The Experts below are selected from a list of 29979 Experts worldwide ranked by ideXlab platform
Darla K. Munroe - One of the best experts on this subject based on the ideXlab platform.
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Monitoring Landscape Fragmentation in an inaccessible mountain area: Celaque National Park, Western Honduras
Landscape and Urban Planning, 2007Co-Authors: Darla K. Munroe, Harini Nagendra, Jane SouthworthAbstract:Many protected areas across the world are in locations marginal for human uses. Debate remains about the impact of these parks on land-cover change, which may be confounded by the role played by the biophysical Landscape. To test whether parks limit Landscape Fragmentation due to their designated protection or biophysical location, one must control for features that render the park inaccessible. We examine the effect of Celaque National Park, Honduras, on Landscape Fragmentation from 1987 to 2000 using remote sensing, GIS and Landscape pattern analysis. Multivariate analyses of variance and covariance were conducted to examine differences in Landscape Fragmentation within the park and the surrounding Landscape adjusting for differences in accessibility. Indicators of patch Fragmentation were significantly correlated with slope, elevation and distance to roads. Different management categories within the park were found to have significant differences in land-cover change and Landscape Fragmentation, and the impact of management category was even more significant after accounting for the differences in accessibility that exist across these zones. Thus, the park boundaries have been important in mediating land-cover change pressures, even after accounting for the substantial differences in the accessibility of forestland for conversion to agricultural land use
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land use policy and Landscape Fragmentation in an urbanizing region assessing the impact of zoning
Applied Geography, 2005Co-Authors: Darla K. Munroe, Cynthia Croissant, Abigail M YorkAbstract:Abstract The research presented here explores the spatial patterns in the Landscape near Bloomington, Indiana, where urban and suburban development is expanding into formerly agricultural and forested areas. Landscape Fragmentation has potentially detrimental impacts on provision of services and functions of forest ecosystems. We investigate the statistical relationship between Landscape Fragmentation and various socioeconomic, biophysical, and spatial variables associated with land use and land cover at the scale of individual, privately owned parcels. We find that the diversity of land uses is much higher, at the aggregate level and at the parcel level, in areas that are zoned to allow for the highest density in housing and smallest lot sizes. These results are still robust after accounting for key geophysical and accessibility characteristics of the individual parcels.
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land cover change and Landscape Fragmentation comparing the utility of continuous and discrete analyses for a western honduras region
Agriculture Ecosystems & Environment, 2004Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
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Land cover change and Landscape Fragmentation—comparing the utility of continuous and discrete analyses for a western Honduras region
Agriculture Ecosystems & Environment, 2003Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
Harini Nagendra - One of the best experts on this subject based on the ideXlab platform.
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Monitoring Landscape Fragmentation in an inaccessible mountain area: Celaque National Park, Western Honduras
Landscape and Urban Planning, 2007Co-Authors: Darla K. Munroe, Harini Nagendra, Jane SouthworthAbstract:Many protected areas across the world are in locations marginal for human uses. Debate remains about the impact of these parks on land-cover change, which may be confounded by the role played by the biophysical Landscape. To test whether parks limit Landscape Fragmentation due to their designated protection or biophysical location, one must control for features that render the park inaccessible. We examine the effect of Celaque National Park, Honduras, on Landscape Fragmentation from 1987 to 2000 using remote sensing, GIS and Landscape pattern analysis. Multivariate analyses of variance and covariance were conducted to examine differences in Landscape Fragmentation within the park and the surrounding Landscape adjusting for differences in accessibility. Indicators of patch Fragmentation were significantly correlated with slope, elevation and distance to roads. Different management categories within the park were found to have significant differences in land-cover change and Landscape Fragmentation, and the impact of management category was even more significant after accounting for the differences in accessibility that exist across these zones. Thus, the park boundaries have been important in mediating land-cover change pressures, even after accounting for the substantial differences in the accessibility of forestland for conversion to agricultural land use
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land cover change and Landscape Fragmentation comparing the utility of continuous and discrete analyses for a western honduras region
Agriculture Ecosystems & Environment, 2004Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
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Land cover change and Landscape Fragmentation—comparing the utility of continuous and discrete analyses for a western Honduras region
Agriculture Ecosystems & Environment, 2003Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
Jane Southworth - One of the best experts on this subject based on the ideXlab platform.
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Monitoring Landscape Fragmentation in an inaccessible mountain area: Celaque National Park, Western Honduras
Landscape and Urban Planning, 2007Co-Authors: Darla K. Munroe, Harini Nagendra, Jane SouthworthAbstract:Many protected areas across the world are in locations marginal for human uses. Debate remains about the impact of these parks on land-cover change, which may be confounded by the role played by the biophysical Landscape. To test whether parks limit Landscape Fragmentation due to their designated protection or biophysical location, one must control for features that render the park inaccessible. We examine the effect of Celaque National Park, Honduras, on Landscape Fragmentation from 1987 to 2000 using remote sensing, GIS and Landscape pattern analysis. Multivariate analyses of variance and covariance were conducted to examine differences in Landscape Fragmentation within the park and the surrounding Landscape adjusting for differences in accessibility. Indicators of patch Fragmentation were significantly correlated with slope, elevation and distance to roads. Different management categories within the park were found to have significant differences in land-cover change and Landscape Fragmentation, and the impact of management category was even more significant after accounting for the differences in accessibility that exist across these zones. Thus, the park boundaries have been important in mediating land-cover change pressures, even after accounting for the substantial differences in the accessibility of forestland for conversion to agricultural land use
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land cover change and Landscape Fragmentation comparing the utility of continuous and discrete analyses for a western honduras region
Agriculture Ecosystems & Environment, 2004Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
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Land cover change and Landscape Fragmentation—comparing the utility of continuous and discrete analyses for a western Honduras region
Agriculture Ecosystems & Environment, 2003Co-Authors: Jane Southworth, Darla K. Munroe, Harini NagendraAbstract:Abstract Current studies of land cover change and Landscape Fragmentation rely predominantly on land cover classifications derived from remotely sensed images. However, limitations of traditional land cover classifications are numerous and well known. This research compares classification-based techniques (discrete data) to the use of vegetation indices (continuous data) for land cover modeling and analyses of Landscape Fragmentation for a study area in western Honduras. The study area typifies many regions of tropical developing countries, where a complex interaction of social and environmental factors have given rise to a dynamic mosaic of patches of reforestation and deforestation. Understanding the complex human dimensions of land use and land cover change in these parts of the world continues to present a challenge for researchers. The land cover modeling analysis compares two models using different formulations for the dependent variable: (i) a continuous analysis using a tobit model regressing the normalized difference vegetation index (NDVI), with non-forest values truncated at 0, on the variables elevation, slope, distance from roads and distance from the nearest market; and (ii) a discrete analysis using a probit model with threshold NDVI coverages (representing forest and non-forest). To examine the patterns of Landscape Fragmentation, a discrete analysis of a forest/non-forest classification using the software FRAGSTATS is compared to a continuous NDVI-based analysis using the local indicator of spatial association (LISA) statistic. Estimated marginal effects and overall predictive power are compared across the tobit and probit formulations. Because the tobit formulation included variation in the dependent variable for forested areas, greater information was retained regarding the subtle relationships among the independent variables and land cover. The LISA statistic, using the NDVI coverages as input, were helpful in the interpretation of the data and its spatial arrangement in the Landscape, indicating that the LISA was a good complement to the FRAGSTATS, classification-based analysis. Given the LISA statistic is parametric and hence subject to outliers, whereas Landscape metrics tend to be non-parametric, we found that the use of both FRAGSTATS and LISA together was more beneficial than either analysis by itself. While there is increasing awareness of the need for using continuous data for land cover modeling and Fragmentation, this area remains little explored. The research presented provides insights for additional future applications utilizing continuous data analyses.
Jochen A. G. Jaeger - One of the best experts on this subject based on the ideXlab platform.
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Multi-scale mismatches between urban sprawl and Landscape Fragmentation create windows of opportunity for conservation development
Landscape Ecology, 2016Co-Authors: Aurora Torres, Jochen A. G. Jaeger, Juan C. AlonsoAbstract:Context Urban sprawl and the expanding transportation infrastructure drive land consumption and Landscape Fragmentation, causing environmental deterioration and loss of species. Current understanding of how these drivers interact to shape Landscape Fragmentation is still poor. However, a strong correlation between urban sprawl and Landscape Fragmentation patterns is commonly assumed.
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Landscape Fragmentation in Europe. Joint EEA-FOEN report. EEA Report No 2/2011.
2011Co-Authors: Jochen A. G. Jaeger, Tomas Soukup, L. Francisco Madrinan, Christian Schwick, Felix KienastAbstract:Landscape Fragmentation in Europe Landscape Fragmentation caused by transportation infrastructure and built-up areas has a number of ecological effects. It contributes significantly to the decline and loss of wildlife populations and to the increasing endangerment of species in Europe, for example through the dissection and isolation of populations, and affects the water regime and the recreational quality of Landscapes. In spite of the planning concept of preserving large unfragmented areas, Fragmentation has continued to increase during the last 20 years, and many more new transportation infrastructure projects are planned, in particular in eastern Europe, which will further increase the level of Landscape Fragmentation significantly. Therefore, data on the degree of Landscape Fragmentation are needed that are suitable for comparing different regions, especially in relation to different natural Landscape types and different socioeconomic conditions. This report quantitatively investigates the degree of Landscape Fragmentation in 28 countries in Europe for the first time for three different Fragmentation geometries at three levels. The three levels include countries, regions (NUTS-X, according to the Nomenclature of Statistical Territorial Units), and a grid of 1 km2 cells (LEAC grid, which is used for Land and Ecosystem Accounting activities). The report applies the method of 'effective mesh density' which quantifies the degree to which the possibilities for movement of wildlife in the Landscape are interrupted by barriers. The effective mesh density values across the 28 investigated countries cover a large range, from low values in large parts of Scandinavia to very high values in western and central Europe. Many highly fragmented regions are located in Belgium, the Netherlands, Denmark, Germany, France, Poland and the Czech Republic. High Fragmentation values are mostly found in the vicinity of large urban areas and along major transportation corridors. The lowest levels of Fragmentation are usually associated with mountain ranges or remoteness. Fragmentation geometry B2 'Fragmentation of non-mountainous land areas' which includes highways up to class 4, railways and urban areas, is the most important Fragmentation geometry, as it is suitable for comparing regions with differing geographical conditions like different amounts of mountains or lakes; it also encompasses the most complete set of physical barriers that may affect a large number of species. Predictive models of Landscape Fragmentation In the second part, this report investigates potential causes that contribute to an increased or decreased degree of Landscape Fragmentation and determines their relative importance. The density of the transportation network and the extent of Landscape Fragmentation are largely a function of interacting socioeconomic drivers such as population density and geophysical factors such as topography. Current levels of Landscape Fragmentation need to be interpreted within the context of these regional socioeconomic and geophysical conditions. Therefore, this report applies a set of statistical models to determine which of these factors drive the process of Landscape Fragmentation in Europe. We analysed the statistical relationships between Landscape Fragmentation and a range of predictive variables, applied these relationships to predict the likely Fragmentation values for all regions in our study area, and compared actual values with predicted values. In general, the most relevant variables affecting Landscape Fragmentation were population density, gross domestic product per capita, volume passenger density, and the quantity of goods loaded and unloaded per capita. The amount of variation in the level of Fragmentation that was explained by the predictor variables was high, ranging from 46 % to 91 % in different parts of Europe. The statistical relationships indicated that different drivers of Landscape Fragmentation are important in different parts of Europe. Efforts for curtailing Landscape Fragmentation should take these differences into account. Relevance for monitoring systems and policymaking The results demonstrate that there is an urgent need for action. Large discrepancies between predicted and observed Fragmentation values provide a basis for identifying areas for prioritising management action. Such data also provide a starting point for scenarios for the future development of Landscape Fragmentation in Europe. There is an increasing need and interest in including indicators of Landscape Fragmentation in monitoring systems of sustainable development, biodiversity, and Landscape quality. We recommend that the results presented in this report be used for this purpose and be updated on a regular basis to detect trends in the development of Landscape Fragmentation. Therefore, this report discusses the use of Fragmentation analysis presented in this report as a tool for performance review in transportation planning and regional planning and recommends a set of measures to control Landscape Fragmentation, such as more effective protection of remaining unfragmented areas and wildlife corridors, the setting of targets and limits and a European deFragmentation strategy. This study provides for the first time an accurate measurement of Landscape Fragmentation for most of the European continent, which supports managers and policymakers in allocating resources towards the protection and restoration of biodiversity and Landscape quality. The report also identifies future research needs.
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implementing Landscape Fragmentation as an indicator in the swiss monitoring system of sustainable development monet
Journal of Environmental Management, 2008Co-Authors: Jochen A. G. Jaeger, Christian Schwick, Rene Bertiller, Kalin Muller, Charlotte Steinmeier, Klaus C Ewald, Jaboury GhazoulAbstract:Abstract There is an increasing need and interest in including indicators of Landscape Fragmentation in monitoring systems of sustainable Landscape management. Landscape Fragmentation due to transportation infrastructure and urban development threatens human and environmental well-being by noise and pollution from traffic, reducing the size and viability of wildlife populations, facilitating the spread of invasive species, and impairing the scenic and recreational qualities of the Landscape. This paper provides the rationale, method, and data for including Landscape Fragmentation in monitoring systems, using as an example the Swiss Monitoring System of Sustainable Development ( Monet ). We defined and compared four levels of Fragmentation analysis, or Fragmentation geometries (FGs), each based on different fragmenting elements, e.g., only anthropogenic, or combinations of anthropogenic and natural elements. As each FG has specific strengths and weaknesses, the most appropriate choice of FG depends on the context and objectives of a study. We present data on the current degree of Landscape Fragmentation for the five ecoregions and 26 cantons in Switzerland for all four FGs. Our results show that the degree of Landscape Fragmentation as quantified by the effective mesh size method is strongly supported by the postulates and indicator selection criteria of Monet , and we identify the most suitable FG focusing on the land area below 2100 m (e.g., excluding lakes) and allowing for an equitable comparison of Fragmentation degrees among regions that differ in area covered by lakes and high mountains. For a more detailed analysis of Landscape Fragmentation in the context of environmental impact assessments and strategic environmental assessments, a combination of all four FGs may provide a more informative tool than any single FG.
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integration of Landscape Fragmentation analysis into regional planning a statewide multi scale case study from california usa
Landscape and Urban Planning, 2008Co-Authors: Evan H Girvetz, Jochen A. G. Jaeger, James H Thorne, Alision M BerryAbstract:Landscape Fragmentation due to urban development, transportation infrastructure, and agriculture poses a threat to environmental integrity. There is a need to quantify the level of Landscape Fragmentation in an ecologically meaningful way for inclusion in planning and decision-making. Effective mesh size (meff )i s an ecologically relevant metric that quantifies Landscape Fragmentation based on the probability that two randomly chosen points in a region are located in the same non-fragmented patch. We investigated variation in meff measured by transportation districts, municipal counties, and six spatial levels of watersheds within the state of California. Four Fragmentation geometries were developed by overlaying highways, roads, urbanized areas, agricultural areas, and natural fragmenting features. Two meff calculation methods were compared: one where planning unit boundaries fragment the Landscape (CUT), the other allowing for cross-boundary connections (CBC). The CUT procedure always produced lower meff values than CBC, with greater differences occurring in smaller planning units, confirming the bias introduced using boundaries with Landscape metrics. Calculated meff values varied from 0 to 20 885 km 2 across 6994 units in California. Roads contributed the most to Fragmentation, while agriculture contributed little, as California’s agricultural areas are already heavily fragmented by roads. This paper provides a systematic, quantitative, and intuitive method for transportation, land use and environmental planners to analyze cumulative impacts of multiple fragmenting features across a range of spatial scales within a variety of planning units. This approach could be used for analyzing the impact of future land development scenarios, and integrated into regional planning processes. © 2008 Elsevier B.V. All rights reserved.
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Modification of the effective mesh size for measuring Landscape Fragmentation to solve the boundary problem
Landscape Ecology, 2007Co-Authors: Brigitte Moser, Jochen A. G. Jaeger, Ulrike Tappeiner, Erich Tasser, Beatrice EiseltAbstract:Patch-based Landscape metrics can be biased by the boundaries and the extent of a reporting unit if the boundaries fragment patches. We call this the “boundary problem”. The effective mesh size m _eff is a convenient method to quantify Landscape Fragmentation, that is based on the probability that two points chosen randomly in a region will be connected, e.g., not be separated by roads, railroads, or urban development. The cutting-out (CUT) procedure, used in the original computation of m _eff, suffers from the boundary problem because the boundaries of the reporting units are considered to be additional barriers. Therefore, m _eff will be underestimated, particularly if reporting units are embedded within the broader Landscape. In this paper, we present a solution to overcome this limitation by a new method called “cross-boundary connections” (CBC) procedure. It attributes the connections between two points that are located in different reporting units to both reporting units. We systematically compare the CBC procedure to the CUT procedure and show that the boundary problem is intrinsic to the CUT procedure, while the CBC procedure is independent of the size and administrative boundaries of reporting units. In addition, we elucidate the superior performance of the new procedure in the case study of South Tyrol where m _eff is being used for sustainability reporting on the level of municipalities. The new CBC procedure eliminates the bias due to the boundaries and the size of reporting units in measuring Landscape Fragmentation through m _eff.
Kukuh Murtilaksono - One of the best experts on this subject based on the ideXlab platform.
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Tropical Forest Landscape Fragmentation in Batang Toru Watershed, North Sumatra
2014Co-Authors: Samsuri Samsuri, I Nengah Surati Jaya, Cecep Kusmana, Kukuh MurtilaksonoAbstract:Timber-based forest management is now shifting to as broader scope including ecosystem-based management. Timber-oriented forest management frequently affects the Fragmentation of forest Landscape. This paper defines the degree of forest Landscape Fragmentation in Batang Toru watershed, North Sumatra through indentification of correlation between forest Landscape Fragmentation and driving factors including biophysical and anthropogenic factors. Identification structure, pattern, and Fragmentation of forest Landscape were performed using Landsat imageries acquired in 1989, 2001, and 2013. Forest and land cover classes were analyzed using FRAGSTAT 3.3 to generate Landscape metrics. Fragmentation of forest Landscape was identified using Landscape metrics, i.e., area, patch density, number of patch, contiguity and proximity index. The clumpiness index of Landscape metrics describes the pattern of forest Landscape, while the patch size proportions expressed structure of forest Landscape. This study found that forest Landscapes located in downstream of the watershed show more fragmented than area in the upper stream, while the sub-watershed of Batang Toru Hilir is more clumped than the others. This study concludes that (1) the forest Landscape Fragmentation tend to increase since 1989 to 2013; and (2) the degree of forest Landscape Fragmentation has close correlation with the distance to main road and river.
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Analysis of Tropical Forest Landscape Fragmentation in Batang Toru Watershed, North Sumatra
2014Co-Authors: Samsuri Samsuri, I Nengah Surati Jaya, Cecep Kusmana, Kukuh MurtilaksonoAbstract:Timber-based forest management is now shifting to as broader scope including ecosystem-based management. Timber-oriented forest management frequently affects the Fragmentation of forest Landscape. This paper defines the degree of forest Landscape Fragmentation in Batang Toru watershed, North Sumatra through indentification of correlation between forest Landscape Fragmentation and driving factors including biophysical and anthropogenic factors. Identification structure, pattern, and Fragmentation of forest Landscape were performed using Landsat imageries acquired in 1989, 2001, and 2013. Forest and land cover classes were analyzed using FRAGSTAT 3.3 to generate Landscape metrics. Fragmentation of forest Landscape was identified using Landscape metrics, i.e., area, patch density, number of patch, contiguity and proximity index. The clumpiness index of Landscape metrics describes the pattern of forest Landscape, while the patch size proportions expressed structure of forest Landscape. This study found that forest Landscapes located in downstream of the watershed show more fragmented than area in the upper stream, while the sub-watershed of Batang Toru Hilir is more clumped than the others. This study concludes that (1) the forest Landscape Fragmentation tend to increase since 1989 to 2013; and (2) the degree of forest Landscape Fragmentation has close correlation with the distance to main road and river.
