Urban Landscape Fragmentation Research Articles

Unravelling blue landscape fragmentation effects on ecosystem services in urban agglomerations

The blue landscape (BL), which refers to the wetlands, rivers, lakes, and other bodies of water, is of immense importance for a sustainable environment. It provides a variety of ecosystem services, including carbon sequestration, water purification, soil fertility, and habitat for diverse flora and fauna. These services are crucial for sustaining the livelihoods of local communities and maintaining the health of the environment. In megacities like Kolkata, India, the BL is often subjected to fragmentation and degradation due to rapid urbanisation, industrialization, and other human activities. This has serious implications for ecosystem services and the overall health of the environment. This study is intended to value ecosystem service losses over the last 25 years and assess the influence of blue landscape fragmentation on ecosystem services in Kolkata, India. To accomplish this goal, satellite data was collected from 1994 to 2019 for both pre-monsoon and post-monsoon seasons. The results of the study showed that significant losses in ecosystem services were observed over this time period, primarily due to the decline of the East Kolkata Wetland and its conversion for settlement and agricultural purposes. Despite the existence of some policies aimed at protecting the wetland, more robust restrictions and remedial strategies are required to conserve and restore the blue landscape in Kolkata. This work adds to the corpus of research on the value of blue landscapes (BLs) and the environmental services they provide. The findings of this study highlight the need for increased attention to the conservation and management of BLs in India and provide a valuable foundation for future research and policy development. Furthermore, this research introduces the innovative concept of urban BLs as a nature-based framework for understanding urban landscape fragmentation, a novel contribution that fills a gap in the existing literature on this topic.

Jerusalem urban landscape fragmentation: from a city of peace into a city of pieces

During the past century, the city of Jerusalem expanded from 1 km2 (the walled city) to reach more than 126 km2 in 2005 and 164 km2 recently. The city presents an open book in urban planning practice, starting with the Ottoman time through the British Mandate (i.e. British rule in Palestine from 1917 to 1948, starting after the defeat of Ottoman rule in the area) and ending with the Israeli occupation. Planners during different regimes added several layers to the original fabric in attempts to transform the city into a ‘modern’ mosaic/collage. In this study, historical plans were analysed and sequential plans were gathered and stratified in order to show how the urban context was deformed and fragmented through unilateral planning.

Urban Landscape Fragmentation as an Indicator of Urban Expansion Using Sentinel-2 Imageries

Rapid urbanization in some cities has led to the emergence of numerous subsidiary settlements around their primary cities. Due to this rapid urbanization and growth, there is a great demand for urban land, mostly for commercial, industrial, and residential uses. Urban green spaces and vegetation are at risk due to a large amount of urban land, as seen by a decline in connectivity and increased fragmentation, especially due to land conversion. However, the identification of the spatial and momentary variability in the clustering and fragmentation of vegetation patterns in urban settings has not made full use of local indicators of spatial distribution measurements, such as Baqubah, a city in Iraq. Since it is essential to measure the degree of fragmentation and evaluate urban expansion trajectories consistently, this study proposes a new approach to assessing the anticipated direction of urban extension, using the fragmentation indicator of built-up patterns in urban areas. Sentinel-2 data was used to map the fragmented urban centres and their future extent in the city at a single time point. The proposed method employs indices to capture the initial distribution of spatial patterns of vegetation cover and built-up areas. The main extracted land cover classes, landscape fragmentation performance, and surface density analysis were accomplished in ArcGIS. The results indicate that the entire built-up area in Baqubah has a high degree of fragmentation at 75%, and about 23% of the open space within the urban extent of the city. Two predicted trajectories of urban expansion were also revealed: one may follow the external road direction, while the other is multi-directional, commencing from the edges of the built-up area. The study concludes that the new method is useful for comprehending and assessing urban landscape fragmentation, as well as anticipating its path. This integrated approach to remote sensing and GIS can sufficiently and effectively determine priority urban regions for successful planning and management. In addition, our study's findings highlight the potential of the suggested strategy as a useful spatially explicit method for determining the spatial clustering and fragmentation of urban landscape patterns. Doi: 10.28991/CEJ-2022-08-09-04 Full Text: PDF

Landscape characteristics effects on Diptera assemblages and their relation with seasonal variations in urban green patches

ABSTRACTThe growth of cities results in the fragmentation of natural habitats, and the alteration of the remaining ones. The effects of landscape‐level drivers on arthropod assemblages in urban green spaces remain poorly understood. The aim of this study was to evaluate the effects of landscape characteristics in Diptera assemblages of urban green patches and their relation with seasonality in a southern hemisphere temperate city. Flies were sampled in urban green patches in Córdoba city, Argentina, in summer and winter of the same year. Landscape metrics derived from Sentinel 2 images were calculated at two levels of spatial heterogeneity hierarchy, at increasing buffer areas. We used generalized linear models to analyse the effects of landscape characteristics on family abundance and richness. Landscape and seasonal effects on Diptera family composition were also assessed. Abundance, richness and composition of dipteran assemblages were associated with the contrasting conditions of summer and winter, urban landscape fragmentation and the aggregation of vegetation patches. In general, fly assemblages were favoured by the aggregation of vegetation patches. The response of dipterans to landscape characteristics differed between seasons. The effects of landscape characteristics on Diptera assemblages' composition were stronger in winter. We concluded that landscape characteristics appear to have a bigger effect when environmental conditions are less favourable for these organisms. Our study provides further understanding of the effects landscape level drivers have on arthropods in green urban patches. This is particularly relevant if we wish to maintain and manage biodiversity through landscape planning.

Understanding Urban Expansion on the Tibetan Plateau over the Past Half Century Based on Remote Sensing: The Case of Xining City, China

The Tibetan Plateau (TP) is an important area that affects global sustainable development. Quantifying spatiotemporal patterns of urbanization is crucial for maintaining the sustainability on the TP. This study took Xining City, the largest city on the TP, as an example to understand the urban expansion in this region in the past 50 years. We combined the high-resolution spy satellite data and China’s long-term urban land dataset (CULD) to quantify the urban expansion of Xining City. The object-oriented random forest classification was performed to extract urban land from spy satellite data in 1969, and the inter-annual correction was used to combine urban land information from 1969 to 2017. We found that the proposed approach can accurately quantify the urban expansion of Xining City over the past half century with an overall accuracy of 91% and a kappa coefficient of 0.86. Such high accuracy benefits from the fine resolution of spy satellite data and the consistency of CULD. We also found that Xining City experienced accelerated and fragmented urban sprawl to higher altitude areas, as a result of socioeconomic development and topographical limitations. The acceleration of urban expansion was more obvious, and the urban landscape fragmentation was more serious at high altitude areas. Such urban expansion encroached on cropland and grassland, and caused increased risks of landslides and other geological disasters. Therefore, Xining City urgently needs to promote the development of compact cities to control urban sprawl at higher altitude areas and provide a reference for improving urban sustainability across the TP. In this study, we analyzed the urban expansion of Xining city from 1969 to 2017, and provided a reliable way to understand the long-term spatiotemporal urbanization based on remote sensing, which has the potential for wide applications. In addition, the extracted urban information can help to improve the urban sustainability of Xining City and the entire TP.

Least‐cost path analysis for urban greenways planning: A test with moths and birds across two habitats and two cities

Abstract One of the major planning tools to respond to urban landscape fragmentation is the development of ecological corridors, that is, interconnected networks of urban green and blue spaces. Least‐cost paths (LCP) appear to be an easy and appropriate resistance‐based modelling method to respond to urban planners’ needs. However, the ecological validation of urban corridors using LCP is rarely performed and needs to be generalized to different species, habitats and cities. We developed an experimental design to test the efficiency of LCP predictions to detect highly connecting landscape contexts that facilitate individual movements compared to movements in less connecting landscape contexts. We deliberately assigned LCP analysis parameters based on the scientific literature and expert knowledge to test a method potentially easy to use for urban stakeholders. To extend the validation, we applied our LCP model to two biological taxa with different habitat requirements: grassland‐dwelling moths and forest‐dwelling passerines, and to two medium‐sized cities. We used mark–release–recapture (MRR) methods for moths and playback recall protocols for passerines to compare the patterns of individual movement between two contrasted connectivity contexts determined by the presence and absence of modelled LCPs. MRR protocol estimated movement rates between herbaceous patches and the two contrasted connectivity contexts. Playback recall protocol consisted in attracting individuals from wooded patches to the two contrasted connectivity contexts. A movement was considered facilitated, when displacement was rapidly engaged and individuals moved a long distance from their wooded patch. Moth and passerine movement patterns differed between the two connectivity contexts: moth recapture rates were higher in highly connecting contexts than in less connecting contexts. For passerine birds, responses to playback recalls were faster and movement distance longer in highly connecting contexts. All results support the hypothesis that both taxa were more prone to move in corridors modelled by LCP. Synthesis and applications. The convergence of the results for different biological models and across cities strengthens the relevance of LCP analysis for planning urban greenways and provides guidelines for landscape planners in the development of these corridors to favour the movement and survival of multiple urban species.

Quantifying effects of socioeconomic development on urban landscape fragmentation

Quantifying effects of socioeconomic development on urban landscape fragmentation

Assessment of Point-Based Fragmentation Using Geospatial Technology and Markov Chain Analysis: A Case Study of Kamrup Districts (Rural and Metro), Assam, India

This study aims to demonstrate the utility of Markov chain analysis and geospatial technology to assess point-based fragmentation. It has been observed that unprecedented urbanization is primarily responsible for abrupt changes in the land system of cities. Such abrupt changes may lead to fragmentation of urban landscape and its neighbourhood areas. Generally, fragmentation begins with point locations and may convert into line- and polygon-based fragmentations. This is necessary to understand that fragmentation has negative consequences on the habitat suitability and ecosystem of a city. Consequently, this may also affect the environment in the context of sustainability. Hence, the present work proposes a framework to identify the possible hot spots of point-based fragmentation. This may help in containing landscape fragmentation. It begins with identification of zones which are more vulnerable to fragmentation using Markov chain analysis. Next, the zone-based vulnerability analysis has been downscaled to point-based fragmentation using block statistics-based spatial overlay operation. Results of the proposed framework have been validated through field survey. It has been found that landscape is fragmenting in the identified hot spots by the proposed framework. Effective measures for containing point-based fragmentation in these places may be adopted to avoid the conversion of point-based fragmentation into either line-based or polygon-based fragmentation.

More fragmentized urban form more CO2 emissions? A comprehensive relationship from the combination analysis across different scales

Abstract Scientifically delineating the spatial heterogeneity of urban landscape fragmentation in relation to CO2 emissions helps the urban carbon mitigation strategy. The combination analysis across spatial resolutions, which is rare, helps explore the comprehensive relationship between urban fragmentation and CO2 emissions. This study compared the relationships between urban form fragmentation and CO2 emissions in an urban system through the analytic framework composed of the Pearson correlation analysis, geographically weighted regression (GWR), and geographical detector methods with the use of multi-source data to construct the CO2 emissions maps. As the result, there was less fragmentation with a 500-m spatial resolution (R500m) than with a 30-m spatial resolution (R30m). In terms of the GWR analysis, the coarse resolution resulted in: 1) positive coefficients of fragmentation metric becoming negative, and 2) greater absolute values of negative coefficients. As to the results of Geographical detector, single factor impact powers and interactions among fragmentation factors showed a weakening effect at R30m, but a strengthening and weakening effect at R500m. However, there were common results observed in low-fragmented areas across different scales. That is, in low-fragmented mixed-function areas and industrial areas, the more fragmented the area was, the less the CO2 emission there would be. However, in low-fragmented residential, administrative and public service areas, the more fragmented the area was, the higher the CO2 emission there would be. Therefore, the government should disperse the mixed function zones and industrial parcels with diverse types of land, and build the contiguous residential and public service land in the low fragmentation area of urban system. The results of this study can provide a reference for the other small and medium towns and cities. The analytical framework can be applied to CO2 emissions research in urban agglomerations, megacities, and small towns.

Dispersión y Escalamiento Urbano en el Sistema de Ciudades Chileno

La expansión espacial incesante de las ciudades, el aumento de la segregación socio-espacial y el aumento del nivel de emisiones afectan severamente al medio ambiente y conforman estructuras emergentes e
 insustentables. El enfoque de los sistemas complejos, la ecología urbana y la ecología del paisaje nos ayudan comprender algunas de las propiedades de este crecimiento urbano. Para ello, se estudia la dispersión del paisaje urbano de 43 ciudades y conglomerados urbanos chilenos, entre 1993, 2003 y 2011, utilizando distintas métricas del paisaje urbano: fragmentación, elongación y aislamiento, en base a coberturas del Observatorio Urbano (MINVU) y al procesamiento en el programa Fragstat. También, se realiza un escalamiento del tamaño de las ciudades según el nivel de emisiones de CO2 de manera exploratoria.
 Los resultados muestran que Santiago presenta los mayores porcentajes de fragmentación y el máximo crecimiento, junto con las ciudades Arica y Calama; la mayor parte experimentan procesos de elongación (Los Ángeles, Chillán e Iquique) y gran parte aumentan su aislamiento (Illapel, San Antonio y Copiapó). Por su parte, el escalamiento de las emisiones presenta un comportamiento sublineal (0,8). Los datos exhiben una alometría heterogénea que dependen estrechamente de la calidad de los datos utilizados, transitando de un modelo de ciudad relativamente compacto a uno difuso y disperso. Los métodos de simulación espacial de la dispersión y de escalamiento pueden servir como proxy para evaluar la sustentabilidad urbana, en la medida que ayudan a determinar la tendencia global de urbanización y pronosticar cómo evolucionarían los sistemas urbanos.

A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation

The combined use of remote sensing based land cover classification and landscape metrics has provided a positive step toward gaining a comprehensive understanding of the features of landscape structure. However, numerous limitations of land cover classification indicate that the utilization of classified thematic maps in landscape pattern analysis is questionable and may even lead to large errors in subsequent analyses. Instead of generating and employing detailed land cover classification maps, the utility of local spatial autocorrelation indices derived directly from satellite imagery to measure landscape fragmentation was examined. Since local spatial autocorrelation can capture spatial pattern at a local scale, it can be expected to detail the spatial heterogeneity for various parts of a landscape instead of providing a single value as in the case with the global measures. This study compares the traditional landscape metrics to the use of satellite imagery based local spatial autocorrelation measures in quantifying landscape structure over Phoenix urban area. Two local spatial autocorrelation indices, the Getis statistic and the local Moran's I were employed in evaluating landscape pattern, using normalized indices as the inputs. Results show that there is a clear relationship between local spatial autocorrelation indices and FRAGSTATS metrics. Both the Getis statistic and the local Moran's I can serve as useful indicators of landscape heterogeneity, for the entire landscape, and for different land use and land cover types. The paper provides a feasible methodology for urban planners and resource managers for effectively characterizing landscape fragmentation using continuous dataset.

Detecting spatially non-stationary and scale-dependent relationships between urban landscape fragmentation and related factors using Geographically Weighted Regression

Landscape fragmentation is usually caused by many different anthropogenic influences and landscape elements. Scientifically revealing the spatial relationships between landscape fragmentation and related factors is highly significant for land management and urban planning. The former studies on statistical relationships between landscape fragmentation and related factors were almost global and single-scaled. In fact, landscape fragmentations and their causal factors are usually location-dependent and scale-dependent. Therefore, we used geographically Weighted Regression (GWR), with a case study in Shenzhen City, Guangdong Province, China, to examine spatially varying and scale-dependent relationships between effective mesh size, an indicator of landscape fragmentation, and related factors. We employed the distance to main roads as a direct influencing factor, and slope and the distance to district centers as indirect influencing factors, which affect landscape fragmentation through their impacts on land use and urbanization, respectively. The results show that these relationships are spatially non-stationary and scale-dependent, indicated by clear spatial patterns of parameter estimates obtained from GWR models, and the curves with a characteristic scale of 12 km for three explanatory variables, respectively. Moreover, GWR models have better model performance than OLS models with the same independent variable, as is indicated by lower AICc values, higher Adjusted R 2 values from GWR and the reduction of the spatial autocorrelation of residuals. GWR models can reveal detailed site information on the different roles of related factors in different parts of the study area. Therefore, this finding can provide a scientific basis for policy-making to mitigate the negative effects of landscape fragmentation.

The effects of sensor spatial resolution and changing grain size on fragmentation indices in urban landscape

Satellite images are now used as the primary source of spatial information for landscape pattern analysis. Choosing data of proper resolution has always been a big problem for landscape pattern analysis using satellite images. However, the effects of remote sensor spatial resolution on urban landscape fragmentation have never been reported. In this study, landscape fragmentation of Shanghai was analysed using land use maps produced from TM and IRS‐PAN images, attempting to discover the effects of remote sensor spatial resolution on urban landscape fragmentation. Four landscape fragmentation indices were computed along a 51 km long and 9 km wide transect cutting across Shanghai with a moving window to detect the behaviour of landscape indices along the gradient of land use zones. The results showed that fragmentation indices were sensitive to varied spatial resolution and grain size, indicating that fine resolution data and small grain size of about 7.5 m might be optimal for urban fragmentation analysis. The behaviour of landscape indices along the gradient of land use zones suggests that urban fragmentation can be distinguished as occurring in two phases: dissection introduced by roads and shrinkage caused primarily by urban sprawl.