Number Of Patches Research Articles

Piecewise Developable Modeling via Implicit Neural Deformation and Feature-Guided Cutting.

We propose a novel and automatic method to model shapes using a small set of discrete developable patches. Central to our approach is using implicit neural shape representation that makes our algorithm independent of tessellation and allows us to obtain the Gaussian curvature of each point analytically. With this powerful representation, we first deform the input shape to be an almost developable shape with clear and sparse salient feature curves. Then, we convert the deformed implicit field to a triangle mesh, which is further cut to disk topology along parts of the sparse feature curves. Finally, we achieve the resulting piecewise developable mesh by alternatingly optimizing discrete developability, enforcing manufacturability constraints, and merging patches. The feasibility and practicability of our method are demonstrated over various shapes. Compared to the state-of-the-art methods, our method achieves a better tradeoff between the number of developable patches and the approximation error.

Driving factors of earthworm communities in Mediterranean urban parks

Earthworm communities within urban environments remain an intriguing subject. This study aims to unravel the intricate relationship between these communities and the heterogeneous urban soils they inhabit. Urban soils, shaped by past and present human activities, harbor a rich diversity of earthworms, yet the specific factors influencing these communities remain poorly understood.Earthworm communities were sampled across 13 urban parks of Montpellier, a Mediterranean city in France. The effect of four variables at two scales were assessed: (i) landscape attributes within a 100-meter radius surrounding each sampling point and (ii) site-specific factors, including soil properties such as organic carbon content and pH levels, soil age, and management practices. Variation partitioning was employed through partial canonical correspondence analysis in order to disentangle the effects of these variables on earthworm community composition.A total of 16 species were identified out of 1270 individuals collected. Most are ubiquist, with a limited number being endemic to the Mediterranean region, potentially indicating biotic homogenization due to urbanization. In addition, multivariate analyses emphasized the substantial influence of landscape characteristics, composed by the rate of green spaces and the number of patches. These landscape-level attributes and especially the connectivity of green spaces emerged as primary drivers, surpassing the influence of management practices, soil age and soil properties.Thus, this research underscores the importance of considering diverse scales, and particularly landscape-level factors, in comprehending and restoring soil fauna such as earthworm communities within Mediterranean urban parks.

Multi-Dimensional Landscape Connectivity Index for Prioritizing Forest Cover Change Scenarios: A Case Study of Southeast China

Predicting forest cover change (FCC) and screening development scenarios are crucial for ecological resilience. However, quantitative evaluations of prioritizing forest change scenarios are limited. Here, we took five shared socio-economic pathways (SSPs) representing potential global changes, namely SSP1: sustainability, SSP2: middle of the road, SSP3: regional rivalry, SSP4: inequality, and SSP5: fossil-fueled development, which were constructed by integrated assessment and climate models. We modeled them with the patch-generating land use simulation (PLUS) and constructed a multi-dimensional landscape connectivity index (MLCI) employing forest landscape connectivity (FLC) indices to assess forest development in Fujian Province, Southeast China. The MLCI visualized by radar charts was based on five metrics, including forest patch size (class area (CA), number (patch density (PD), isolation (landscape division index (DIVISION), aggregation (mean nearest-neighbor index (ENN_MN), and connectance index, (CONNECT). The results indicate that FC will remain above 61.4% until 2030, with growth observed in SSP1 and SSP4. Particularly, FC in SSP4 substantially increased, converted from cropland (1140.809 km2) and grassland (645.741 km2). SSP4 has the largest MLCI values and demonstrates significant enhancements in forest landscape integrity, with CA, ENN_MN and CONNECT increasing greatly. Our study offers valuable approaches to and insights into forest protection and restoration.

Effects of the main media of wind and water on the biodiversity pattern of grassland and its driving mechanism in Poyang Lake

AbstractAs important media for species diffusion, water and wind are two important factors for grassland biodiversity conservation in lake areas. Exploring their driving mechanism on grassland biodiversity is crucial for maintaining the lake ecosystem's equilibrium. Our study utilizes the data of wind velocity and water level, which are significant performance factors for wind and water respectively in Poyang Lake from 2000 to 2020 to reveal their interannual time‐series fluctuation characteristics and their influence mechanism on the grassland biodiversity pattern. Landscape pattern indices and biodiversity indicators, such as the number of patches (NP), patch density (PD), landscape spreading index (CI), landscape fragmentation index (LSD), landscape aggregation index (AI), Simpson diversity index (MSIDI) and Simpson evenness index (MSIEI) were analysed, trend analysis, redundancy analysis and structural equation modelling were applied in this study. The main results were: (1) From 2000 to 2020, Poyang Lake's wind velocity decreased gradually, and the water level first decreased and then rose. NP in Poyang Lake fluctuated substantially, LSD fluctuated frequently and obvious temporal heterogeneity existed. (2) CI and AI increased from low to high value, facilitating species dispersal and migration. The dominant species with high aggregation gradually established stronger connectivity. Moderate spreading degree and aggregation degree maintained high biodiversity and evenness, whereas excessive spreading degree and aggregation degree led to homogenization of species, decrease in biodiversity, reduction in species evenness, and increase in dominance. (3) As the landscape transformed from having no obvious dominant species to being dominated by several dominant species, MSIEI and landscape dominance changed from high to low and low to high respectively. Moreover, the biodiversity shifted from high to low, and species distribution in the landscape shifted from balanced to unbalanced. (4) The effect of water level on PD, AI, LSD, MSIDI and MSIET was significantly higher than that of wind velocity. LSD was mainly regulated by the minimum wind velocity affecting the maximum and average water levels. MSIDI and MSIET were primarily governed by the minimum wind velocity affecting the minimum water level. The minimum water level decreased as the minimum wind velocity increased, and MSIDI and MSIET weakened as the minimum water level decreased.

Self-Assembly of Model Three- and Four-Patch Colloidal Particles in Two Dimensions.

A coarse-grained effective solvent model of two-patch particles is extended to study the self-assembly of three- and four-patch particles to two-dimensional honeycomb and square lattices, respectively. Employing this model, grand canonical ensemble simulations are done to calculate vapor-liquid equilibria and the critical temperatures for patchy particles of various patch widths. The range of stability of the liquid, although very limited compared to isotropic particles, which interact through a longer-range potential, depends on the patch width and on the number of patches. Biased sampling and unbiased simulations are also done to investigate the mechanism of nucleation and crystal growth for honeycomb and square lattices, self-assembled from three- and four-patch particles, respectively. A two-step mechanism governs the nucleation of both lattices. In the first step, the particles form a dense amorphous network, and in the second step, the particles inside the amorphous network reorient to form crystalline nuclei. Barrier heights for the nucleation of honeycomb and square lattices are 7.8 kBT and 7.4 kBT, which are close to the reported values for the nucleation of the kagome lattice. In agreement with confocal microscopy experiments, the self-assembly in a honeycomb lattice involves the formation of 5- to 7-membered rings. The 5- and 7-membered rings hamper the nucleation of the honeycomb lattice, through defect formation and rotation of the symmetry planes of crystals that form at their surfaces. With the progress of self-assembly, a substantial amount of restructuring of the defects and crystals in their vicinity is needed to heal the defects.

Impact of carbon neutralization policy on the suitable habitat distribution of the North China leopard

The Chinese government has introduced a carbon neutral policy to cope with the rapid changes in the global climate. It is not clear what impact this policy will have on wildlife. Therefore, this study analyzed the suitable habitat distribution of China’s unique leopard subspecies in northern Shaanxi, and simulated the potential suitable habitat distribution under different carbon emission scenarios at two time points of future carbon peak and carbon neutralization. We found that in the future SSPs 126 scenario, the suitable habitat area and the number of suitable habitat patches of North China leopard will continue to increase. With the increase of carbon emissions, it is expected that the suitable habitat of North China leopard will continue to be fragmented and shifted. When the annual average temperature is lower than 8 °C, the precipitation seasonality is 80–90 mm and the precipitation of the warmest quarter is greater than 260 mm, the probability of occurrence of North China leopard is higher. The increase in carbon emissions will lead to the reduction, migration, and fragmentation of the suitable habitat distribution of the North China leopard. Carbon neutrality policies can protect suitable wild habitats. In the future, the impact of carbon neutrality policies on future wildlife habitat protection should be carried out in depth to effectively promote the construction of wildlife protection projects.

Ants and predators cope with pest pressures by interacting with the surrounding vegetation at low spatial scales

AbstractBiological control of pests can be enhanced by the presence of semi‐natural habitats within agricultural landscapes. However, this assumption remains controversial due to inconsistencies related to the type of agroecosystems and the natural enemies studied. Within olive orchards, there is a lack of information regarding the interaction among natural enemies and their relation with habitat structure to control pests at the landscape scale. Here, we investigate the effects of the natural habitat on the pest, pest damage and the interaction of pests and natural enemies – using a trophic guild approach, in organic olive orchards. For this, we decomposed the natural habitats into vegetation structures and analysed their effects with a multi‐scale perspective. Our results show that (1) greater proportions of natural habitats increase the abundance of ants (omnivores) and predators and diminish pest pressures – reducing the impact of Prays oleae on olive fruits. (2) Vegetation structures within natural habitats were grouped, based on their effects, into three main vegetation groups: grassland and forest, scrublands and olive trees. However, the dense scrubland and the dense forest improve the abundance of natural enemies that are linked to pest damage the most. (3) Prays oleae increases in landscapes dominated by low numbers of patches that are highly aggregated. Conversely, ants and predators increased in landscapes dominated by high numbers of patches that have a less edge‐resembling shape. (4) Within the olive canopy, the abundance of lacewing larvae and salticid spiders is related to lower pest damage and a reduction in P. oleae adults respectively. However, when ants and predators interact with the natural habitat, they can cope with pest pressures without the need for high abundances, supporting ‘the more‐effective natural enemy hypothesis’ in agroecosystems.

Investigating of Spatial Urban Growth Pattern and Associated Landscape Dynamics in Congolese Mining Cities Bordering Zambia from 1990 to 2023

This study investigates the spatial urban growth patterns of cities along the Democratic Republic of the Congo (DRC) and Zambia border, a region of significant economic importance characterized by cross-border trade. This activity has led to rapid but unplanned urban growth. The objective is to quantify the spatial expansion of Congolese cities (Kipushi, Kasumbalesa, Mokambo, and Sakania) bordering Zambia and to evaluate associated landscape changes. The methodology of this study includes the supervised classification of Landsat images with a spatial resolution of 30 m for the years 1990, 2000, 2010, and 2023. This classification was validated using field data. Subsequently, landscape metrics such as class area, patch number, Shannon diversity index, disturbance index, urban expansion intensity index, largest patch index, and mean Euclidean distance were calculated for each city and each date. The results reveal substantial landscape transformations in the border cities between 1990 and 2023. These changes are primarily driven by rapid urban expansion, particularly pronounced in Kasumbalesa. Between 1990 and 2023, forest cover declined from 70% to less than 15% in Kipushi, from 80% to 10% in Kasumbalesa, from 90% to 30% in Mokambo, and from 80% to 15% in Sakania. This forest cover loss is accompanied by an increase in landscape element diversity, as indicated by the Shannon diversity index, except in Kipushi, suggesting a transition towards more heterogeneous landscapes. In these border cities, landscape dynamics are also characterized by the expansion of agriculture and savannas, highlighted by an increase in the disturbance index. Analysis of spatial pattern changes shows that built-up areas, agriculture, and savannas exhibit trends of patch creation or aggregation, whereas forests are undergoing processes of dissection and patch attrition. Congolese cities bordering Zambia are undergoing substantial spatial changes propelled by intricate interactions between economic, demographic, and infrastructural factors. Our results underscore the need for sustainable development strategies to address urban sprawl through smart growth policies and mixed-use developments, mitigate deforestation via stricter land use regulations and reforestation projects, and enhance cross-border cooperation through joint environmental management and collaborative research initiatives.

Test-based patch clustering for automatically-generated patches assessment

Previous studies have shown that Automated Program Repair (apr) techniques suffer from the overfitting problem. Overfitting happens when a patch is run and the test suite does not reveal any error, but the patch actually does not fix the underlying bug or it introduces a new defect that is not covered by the test suite. Therefore, the patches generated by apr tools need to be validated by human programmers, which can be very costly, and prevents apr tool adoption in practice. Our work aims to minimize the number of plausible patches that programmers have to review, thereby reducing the time required to find a correct patch. We introduce a novel light-weight test-based patch clustering approach called xTestCluster, which clusters patches based on their dynamic behavior. xTestCluster is applied after the patch generation phase in order to analyze the generated patches from one or more repair tools and to provide more information about those patches for facilitating patch assessment. The novelty of xTestCluster lies in using information from execution of newly generated test cases to cluster patches generated by multiple APR approaches. A cluster is formed of patches that fail on the same generated test cases. The output from xTestCluster gives developers a) a way of reducing the number of patches to analyze, as they can focus on analyzing a sample of patches from each cluster, b) additional information (new test cases and their results) attached to each patch. After analyzing 902 plausible patches from 21 Java apr tools, our results show that xTestCluster is able to reduce the number of patches to review and analyze with a median of 50%. xTestCluster can save a significant amount of time for developers that have to review the multitude of patches generated by apr tools, and provides them with new test cases that expose the differences in behavior between generated patches. Moreover, xTestCluster can complement other patch assessment techniques that help detect patch misclassifications.

Diversity and Distribution of Monocot Understory Herbs during Tropical Forest Succession in Northeastern Costa Rica

Broad-leaved monocot herbs form one of the most common and diverse growth forms of Neotropical plants. Their significance and frequency of occurrence is particularly notable in the understories of tropical rainforests, where they form a dominant element. We assessed and quantified changes in the cover and diversity of understory herb communities in a chronosequence of 1 ha permanent plots established as part of a multidisciplinary study on tropical forest regeneration in the Atlantic lowlands of northeastern Costa Rica. Sampled were two young stands cleared 12 years ago, two secondary forests with 21 and 39 of years of recovery since clearance, and two stands in old-growth primary forest. Changes in species composition during succession were assessed using Chao’s Jaccard similarity index. Observed species richness ranged from 15 to 26 species in individual plots, with the greatest number of species in the 21-year intermediate-age and fewest in the young 12-year plots. Herb species sampled represented 6 families, 15 genera, and 39 species, with the Araceae contributing the largest number of species. Ten species were sampled in all six stands, while fourteen species were found exclusively in one plot. Herb density (ramets m−2) showed a hump-shade trend, with peak density in the intermediate stands and a lower level in mature and young secondary forests. Mean herb cover in 25 m2 quadrats ranged from 2.0% (young stand) to 22.7% (intermediate-age stand) and differed significantly both among stand types and among sites. Both observed and estimated species richness increased along the chronosequence as a whole, with the highest number of species in primary forest, although only slightly higher than in intermediate-age stands. Over half of the species exhibited some degree of clonal growth, with the extent of clonal spread varying among species and forest stands. Although we did not find a clear pattern between clonality and forest age, we observed a greater number of clonal patches in secondary over primary forest stands.

Effects of repeated drawdown flushing on riverbed fine sediment dynamics downstream from a dam

Sediment accumulation in reservoirs is frequently a problem, impelling dam managers to implement strategies such as drawdown flushing to limit siltation. Drawdown and other sediment removal methods may induce riverbed clogging downstream of dams, especially in river sections where water is diverted, thereby reducing transport capacity. In this study, we investigate the effects of drawdown flushing downstream of the Plan d’Arem run-of-the-river dam (Upper Garonne, Spain – France border) using an adaptive inter-site comparison strategy to consider a range of spatial and temporal conditions, which allow us to separate the effects of dam storage and flushing from other potential factors. Drawdown flushing has been undertaken three times during the study period over a short span of time (2 months). We couple bed material sampling, which provides direct information on bed composition, with airborne infrared thermal imaging to better interpret whether fine sediment interstitial storage within the bed is associated with clogging. We also measure bed surface grain size and bed mobility in order to investigate their potential role in controlling fine sediment dynamics. We identify surface grain size and water diversion as the main factors controlling fine sediment spatial distribution, with coarse-grained bed-surfaces and by-passing promoting fine sediment enrichment. As a result, sites located upstream and within the by-passed reached of the Plan d’Arem dam show higher fine sediment interstitial storage than sites downstream from the by-passed reach. Results from thermal imagery demonstrate such interstitial storage does not induce clogging effect. The reaches with the most important sediment storage host a high number of cool-water patches, indicating water exchanges with the hyporheic zone. Post-flushing bed composition indicates systematic export of fine sediments from the bed matrix at all sites after the first operation, afterwards fine levels remain low after the second and the third flushing. The low impact of dam flushing in term of clogging is interpreted by the fact that the interstitial material is very sandy.

Identification of spatial protection and restoration priorities for ecological security pattern in a rapidly urbanized region: A case study in the Chengdu–Chongqing economic Circle, China

The continuous expansion of modern cities not only leads to ecological degradation but also seriously threatens regional ecological security and sustainable development. The construction of ecological security patterns (ESPs) has emerged as a significant approach to alleviate or even solve the conflict between regional development and ecological protection. The Chengdu–Chongqing Economic Circle (CCEC) represents the core area of regional economic development strategy in western China, characterized by rapid economic growth from 2000 to 2020. This study integrates assessments of ecosystem services importance, eco-environmental sensitivity and landscape connectivity; uses circuit theory and hydrological analysis to establish a research framework for the spatiotemporal evolution of regional ESP; and develops an optimized ESP combined with the Major Function Oriented Zone. The results indicate that urban expansion significantly impacted the ESP of the CCEC between 2000 and 2020. The fragmentation and merging of ecological sources occurred simultaneously, the number of patches reduced by 28.13% from 64 to 46. The early ecological security network was compromised, leading to the disappearance or elongation of some ecological corridors. The number of ecological corridors decreased by 36.03% from 136 to 87; the total length was reduced by 29.92% from 7500.57 km to 5256.28 km. Urgent optimization of the ESP is needed, reducing the number of key ecological protection areas by 50% from 106 to 53 while increasing priority restoration areas by 13.51% from 37 to 42. The study also reveals the insufficiency of the current Major Function Oriented Zone in protecting linear corridors, necessitating focused attention on the protection and restoration of ecological sources and surrounding corridors in important development zones. Additionally, a spatial optimization strategy of "one shelter, two cores, and three regions" is proposed to enhance regional ecosystem stability and connectivity. The aim was to strike a balance between ecological protection and food security by recommending an ecological corridor width range of 30∼100 m. These research findings offer scientific guidance for ecological space protection and restoration in the CCEC, contributing to the enhancement of both scientific and rational ecological planning in rapidly urbanizing areas.

Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km2 in 1991 to 33.4 km2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km2 to 58.7 km2, driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km2 to 10.5 km2, indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience.

Study on the influence of landscape pattern on the spread of pine wilt disease from a multi-scale perspective

Since the introduction of pine wilt disease (PWD) into Chongqing, China, it has been continuously spreading, posing a significant threat to the local forest ecosystem dominated by pine forests. Utilizing data spanning the last two decades on the PWD epidemic subcompartment and host coniferous forest in Chongqing, this study employs a geographic detector model to scrutinize the impact of forest landscape patterns on PWD dissemination at the county, township, and 1 km grid scales. The findings reveal three distinct stages of the PWD epidemic in Chongqing from 2001 to 2020: diffusion, stabilization, and outbreak. The western and central regions of Chongqing experienced severe impacts, while the southern part exhibited relatively milder effects. Across the three spatial scales, various landscape pattern indices exhibit robust and consistent impacts on PWD occurrence. Notably, patch area emerges as the most influential factor, with an explanatory power reaching 0.228. Additionally, landscape shape index, number of patches, patch density, river and road exert substantial influence on PWD incidence. Conversely, the impact of edge density, landscape dominance, landscape separation, and landscape fragmentation on PWD occurrence is comparatively weak. Moreover, the interaction of different landscape pattern factors nonlinearly enhances the explanatory power of PWD occurrence. Among these interactions, the synergy between patch area and landscape dominance proves to have the highest explanatory power for the spatial differentiation of PWD at 0.718. This study explores the relationship between the invasion and spread of PWD and landscape patterns, offering useful insights for the prevention and early warning of PWD. Additionally, this research provides valuable reference points for promoting the healthy and sustainable development of forest resources in China.

A New Paradigm for Assessing Detailed Dynamics of Forest Landscape Fragmentation

There is an urgent need for a thorough assessment of forest landscape fragmentation to inform forest protection and restoration, and reforestation policies. However, there is currently a lack of an effective comprehensive index for forest landscape fragmentation, and detailed knowledge of the forest landscape fragmentation dynamics remains insufficient. Here, taking Putian City of Fujian Province in Southeastern China as a case, we employed a forest fragmentation comprehensive index (FFCI) to capture key features of forest landscape fragmentation, such as patch size, number, and distribution. Then, bivariate spatial autocorrelation analysis was employed to identify the spatial associations between the static forest landscape fragmentation (FFCI) and the dynamic forest landscape fragmentation (ΔFFCI), and the spatial coupling modes among the three individual components of FFCI (mean patch area, MPA; aggregation index, AI; patch density, PD) were identified to explore the detail process of forest landscape fragmentation. Finally, the random forest model was applied to observe the impact factors of forest landscape fragmentation dynamics. The findings showed that forest landscapes with different degrees of fragmentation exhibited more noticeable changes at both ends (i.e., either high or lower-level fragmentation), with the intermediate level remaining consistent from 2000 to 2020. Around 18.3% of forest landscapes experienced a decrease in fragmentation, particularly in the northern part of the study area, while approximately 81.7% of forest landscapes exhibited an increasing trend in fragmentation. The bivariate spatial autocorrelation analysis indicated that the proportion of Low–High-type grids was the highest at 17.3%, followed by the High–High type at 7.0%. We also identified eight forest landscape fragmentation modes, which indicate the most significant forest landscape fragmentation pattern is a decrease in MPA and an increase in PD. Moreover, the anthropogenic factors (e.g., population density and night light intensity) were found to dominate the FFCI dynamics during 2000–2020. This study offers an efficient research paradigm for the dynamics of forest landscape fragmentation. The outcomes are conducive to an in-depth comprehension of the detailed dynamic information of forest landscape fragmentation, and supply a scientific foundation for enhancing the overall ecological service function of the forest.

Mitigating urban heat island through neighboring rural land cover

Globally, the deteriorating Urban Heat Island (UHI) effect poses a significant threat to human health and undermines ecosystem stability. UHI mitigation strategies have been investigated and utilized extensively within cities by the provision of green, blue or gray infrastructures. However, urban land is precious and limited for these interventions, making it challenging to address this issue. Neighboring rural land cover may serve as a cooling source and have a great potential to mitigate UHI through processes such as heat absorption and circulation. This study aims to address the following questions: (1) what is the location of neighboring rural land cover to effectively mitigate UHI for the entire city and (2) what are the key parameters of the landscape. We investigated the quantitative and qualitative relationships between rural land cover and UHI, drawing on geographical and environmental data from 30 Chinese cities between 2000 and 2020. We found that the rural land cover extending outward from the urban boundary, approximately half of the equivalent diameter of city, had the most pronounced impact on UHI mitigation. The number and adjacency of landscape patches (a patch is a homogeneous and nonlinear basic unit of a landscape pattern, distinct from its surroundings) emerged as two key factors in mitigating UHI, with their individual potential to reduce UHI by up to 0.5 °C. The proposed recommendations were to avoid fragmentation and enhance shape complexity and distribution uniformity of patches. This work opens new avenues for addressing high-temperature urban catastrophes from a rural perspective, which may also promote coordinated development between urban and rural areas.

Projected urban flood risk assessment under climate change and urbanization based on an optimized multi-scale geographically weighted regression

Previous research has primarily focused on evaluating flood risks influenced by single factors, often neglecting the combined impacts of climate change and urbanization on historical and future flood risks. This study utilized 12 assessment indicators across three criteria layers. It employed the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and an optimized Multi-scale Geographically Weighted Regression (MGWR) to develop a comprehensive assessment framework for historical and projected urban flood risks under combined scenarios of RCPs and SSPs. The risk of future extreme precipitation events increased under 4 RCPs. Compared with 2010, Beijing's urban land area is expected to increase by an average of 53.64 % in 2060 under 5 SSPs, accompanied by rapid socioeconomic development. MGWR based on K-means optimization improves operational speed by reducing the number of patches. The areas classified as high and highest flood risk levels increased by 38.87 % and 60.17 % from the 2010s to the 2060s, indicating an upward trend in future flood risk. Higher flood risk is observed under the high emissions combination scenario. Structural equation modeling (SEM) revealed that road network density (RND), runoff depth (RD), and distance to road (DRO) were the main influencing factors contributing to flood risks in Beijing.

Fast Noise Level Estimation via the Similarity within and between Patches

Patch level-based noise level estimation (NLE) is often inaccurate and inefficient because of the harsh criteria required to select a small number of homogeneous patches. In this paper, a fast image NLE method based on a global search for similar pixels is proposed to solve the above problem. Specifically, the mean square distance (MSD) is first expressed in the form of the standard deviation (std) and mean value of image patches. Afterward, the two values, std and mean, are calculated and stored in advance. Then, a 2D statistical histogram and summed area table are adopted to speed up the search for similar patches. Further, the most similar pixels are selected from similar patches to obtain an initial estimation. Finally, we correct the deviation of the initial estimation by re-injecting noise for secondary estimation. Experimental results show that the proposed method outperforms the state-of-the-art techniques in fast NLE and guided denoising.

Podejście oparte na GIS analizie do relacji między jednostkami gruntów a użytkowaniem gruntów w centralnym regionie Portugalii

Land units refer to coherent spatial areas characterized by a degree of homogeneity concerning certain properties like geology, soils, and climate. The Land use mosaic corresponds to a circumstantial layer representing the landscape’s present state, depicting the present resource allocation factors. Nevertheless, the stable potential layer is related to the stable characteristics of each site and allows the identification of use constraints or potentials. In this study, we use a methodology based on the land unit concept to define a stable potential layer at a regional level. Therefore, land units were delimited for the Central region of Portugal, resulting from the combination of geomorphology, soil parent material, and bioclimatic influence. For each land unit representative sample areas were characterized in terms of their land use mosaic characteristics. For that purpose, selected landscape metrics were used to quantify the land use mosaic geometrical attributes: Shannon’s Diversity Index, Edge Density, Mean Patch Size, and Number of Patches. The existing land use types were also quantified. Finally, a cluster analysis was performed to define groups of samples representing the land units with similar land-use mosaic types. The landscape metrics that best explain the influence of the permanent structure of the territory on the circumstantial structure of use are Shannon's Diversity Index, Edge Density, and Number of Patches. The highest diversity land cover patterns are located in formations with a lithology rich to very rich in silica under Mesomediterranean dry to subhumid climate. The validation of the previously defined land units confirmed the reliability of the proposed methodology, with most of the land units strongly influencing the land use mosaic. The delimitation and characterization of homogeneous land units are useful for the definition of soil suitability and for the choice of the most appropriate uses and activities by the stakeholders.

Knowing the lay of the land: changes to land use and cover and landscape pattern in village tank cascade systems of Sri Lanka

Social-ecological systems (SESs) possess a great diversity of land use and land cover (LULC) types with unique assemblages of biodiversity and ecosystem services. However, LULC changes due to landscape fragmentation are emerging as major threats to the system productivity of SESs around the world. This study examined changes to LULC extent and landscape patterns in the Village Tank Cascade Systems (VTCSs) of Sri Lanka using satellite imagery and GIS techniques between 1994 and 2021. Multispectral Landsat images (5 TM and 8 OLI/TIRS) obtained from Google Earth Engine were classified using machine learning algorithms. Overall accuracies obtained were 85.9% (1994) and 88.6% (2021). The LULC change matrix and spatial pattern metrics were used to examine LULC and landscape pattern change dynamics over the VTCS landscapes. LULC change matrix results revealed that forest, which is the dominant LULC class covering 73.7% of the total land area was reduced by 206,725 ha due to transformation into agricultural (70.43%) and scrub (24.33%) lands between 1994 and 2021. Over this time landscape pattern of the VTCS has gradually changed from forest to agricultural land-dominated landscape, with forest and agricultural land types showing a significant negative correlation (p < 0.001; R2 > 0.868), particularly in the southeastern region. Landscape patterns were analysed based on eight spatial metrics calculated at both the landscape and class levels using FRAGSTATS spatial pattern analysis software. At the landscape level, the structure became more dispersed and complex in shape. Heterogeneity was noted to have gradually increased with weakening connectivity, whereas the fragmentation process had gradually accelerated. At the class level, the dominance of forest patches decreased, fragmentation and isolation increased, and connectivity and shape complexity reduced leading to the loss of fragmented forest habitats. The number of patches within the agricultural class increased and became more aggregated and complex in shape. Landscape performance indicators show that VTCSs have experienced a gradual loss of environmental sustainability. Assessment of LULC along with fragmentation can help to monitor the spatial pattern impacts that determine ecological integrity. Thus, the study provides scientific guidance for ecological restoration in degraded VTCSs to effectively improve ecological productivity.