5 km by 5 km grid cell. Conclusions: This study emphasizes scale and zoning effects on EEI and PB, providing guidance for using these metrics to represent ecological stress and contributing to sustainable urban planning. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Context: The spatial extent at which landscape variables most strongly influences wildlife populations (i.e., scale of effect) is of key importance to ecology and conservation. Many factors can influence scales of effect, but these relationships are poorly understood. In particular, the way scales of effect vary with different landscape metrics has not been extensively tested. Objectives: Our study tested whether metrics of landscape configuration have wider or narrower scales of effect than habitat composition. We also examined how species traits and landscape context influence the magnitude of differences in scales of effect between metrics. Methods: We calculated scales of effect for four metrics of habitat configuration and one metric of composition directly from species presence/absence data in online repositories including 102 species of forest mammals from 33 studies across the globe. We then compared the magnitudes and variability of scales of effect using Hedge's g. Results: Two metrics of configuration (flux and patch density) had significantly wider scales of effect than habitat composition, while the differences between the other two metrics of configuration and composition were not statistically significant. The magnitude of the difference between metrics varied among samples, but none of the factors tested explained this variability. Conclusions: For forest mammals, the scale of effect of a configuration metric can be expected to be 15–20% wider than a composition metric. However, this pattern may not hold for metrics of configuration that do not quantify attributes of the landscape that mediate species dispersal or that are correlated with the metric of composition. [ABSTRACT FROM AUTHOR]

At appropriate scales, optimizing landscape pattern in urban green spaces is shown to augment carbon sink. However, existing research primarily concentrates on regional or city-wide areas, often overlooking the nuanced effects of landscape pattern on carbon sink within specialized urban ecological function areas. Focusing on the city of Xi'an and emphasizing the forest within green spaces as the principal subject, this study investigated the spatial interplay between forest landscape pattern and carbon sink across the Ecological Control Area, the Urban Ecological Construction Buffer Area, and the Tsinling Mountains Ecological Protection Area. Grounded in field surveys, this study employed GF1-WFV remote sensing imagery to ascertain the 2021 land-use data in Xi'an and further classified forests into five distinct types: deciduous broad-leaved forest, evergreen coniferous forest, evergreen broad-leaved forest, coniferous and broad-leaved mixed forest, and evergreen-deciduous broad-leaved mixed forest. Employing the Carnegie-Ames-Stanford Approach model and landscape metrics methods, the study evaluated the carbon sink and landscape pattern at multi-scale. Through semi-variance analyses, we discerned the appropriate grid scales. Finally, multiple linear stepwise regression model elucidated the significant landscape metrics, while geographically weighted regression model were employed to scrutinize spatial relationships. Our findings suggested that grid scales of 5 km for the Ecological Control Area, 3 km for the Urban Ecological Construction Buffer Area, and 6 km for the Tsinling Mountains Ecological Protection Area are most appropriate for effective management and planning. Metrics related to area, edge, and fragmentation were pivotal in enhancing carbon sink, and their influence was spatially variable. This study furnished an in-depth analysis of how landscape pattern and carbon sink interact spatially within various urban ecological function areas at appropriate grid scales, thereby providing a scientific framework for the sustainable planning and management of green spaces.

The Japanese City Planning Act aims to control urban sprawl and promote compact urban development. Despite Japan's aging population, urban sprawl remains a concern in shrinking sprawl situations. This impacts ecosystem services owing to the loss of natural areas. Ecological quality is regarded as a basic parameter for preventing urban sprawl. This study examined urban sprawl, ecological quality, and their relationship in Chiba Prefecture within the spatial context of the metropolitan region. Utilizing Shannon entropy and landscape metrics for urban sprawling studies, the analysis revealed a gradual shift towards compact development at the center, while the urban periphery was unevenly distributed. The remote sensing ecological index (RSEI), supported by remote sensing, assesses ecological quality. Despite some limitations, the average RSEI indicated moderate quality, offering a suitable human environment. Pearson's calculations were used to determine the inverse correlation between urban sprawl and ecological quality. Chiba's slight increase in sprawl was attributed to the transition from non-compact to eco-city development. The proposed plans were formulated based on similar urban sprawl and RSEI patterns in other cities for further sustainable compact development. [ABSTRACT FROM AUTHOR]

Local landscape patterns in cities can substantially alter surrounding land surface temperature (LST) and affect the surface urban heat island effect. Previous studies have confirmed that some urban functional areas produce pronounced local heat/cold island effects in cities; however, the mitigating of this effect from the perspective of surrounding landscapes has not been investigated in depth. Additionally, different types of industrial plants have not been individually studied across multiple cities as major contributors to the local heat island effect. Therefore, based on 17 mega plants in various cities in the Northern Hemisphere, this study explores the impact of surrounding landscapes on the surface industrial heat island (SIHI) effect, proposes cooling metrics from a new landscape patch perspective, and quantifies the impact of different patch configurations on the SIHI using Extreme Gradient Boosting regression models and Shapley Additive exPlanations. The primary results are as follows: 1) Regarding to the footprint of the SIHI effect, the coverage of impervious surfaces dominates the ambient LST pattern. Industrial plant types and latitudes are moderately influencing factors. 2) In terms of the cooling effect, landscape patch size and width relative to industrial plant size has a pronounced impact on the LST cooling speed. Besides, various land cover types have distinct relative cooling thresholds for patch area and distance from the plants. The influence of patch attributes on LST cooling speed is determined by the distinct land cover type. 3) What is prominent is that the patches of water bodies with larger relative footprints often exhibit higher cooling speeds. This study aims to provide guidelines for urban planners in assessing the local thermal environment and mitigating further urban warming.

One of the most common climatic phenomena associated with urban issues is urban heat islands. Therefore, it is essential for urban planning to study this phenomenon. This article aims to investigate the performance of extraction methods for heat islands and introduce the prior method. Also, identify and analyze the landscape dynamics of heat islands over time in the study area. For this purpose, at first, the land surface temperature (LST) in the city of Birjand, was extracted using the satellite images in the years 2000-2019 in two cold and warm seasons using the mono-window, Planck's equation, radiative transfer equation, and single-channel method in the two seasons of summer and winter. The statistical method of mean absolute error was used for the comparison and selection of the accurate method. The results showed that the accuracy of the single-channel method (Landsat) was higher than other algorithms (MAE = 3.38 °C). The landscape dynamics were also identified using a package of landscape metrics, including PSSD, MPS, CA, NP, and MPFD. On the other hand, during the study period, the summer trend of the city's air quality showed an improvement in the condition of the land in the southern and eastern parts, and the winter trend showed an improvement in the condition of the land in the eastern to northern parts of the city. As a result, the phenomenon of urban heat islands in hot, dry weather causes a decrease in the temperature of the earth's surface with the increase of urban areas. [ABSTRACT FROM AUTHOR]

Mangrove forests, as an essential component of the coastal zones in tropical and subtropical areas, provide a wide range of goods and ecosystem services that play a vital role in ecology. Mangroves are globally threatened, disappearing, and degraded. Consequently, knowledge on mangroves distribution and change is important for effective conservation and making protection policies. Developing remote sensing data and classification methods have proven to be suitable tools for mapping mangrove forests over a regional scale. Here, we scrutinized and compared the performance of pixel-based and object-based methods under Support Vector Machine (SVM) and Random Forest (RF) algorithms in mapping a mangrove ecosystem into four main classes (Mangrove tree, mudflat, water, and sand spit) using resampled and fused Sentinel-2 images. Additionally, landscape metrics were used to identify the differences between spatial patterns obtained from different classification methods. Results showed that pixel-based classifications were influ-enced heavily by the effect of salt and pepper noise, whereas in object-based classifications, boundaries of land use land cover (LULC) polygons were smoother and visually more appealing. Object-based classifications, with an excellent level of kappa, distinguished mudflat and sand spit from each other and from mangrove better than the pixel-based classifications which obtained a fair-to-good level of kappa. RF and SVM performed differently under comparable circumstances. The results of landscape metrics comparison presented that the classification methods can be affected on quantifying area and size metrics. Although the results supported the idea that fused Sentinel images may provide better results in mangrove LULC classification, further research needs to develop and evaluate various image fusion approaches to make use of all Sentinel's fine resolution images. Our results on the mapping of mangrove ecosystems can contribute to the improvement of management and conservation strategies for these ecosystems being impacted by human activities. [ABSTRACT FROM AUTHOR]

The Japanese City Planning Act aims to control urban sprawl and promote compact urban development. Despite Japan’s aging population, urban sprawl remains a concern in shrinking sprawl situations. This impacts ecosystem services owing to the loss of natural areas. Ecological quality is regarded as a basic parameter for preventing urban sprawl. This study examined urban sprawl, ecological quality, and their relationship in Chiba Prefecture within the spatial context of the metropolitan region. Utilizing Shannon entropy and landscape metrics for urban sprawling studies, the analysis revealed a gradual shift towards compact development at the center, while the urban periphery was unevenly distributed. The remote sensing ecological index (RSEI), supported by remote sensing, assesses ecological quality. Despite some limitations, the average RSEI indicated moderate quality, offering a suitable human environment. Pearson’s calculations were used to determine the inverse correlation between urban sprawl and ecological quality. Chiba’s slight increase in sprawl was attributed to the transition from non-compact to eco-city development. The proposed plans were formulated based on similar urban sprawl and RSEI patterns in other cities for further sustainable compact development.

Landscape ecological risk assessment is a basic content of studying the relationship between landscape and ecosystem. It can reveal the spatial–temporal heterogeneity and scale effects of ecological risks, and provide the comprehensive spatial characterization and visualization of multisource risks. Yulin is a typical agropastoral zone in the north of China. Land use and land cover (LULC) changes are frequent and intense, and the landscape ecological environment is very fragile. This study analyzed the change characteristics of land use and land cover of Yulin by ArcGIS, assessed the landscape ecological risks using 4 landscape metrics, and discussed the spatial–temporal trends and the influencing factors for the landscape ecological risk. The results show that the absolutely dominant land use and land cover types in Yulin are grassland and cultivated land. The changes mainly happened in grassland, artificial surface, cultivated land, and bare land, with the variation of − 2.83%, 1.85%, 1.35%, and − 0.23%, respectively. High landscape ecological risks are mainly distributed in Yuyang and part of Jingbian. Most part of Yulin region belongs to the risk grade of Low/Medium and Medium. No statistically significant temporal trends of landscape ecological risk is observed. Variation of grassland, cultivated land, and bare land has more impacts on the landscape fragmentation than other land use and land cover. Risk grades of High and Medium/High mainly cover the lower normalized difference vegetation index (NDVI) region (0.1–0.4) at the edge of the Mu Us desert. The relationship between the landscape ecological risk and the NDVI reveals that the extent, continuity, pattern, and the type of vegetation cover are influencing factors for the landscape ecological risk from the view of the local habitats. The study results may be helpful for the vegetation restoration, land use planning, and sustainable development of the Yulin and other similar regions. [ABSTRACT FROM AUTHOR]

Mangrove forests distributed along the coast of southern Iran are an important resource and a vital habitat for species communities and the local people. In this study, accurate mapping and spatiotemporal change detection were conducted on Iran's mangroves for three decades, using the Landsat imagery available for the years 1990, 2000, 2010, and 2020. Four general vegetation indices and eight mangrove-specific indices were employed for mangrove mapping in three study sites. Additionally, six important landscape metrics were implemented to quantify the spatiotemporal alteration of the mangrove forests during the study period. Our results showed the robustness of the submerged mangrove recognition index (SMRI), validated as the most effective index (F1-score ≥ 0.89), which was used for mangrove identification within all nine sites. The mangrove area of southern Iran was estimated at approximately 13,000 ha in 2020, with an overall increase of 2313 ha over the whole period. A similar trend could be observed for both the landscape connectivity and complexity. Our results revealed that a stronger connectivity and higher complexity could be detected in most sites, while there was increased fragmentation and a weaker connection in some locations. This study provides an accurate map of Iran's mangrove forests over time and space. [ABSTRACT FROM AUTHOR]

In this study, we investigate the urban landscape patterns in Wuhan, China based on the land use data in the vector format. Using the approach of landscape metric analysis, we calculate forty-four vector-based landscape metrics and then reduce redundant ones through a combination of Spearman correlation analysis and factor analysis, in order to extract a core set of characterizing landscape metrics. We find that the urban landscape can be depicted by six factors including the overall shape and diversity, mean proximity, overall area variation, fragmentation variation, elongation variation, and mean shape complexity. After analyzing typical patterns indicated by the core metrics and the spatial distribution of land use patterns, we compare our findings with other studies and discuss how the core metrics coincide and differ. [ABSTRACT FROM AUTHOR]

Peri-urban areas constitute an enormous resource in terms of natural capital, landscape heritage and economic activities, but, at the same time, they are often affected by physical and socio-economic degradation, drawing the attention of decision makers and planners. Many studies have focused on these contexts both in terms of suburbs, with a close dependence on urban centers, and new land typologies. The present paper focuses on documentary evidence of the direct impacts of urban growth on rural lands. The study area entails the Vesuvius National Park, which, belonging the Naples metropolis, is well-known for its historical, geo-morphologic and naturalistic value. Furthermore, the area has a history of high-quality cartographic production: the 1817, 1907, 1960, 2009 time steps maps were digitized, georeferenced, vectorized and compared in a GIS environment. The results highlight a strong change in land-use, in vineyards and urban class types, with a more disaggregated landscape mosaic. The approach shows that the historical modeling of land-use changes supports the understanding of current land-use dynamics and landscape patterns. The study also shows the need to integrate landscape planning and landscape ecology approaches, highlighting the close interactions between urban, agricultural and natural areas, for the purpose of supporting decision makers in land-use management and conservation policies. [ABSTRACT FROM AUTHOR]

Some human activities have caused a decrease in coverage in the Vanguardia Reserve and changes in the diversity and structure of the vegetation. The objective of the study was to compare the diversity and structure of vegetation, relating habitat variables with landscape metrics. Vegetation was sampled in five sectors; in each sector 3 plots of 50 x 2 m were established, except in Ocarros where 4 plots were evaluated. In each plot, all trees and shrubs with diameter at breast high DBH ≥ 1.0 cm were censored. An ANOVA was performed to compare the structure and diversity between plots. A floristic similarity dendrogram was developed using the Bray-Curtis index. Pearson correlations were calculated between habitat variables and landscape metrics using PAST. No significant differences in diversity and abundance were found between the compared plots. DBH averages and coverage showed statistical differences between some plots. The richness of trees, shrubs and total abundance was positively correlated with the distance to the roadways. The diversity was negatively correlated with the distance to the mature forest fragment. The differences in coverage and DAP suggest that the reserve is facing different degrees of disturbance, causing variation in ecological attributes. The positive correlations between some vegetation variables and landscape metrics indicate that the roads influence the structure and diversity of the vegetation. [ABSTRACT FROM AUTHOR]

Context: To analyze the scales at which landscape structure influences ecological processes, two approaches with different underlying ecological assumptions exist; the usual threshold method and the weighted-distance method. Objectives: We used abundance of species to test if the combination of weighted-distance and threshold approaches improves the explained variance of landscape metrics. Methods: We developed a workflow using the two approaches to calculate metrics computed at multiple scales. The latter was developed using weighted metrics based on different weighted-distance functions, and one metric could be selected for more than one spatial scale. Then, we tested the explained variance of species distribution (the activity-density of Abax parallelepipedus) by these two approaches applied independently and then together in modeling a specific ecological response. Results: The combination of metrics computed at multiple scales calculated by both weighted-distance and threshold method improved the predictive performance of the models. More precisely, adding metrics derived from the weighted-distance method to the threshold method significantly increased the explained variance when using the same environmental variables. The mean R2 values of the selected model for the threshold method was 0.34 ± 0.10, 0.49 ± 0.11 with the weighted-distance method, and reached 0.71 ± 0.07 with the two methods combined. These results demonstrate the importance of combining metrics using the weighted-distance method and the threshold method. In addition, activity-density was better explained by metrics selected at multiple scales. Conclusions: This study highlights the importance of combining threshold and weighted-distance method at several scales to improve the explanation of ecological responses based on species abundance. [ABSTRACT FROM AUTHOR]

Coastal wetlands are critical ecosystems that are under intense pressure due to anthropogenic activities. In addition to urban growth and agriculture, shrimp farming has become one of the main drivers behind the loss of tropical and subtropical coastal wetlands. Despite its socio-economic importance, shrimp farming has high environmental costs worldwide. Consequently, monitoring shrimp farming at regional and local scales is essential to determine if the resulting pressure on coastal wetlands is increasing. We analyzed land use/land cover (LULC) in the Bahía Santa Maria-La Reforma (BSMR) lagoon system in northwestern Mexico using remote sensing data to determine landscape and surface cover changes. We also projected future scenarios based on stochastic models and evaluated landscape metrics considering the effects of shrimp farming. Four LULC thematic maps (1985, 1994, 2002, and 2017) with overall accuracy values > 80% and two projected maps (2027 and 2037) were produced. Agriculture was the dominant LULC class in the BSMR coastal lagoon system, although saltmarshes appear to be the most critical wetland type in the area. Shrimp farming, which was nonexistent in 1985, represented 4% of the total landscape in 2017. By 2037, this value is expected to increase to 5%. Saltmarshes showed negative trends due to the expansion of shrimp farming. Considering the importance of wetlands given their ecosystem services, this study highlights LULC changes due to economic activities and the need to improve management strategies to protect the wetlands of the BSMR coastal lagoon system. • LULCC was evaluated via post-classification comparison analysis. • The use of multidate images reduced biases derived from phrenological shifts. • Future scenarios were predicted with stochastic and artificial neural network models. • Saltmarshes are the most critically threatened wetland type in the study area. • Shrimp farming is the main driver of coastal wetland loss and fragmentation. [ABSTRACT FROM AUTHOR]

Land-use change and habitat fragmentation are well-known to affect host-parasitoid interactions. However, the study of the effects of landscape composition, as a result of habitat fragmentation, on host-parasitoid food webs is still limited especially in a tropical agricultural landscape. This research was aimed to study the effect of agricultural landscape composition on the structure of host-parasitoid food webs. Field research was conducted in sixteen long-bean fields located in Bogor Regency, West Java, Indonesia. In each long-bean field, sampling of insect pests and their parasitoids was carried out using direct observation within a plot size of 25 m × 50 m. The collected insects were brought to the laboratory for rearing and observed for emerging parasitoids. Landscape composition of each long-bean field was measured by digitizing the whole patch within a radius of 500 m from the long-bean field as a center of landscape, and landscape parameters were then quantified by focusing on number of patches and class area of both semi-natural habitats and crop fields. In total, we found 51 morphospecies of insect pests and 110 morphospecies of associated parasitoids from all research locations. Lepidopteran pests are the most abundant and species-rich with 35 morphospecies and with 76 morphospecies of parasitoids. Based on the generalized linear models, landscape composition especially class area of natural habitat and crop field showed a positive relationship with host-parasitoid food-web structure especially on connectance and compartment diversity. In conclusion, landscape composition contributes to shaping the host-parasitoid food-webs in a tropical agricultural landscape.

Urbanization has led to the rapid and large-scale changes in land use and land cover and has affected the spatial distribution of land surface temperature (LST) in urban areas. Studying the LST pattern and their spatial heterogeneity characteristics at different scales can help understand the dynamic mechanism of the thermal landscape and provide insights into urban ecological planning. We utilized transfer matrixes, landscape metrics, and spatial autocorrelation analyses to study the transfer of LST classes, changes in the LST pattern, and changes in LST clusters with varying grain sizes by taking the central urban districts of Hangzhou City in China as a case study. Results indicate that (1) the transfer proportion of the LST classes increased, except for high-temperature class, and each LST class shifted to the adjacent dominant LST class with the increase in grain size. (2) The landscape metrics remarkably changed as the grain size increased, indicating that the LST pattern was scale-dependent. As the grain size increased, the small patches gradually merged into large patches; the fragmentation, complexity, and ductility of the urban thermal landscapes decreased; and the shape of the patches became simple and regular. (3) The LST pattern exhibited a positive spatial autocorrelation. The area of low–low cluster decreased, whereas that of non-significant clusters substantially increased with the grain size. The area of high–high cluster remained steady when the grain size exceeded 90 m. (4) Patch density, mean patch fractal dimension, clumpiness index, and contagion index exhibited predictable responses to changing grain size, whereas Shannon's diversity and Shannon's evenness indexes showed erratic responses, indicating that the diversity and evenness of the LST pattern were not scale-dependent. (5) The suitable domain of scale for the analysis of LST pattern was (60, 120), and the optimal grain size was 120 m. The selection of domains of scale and optimal grain size need to be determined according to the changes in thermal landscape patterns at different grain sizes and regional environments. [ABSTRACT FROM AUTHOR]

During the last two decades, a wide range of geographical tools including the calculation of landscape metrics were transposed to ecological studies to build models for land-use dynamics. Currently, few studies have evaluated the biases which can occur during the rasterization step which could influence the results. The purpose of this study was to evaluate the influence of dataset rasterization on area and perimeter variables, which are frequently used to calculate landscape indices, according to (i) the rasterization cell size and (ii) the shape of geographic features. The Urban Atlas 2006 dataset focused on Bas-Rhin department (France) was used as a vector reference layer. Rasterization was performed for various cell sizes to evaluate the influence of spatial resolution on the errors injected into shape descriptors. Five morphological metrics were calculated for all geographic features. For the first time, a UMAP algorithm was performed to relate the rasterization relative errors at all spatial resolutions with morphological attributes. Results showed that low values of area errors were obtained for cell sizes lower than 5 m (10%) with an overestimation tendency. For cell sizes greater to 10 m, overestimations and underestimations were occurring according to the shape of geographic features. This study showed that sensitivity analyses must be performed before any study carried out on landscape changes estimation to define the best raster cell size as function to the morphological attributes of the geographic features, the predefined error threshold.

Soil erosion threatens environmental sustainability worldwide. Exploring the trajectories of soil erosion and associated drivers is of great significance for combating land degradation. This study selected the highly eroded Loess Plateau (LP) and Karst Plateau (KP) as contrasting regions to monitor soil erosion dynamics. Monitoring was performed by applying the Revised Universal Soil Loss Equation based on a GIS platform and multi-source input data to investigate associated drivers. The results established that soil erosion in both regions was substantially reduced by ecological restoration projects and significant land use/cover conversions. Landscape and geomorphological variables were found to be the dominant factors controlling soil erosion in the LP and KP, as they influenced land use patches and geomorphological patterns, respectively. The correlations between fragmentation metric indices and soil erosion indicated that the appropriately intensive fragmentation in the LP could mitigate or prevent soil erosion by disturbing its formation and transportation and ultimately positively influenced soil erosion control. Geomorphological patterns were also determinative factors, particularly for the KP, where almost all geomorphological variables were significantly correlated with the erosion modulus. Owing to the peculiar landform and landscape conditions in karst areas and loess hilly–gully areas, geomorphological and landscape variables should be considered when determining the main factors affecting soil erosion processes and integrated into the forecasting model to improve the accuracy of the simulation. The findings of this study are expected to (i) improve the efficacy of soil erosion control and (ii) promote the sustainable planning and management of land and soil resources. [ABSTRACT FROM AUTHOR]

In Côte d'Ivoire, the political-military crisis from 2002 to 2011 caused an intensification of human pressure on certain protected areas. This increased pressure has led to significant deforestation in the Mont Péko national Park. However, the impact of disturbances on the forest cover structure of this park is little known. The purpose of this study was to document the impact of the crisis on the fragmentation of the forest cover of Mont Péko national Park in order to contribute to its rehabilitation. Thus, the structural dynamics of the landscape were analyzed using metrics of landscape ecology derived from four thematic digital maps from Landsat satellite imagery, throughout the periods before, during and after the crisis. Analysis of landscape spatial transformation processes between 1988 and 2016 showed a growing trend in forest cover fragmentation. Statistics on selected landscape metrics were produced to quantify the structural changes resulting from this fragmentation. Analysis of landscape metrics showed a significant increase in the level of fragmentation of forest cover during and after the period of crisis. The overall structural dynamics of the landscape of the Mont Péko national Park during the periods studied reveals a fragmentation of the forest at the expense of the creation of cocoa plantations. There is therefore an urgent need to strengthen the supervisory capacity of managers in order to eradicate the scourge of cocoa cultivation in the Mont Péko national Park.

Peri-urban areas constitute an enormous resource in terms of natural capital, landscape heritage and economic activities, but, at the same time, they are often affected by physical and socio-economic degradation, drawing the attention of decision makers and planners. Many studies have focused on these contexts both in terms of suburbs, with a close dependence on urban centers, and new land typologies. The present paper focuses on documentary evidence of the direct impacts of urban growth on rural lands. The study area entails the Vesuvius National Park, which, belonging the Naples metropolis, is well-known for its historical, geo-morphologic and naturalistic value. Furthermore, the area has a history of high-quality cartographic production: the 1817, 1907, 1960, 2009 time steps maps were digitized, georeferenced, vectorized and compared in a GIS environment. The results highlight a strong change in land-use, in vineyards and urban class types, with a more disaggregated landscape mosaic. The approach shows that the historical modeling of land-use changes supports the understanding of current land-use dynamics and landscape patterns. The study also shows the need to integrate landscape planning and landscape ecology approaches, highlighting the close interactions between urban, agricultural and natural areas, for the purpose of supporting decision makers in land-use management and conservation policies.

The continuous expansion of urban land has led to massive encroachment upon cropland. To examine the impacts of urban expansion on the loss and fragmentation of cropland in China’s nine major grain production areas (MGPAs), we used standard deviation ellipse, land use transfer matrix, land use dynamic degree, and landscape metric to explore the spatio-temporal evolutions, mutual transfer, and landscape patterns of cropland and urban land. The results show the following: (1) From 1995 to 2018, the areas of cropland in MGPAs showed a trend of “short-term increase—long-term decrease—short-term increase”, while that of urban land grew continuously; (2) Urban expansion is the main cause of cropland loss. The cropland area converted to urban land accounts for a large proportion (49.26%) of the total transfer of cropland to other land types, especially in the densely populated, rapidly urbanizing and industrializing Taihu Lake Plain, Jianghuai Region, and Pearl River Delta; (3) In most MGPAs, urban expansion has led to fragmentation of cropland, especially in the Pearl River Delta, as indicated by the significant change of patch density. However, in the Sanjiang Plain and Songnen Plain, a less pronounced or even reduced cropland fragmentation was observed due to the significant conversion of other land types to cropland under specific land policies. From these results, we suggest that the government should regulate the encroachment of urban land on cropland and the transfer of natural land to it, and encourage the rural land consolidation to increase the cropland.

Linking landscape patterns to specific ecological processes has been and will continue to be the key topic in landscape ecology. However, this goal is difficult to achieve by using the traditional landscape metric based on the Patch-Mosaic Model (PMM), as they don't integrate ecological processes with landscape patterns. In this paper, we proposed a conceptual model, i.e., the Source-Pathway-Sink Model (SPSM), which designates the role of a landscape unit into "source", "sink", or "pathway" based on specific ecological processes during the landscape pattern analysis. While the traditional landscape metrics derived from the PMM model is visual- or geometrical-oriented and lack of linkage to ecological significance, the SPSM model is process-oriented, dynamic, and scale dependent. A comparison between the PMM and the SPSM models shows that the SPSM model is complementary to the PMM model, and can provide a simple and dynamic perspective on landscape pattern analysis. The SPSM model may represent a conceptual innovation in landscape ecology. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to an increase in urban land surface temperature (LST). In contrast to individual cities or megacity scale, urban agglomeration can increase LST in a continuous area due to decreasing or disappearing distance between cities. Thus, the impact of ISA on LST needs further understanding in the large scale of urban agglomerations. This study investigated the impacts of impervious surface area (ISA) on LST in urban agglomeration region. The distribution of ISA and LST of the Greater Pearl River Delta in 2015 was extracted using the Landsat 8 OLI and Aqua MODIS images. Next, the standard deviational ellipse methods were used to systematically analyze the spatial correlation of ISA and LST. Subsequently, the influences of ISA density and landscape pattern of ISA on LST were analyzed by various methods. The results showed that when the ISA density increased 10%, the daytime LST increased 0.46 °C at the density level lower than 70% and 0.55 °C at the density level higher than 70%, respectively. Likewise, when the ISA density increased 10%, the nighttime LST increased 0.285 °C at the density level lower than 70% and 0.39 °C at the density level higher than 70%, respectively. In addition, the results of correlation analysis indicated that landscape metrics of ISA and the density of ISA had significant correlation with the LST. However, the correlation was higher at daytime than at nighttime, due to the large terrain, complex environment and diverse surface cover types in the study area. [ABSTRACT FROM AUTHOR]

Highlights • Focus on eco-landscapes comparison and analysis among metropolitan inner cities. • Explored an effective urban mapping method based on Sentinle-2 and Google Earth images. • London appears to achieve the best eco-landscape induced ecological quality. • Result shows all inner cities have high landscape consistency. Abstract With increasing attention being paid to sustainable urban development and human habitation improvement, urban ecological land cover (UELC), i.e., surface water and green space, has played an important role of the highly compact inner urban regions. In this study, we developed an efficient approach for UELC mapping by coupling Sentinel-2 multi-spectral imagery and Google Earth high-resolution imagery. In contrast with the conventional single-source and multi-source imagery-based classification methods, the proposed method respectively achieved the highest overall accuracies of 91.50% and 94.05% in the UELC mapping for two test sites (i.e. Shanghai and Seoul). The proposed method is used for urban surface mapping among six world-class cities. For an in-depth analysis of the landscape structures for inner urban regions, seven landscape metrics are introduced for the quantification of the UELC structure based on the obtained high-precision UELC maps. The result shows that London appears to have the best UELC-induced ecological quality, that is, with high percentage of landscape, area-weighted mean fractal dimension, edge density, Shannon's evenness index values and a low contagion index value, while Tokyo is exactly the opposite. Several common characteristics found through the statistical analysis are: 1) all the inner-city regions have small UELC coverage (< 50%) and low shape complexity; 2) green space generally contributes more to urban eco-environment than the urban surface water; and 3) all cities show high landscape consistency in the inner urban region. [ABSTRACT FROM AUTHOR]

The water quality of headwater streams is a worldwide concern because of their critical roles in supplying clean water for drinking and other consumptive uses. Here, we evaluate temporal trends and spatial dynamics of the permanganate index (COD), ammonia-nitrogen (AN), and total phosphorus (TP) for 31 sites in headwater watersheds of the Huai River Basin, China. The seasonal Mann-Kendall test and correlation and variance analyses were applied to long-term time series (2003-2010) of water quality data in order to investigate the patterns of water quality trends, as well as their linkages with the watershed landscape. The results indicated that (1) more than 1/3 of headwater monitoring sites have exhibited either significantly increasing or decreasing trends in COD, AN and TP, while only TP increased for most them; (2) obvious increasing concentration gradients were observed for all water quality parameters along the upstream to the downstream continuum. Such spatial patterns can be highly explained by land cover and landscape configuration metrics. The percent of urban land and urban-related landscape metrics (such as the Landscape Division Index) were the primary explanatory variables for AN, while the aggregation metrics of cropland and urban land cover were the main predictors of COD and TP; (3) historical dynamics of COD, AN, and TP were influenced by land cover transitions. The trends of COD and TP may be attributable to the change in the wetland landscape, while the trends of AN were likely related to changes in forestland area as well as environmental management. Overall, our study determined the spatial and temporal dynamics of water quality parameters in the headwater watersheds and interpreted the possible reasons behind their spatio-temporal dynamics, which can have important implications for sustainable landscape planning as well as headwater watershed management. [ABSTRACT FROM AUTHOR]

Abstract Landscape metrics are often used to model nonpoint source pollution from agricultural and urban surface runoff. By considering topography and the spatial arrangement of land cover, landscape metrics can better account for hydrologic connectivity, loading quantity, and vegetated buffer filtering between nutrient loading sources and streams. For this study we develop a surface runoff nutrient loading metric that considers source (i.e. cropland or developed) loading and buffer filtering along hydrologic transport vectors, or flow paths. We use General Additive Modeling to evaluate the relationship between this metric and in-stream nitrogen (N) and phosphorus (P) concentrations in the Saginaw Bay watershed in Michigan, US and compare the relative predictive power between this metric and other landscape metrics that do not consider hydrologic connectivity. The flow path-based cropland loading metric was a stronger predictor of in-stream NO 3 concentrations than alternative metrics. In-stream P concentrations were best predicted by models that included 48-h antecedent precipitation and catchment-wide proportion of developed landcover. Metric maps reveal high nutrient loading areas where only a small proportion of loading reaches streams via surface runoff, highlighting the need to consider nutrient loading via drainage tiles and other subsurface pathways in efforts to quantify nonpoint source loading to surface waters. The flow path-based loading metric is represented spatially as a gridded dataset showing estimates of nutrient loading adjacent to streams, and with higher resolution stream delineation data it could be used by land managers to target locations for precision buffer placement to intercept surface runoff and reduce nutrient loading. [ABSTRACT FROM AUTHOR]

Particulate matter in the airborne environment is one of the top environmental concerns, as well as reasons of deaths and diverse diseases. Urban green infrastructure can improve the air quality by mitigating particulate matters from airborne environment and provide high spatial monitoring of particles by means of leaf particles as indicators. Three common species in Beijing (ailanthus, ash, and willow) were chosen to represent three different leaf characteristics. Then, we analyzed the correlation relationship of the particle metrics at landscape, class, and patch levels and implemented the principal components analysis and factor analysis. Firstly, at landscape level, metrics are mostly correlated with each other and the correlation relationship of metrics of ailanthus and willow were stronger than that of ash, which has coarse-texture leaves without hair. At class level, most of the metrics were correlated and the correlation relationship of metrics of ailanthus, whose leaves have microgrooves without hair, was weaker than that of ash and willow. At patch level, judging from proximity, the distance between particles from the same range was smaller for particles with complicated shape. Secondly, particles from four ranges were analyzed separately. The shape complexity of particles decreased and increased as the area increased respectively for PM1 (diameter ≤ 1 μm) and large particles (diameter ≥ 10 μm). Two principle components were identified for landscape and class levels respectively. These results will be useful for the in-depth understanding of the particles deposited on the leaf surface. [ABSTRACT FROM AUTHOR]

The availability of remote sensing images of various resolutions has enabled the incorporation of landscape structures in land-cover mapping. Despite the effectiveness of landscape metrics in quantifying landscape structures, they are inadequate in characterizing three elements: spatial neighborhoods, spatial dependencies, and semantic dependencies. Moreover, methods for mining the regularity of landscape-structure heterogeneity (i.e., spatial variations in landscape structures) are still limited, particularly for applications in urban land-cover mapping. This study hence proposes a novel approach with the aims to (1) characterize landscape structures considering the above three elements; (2) mine the regularity of landscape-structure heterogeneity; and (3) apply landscape-structure information as contexts to improve urban land-cover mapping. To achieve the first aim, landscape-structure features including pair-wise spatial relationships and neighborhood-based landscape metrics are defined. To accomplish the second aim, a clustering technique and a landscape infographic are used to cluster landscape structures and visualize landscape-structure types, respectively. Finally, a hierarchical classifier based on the feedforward multi-layer perceptron is developed for the third aim. Experiments are conducted in a heterogeneous urban environment in Beijing, China. The results show that the proposed approach, which considers 34 landscape-structure features and 19 landscape-structure types, achieves a classification accuracy improvement of 6.43% compared with the approaches without considering landscape-structure information. This study therefore demonstrates the effectiveness of incorporating landscape-structure features and landscape-structure types in improving urban land-cover mapping. [ABSTRACT FROM AUTHOR]

Globally, wetland loss and degradation have become serious environmental and ecological issues. Wetland monitoring of Ramsar sites in China is important for developing reasonable strategies to protect wetlands. Satellite image time series may be used for the long-term monitoring of wetland ecosystems. The present study used moderate-resolution imaging spectroradiometer (MODIS) time series data collected in 2001 and 2013 for 20 Ramsar sites in China and assessed the environmental status of these reserves using landscape metrics. The results showed that specific seasonal wetland classes, such as flooded mud, permanent water and seasonal marshes, can be identified using MODIS time series data with acceptable accuracy. In addition to wetland area, we suggest using other landscape metrics, including landscape integrity and landscape disturbance or degradation indices, to assess wetland environmental quality. The slight wetland loss (0.8%) noted in the 20 reserves evaluated herein could indicate the effectiveness of efforts of the Chinese government and local government agencies to protect Ramsar sites. The existing unfavourable environmental conditions, which were manifested by low landscape integrity and high landscape disturbance or degradation for some reserves, were caused primarily by increasing water requirements outside the reserves and by agricultural development within reserves. Therefore, determining how to balance relationships between economic development and ecological protection of the reserves will be important in the future. [ABSTRACT FROM AUTHOR]

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy. [ABSTRACT FROM AUTHOR]

According to the plant information of Puxing Village, a typical village in Chengdu Plain, the GIS map was drawn to analyze the landscape ecology pattern by FRAGSTATS software. The results show that in the past 10 years, although urbanization had a great impact on the rural ecological pattern, it was still in a stable ecological environment. The comparison of the landscape index shows that the replacement of the vegetation community pattern leads to the conversion of the source population from the original farmland to laurel and the increase of whole vegetation community under artificial intervention is the most important factor for the change of the vegetation community richness. At the same time, the pattern analysis at the horizontal level also reveals the obvious effect of the fast road as an artificial product for the enhancement of nearby vegetation community richness. [ABSTRACT FROM AUTHOR]

For the purpose of testing the group of landscape indicators an analysis was performed of the fundamental characteristics of the horizontal landscape structure of Vransko Lake Nature Park. The objectives of this study were (i) to select and analyse the group of landscape indicators at the level of elements and classes as fundamental landscape units that are relevant and useful in improving landscape planning; (ii) to analyse the horizontal landscape structure of Vransko Lake Nature Park; and (iii) to analyse changes to the features of the horizontal structure of determined classes due to anthropogenic effects and the identification of dominant/stable and threatened/labile types of classes. The fundamental hypothesis of the paper is that through an analysis of landscape indicators, it is possible to precisely determine the spatial relations between the elements and classes within the landscape, and that it is possible to determine fragmentation and the existence of specific dominant/stable and threatened/labile landscape types. Methods applied in this study were landscape analysis methods based on landscape indicators, GIS and statistical methods. Two extension (Patch Analyst and V-Late) within ArcGIS were used and software Fragstat. The landscape of Vransko Lake Nature Park includes 30 habitat classes. A habitat map was drafted in the scale 1:5000, according to the rules of the National Habitat Classification of the Republic of Croatia. For the purpose of analysing the horizontal structures of elements within Vransko Lake Nature Park, 12 landscape indicators were used. The analysis was conducted at the level of 30 classes representing habitats. Through the analysis of six selected indicators (CA, MPS, Proportion, TE, MNNdist i Proximity) of landscape structure, dominant and threatened classes within the landscapes of Vransko Lake Nature Park were identified. As threatened landscape classes traditional vineyard and thermophilic flood vegetation were recognized. Dominant landscape classes are mixed, less frequently, pure evergreen forests and thorny low vegetation (dračici). [ABSTRACT FROM AUTHOR]

This study was taken up to investigate the effects of landscape patterns on the soil erosion processes in a mountain-basin watershed. The revised universal soil loss equation and sediment delivery distribution models were used to estimate the soil erosion processes. The landscape patterns include the landscape metrics at the landscape level, landscape composition and configuration indicators on the basis of source-sink landscape theory. In the study area, the grassland, bare land, farmland and construction land were the sediment-source landscape; the forest and shrub were the sediment-sink landscape. The correlation analysis results showed that the soil erosion processes were significantly associated with the landscape patterns of the study area. At the landscape level, fragmentation metric was positively correlated with soil erosion; diversity metric was negatively related to soil erosion and sediment yield at the sub-basin scale. Among the source-sink landscape composition and configuration indicators, the composition indicator was positively correlated with soil erosion rate and sediment yield. In the configuration landscape indices, the shape index was negatively correlated with soil erosion rate and sediment yield; the fragmentation index was positively correlated with soil erosion rate and negatively correlated with sediment delivery rate. These results indicated that the optimization measures, such as increase in the area, connectivity and regularity of sediment-sink landscape, or decrease in the proportion, connectivity and regularity of sediment-source landscape, were favorable for soil conservation. Furthermore, the landscape indicators based on the source-sink theory could provide more information for landscape pattern optimization to reduce soil erosion. [ABSTRACT FROM AUTHOR]

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing amore fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments. [ABSTRACT FROM AUTHOR]

The pattern and structure of urban green space (UGS) plays a significant role in the landscape and ecological quality (LEQ) of UGS, especially in a compact city with limited space. Based on landscape metrics, this study proposes an innovative method to quantify the effects of UGS pattern and structure on LEQ. Taking Shanghai, China as the study area, we calculated all landscape-level spatial metrics in FRAGSTATS, used correlation analysis in SPSS for data reduction, and adopted factor analysis and cluster analysis to statistically analyze the metrics and assesse the LEQ of UGS. These methods bridge the research gap of UGS distribution assessment for LEQ value by landscape metrics. Results showed that new districts usually have higher LEQ of UGS than old towns. Of the 17 districts in Shanghai, Chongming has the highest LEQ of UGS and Hongkou has the lowest. For the UGS pattern and structure, the eight old towns are similar, in contrast to the new districts of Chongming and Pudong, which are more dissimilar than the other districts for LEQ of UGS. The findings could help compact cities having limited UGS to develop and achieve better LEQ. [ABSTRACT FROM PUBLISHER]

Mapping large areas for planning and conservation is a challenge undergoing rapid transformation. For centuries, the creation of broad-extent maps was the near-exclusive domain of expert specialist cartographers, who painstakingly delineated regions of relative homogeneity with respect to a given set of criteria. In the satellite era, it has become possible to rapidly create and update categorizations of Earth’s surface with improved speed and flexibility. Land cover datasets and landscape metrics offer a vast set of information for viewing and quantifying land cover across large areas. Comprehending the patterns revealed by hundreds of possibly relevant landscape metric values, however, remains a daunting task. We studied the information content of a large set of landscape pattern metrics across Quebec, Canada, asking whether they were capable of making consistent, spatially cohesive distinctions among patterns in landscapes. We evaluated the possibility of metrics to identify representative landscapes for efficient sampling or conservation, and determined areas where differences in nearby landscape patterns were the most and least pronounced. This approach can serve as a template for a landscape perspective on the challenges that will be faced in the near future by planners and conservationists working across large areas.

This paper presents the PixScape software dedicated to landscape visibility modeling based on digital spatial data. PixScape is an integrated software combining all existing functions in standard GIS tools in this field, and proposing ‘other original functions. It facilitates the overall processing chain of visibility analyses, and offers a wide range of commonly used metrics. Its originality is to offer a choice between two specific methods of visibility computations, and the possibility of advanced analysis of landscape visible configuration. The paper presents an overview of all the visibility analysis parameters offered by PixScape, all the available visibility metrics, and the parallelization methods for reducing computation time.

An urban fringe area, depicted as a typical ecotone, is a region where both social and environmental problems are concentrated. Identifying and evaluating the spatial–temporal characteristics of urban fringe areas is significant for future development. On the basis of the land use data extracted from remote sensing data, the Shannon diversity index (SHDI) of each unit can be calculated, and identifying the urban fringe area by the breakpoint method is reliable. By using the rapidly growing Changchun as example, this study identifies the urban fringe of Changchun in 1995, 2005, and 2015 by applying the breakpoint method. The expansion amount, change mode, direction of expansion, landscape, and influence factors are evaluated. Policy and planning are the main factors influencing the development direction of the Changchun fringe area. The urban fringe area of Changchun City is extended to the east, southeast, and north. From 1995 to 2005, the outlying expansion was the dominant type. The main change mode was the infilling type due to the reduction of available land, from 2005 to 2015. In accordance with the landscape metrics, the landscape within the urban fringe transformed from fragmentation to regularization. The development of the urban fringe also transformed from a disorderly to an orderly manner.