Introducing a new method for assessing spatially explicit processes of landscape fragmentation

Li, Shujuan; Yang, Bing

doi:10.1016/j.ecolind.2015.03.031

Cited by 33 publications

(31 citation statements)

References 28 publications

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“…First, the land use data used in this study were sourced from remote-sensing images and other institutions; however, the classification of images cannot be 100% correct, and the spatial misalignment of data may have resulted in incorrectly assessed pattern and processes of fragmentation [20]. Therefore, data processing is critical to reduce the misdetection of fragmentation.…”

Section: Limitations and Further Studiesmentioning

confidence: 99%

“…This study assessed the processes of landscape fragmentation at pixel level from Forman (1995) and the model of Li and Yang (2015). Forest patches converted from urban land, cropland, water or other land were regarded as forests in the measurement procedure.…”

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

“…Attrition occurs in the isolated forest patches. This method detects the spatial relationship between the lost and remaining areas of forest, to identify the different spatial processes of forest fragmentation, which have different impacts on the ecosystem [20]: for example, perforation and subdivision may result in a decrease in average size and an increase in total boundary length. Shrinkage and attrition Sustainability 2017, 9, 374 7 of 19 may result in a decrease in total boundary length; however, attrition also causes a decrease in patch number [18].…”

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

“…Forest patches converted from urban land, cropland, water or other land were regarded as forests in the measurement procedure. The spatial processes of landscape fragmentation, including perforation, subdivision, shrinkage, and attrition, were identified using a modified version of the model by Li and Yang (2015). Perforation is visible in the original forest patches, while shrinkage and subdivision always occur in the middle phases of landscape change [18].…”

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

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Forest Fragmentation and Driving Forces in Yingkou, Northeastern China

2017

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Forest fragmentation, the process of changing original large and intact forest patches into smaller and isolated areas, significantly influences the balance of surface physical environment, biodiversity, and species richness. Sufficient knowledge of forest fragmentation is necessary to maintain ecological balance and promote sustainable resource utilization. This study combines remote sensing, geographical information systems, and landscape metrics to assess forest fragmentation at landscape and pixel levels during different time periods (2000-2005, 2005-2010, and 2010-2015) in the Yingkou region. Spatial statistical analysis is also used to analyze the relationship between forest landscape fragmentation and its determinants (e.g., natural factors, socioeconomic factors, and proximity factors). Results show that forest patches became smaller, subdivided, and isolated during 2010-2015 at the total landscape level. Local changes occurred in the southwest of the study region or around the development area. Our data also indicate that shrinkage and subdivision were the main forest fragmentation processes during three times, and attrition became the main forest fragmentation process from 2010 to 2015. These changes were significantly influenced by natural factors (e.g., elevation and slope), proximity factors (e.g., distance to city and distance to province roads), and socioeconomic factors (e.g., gross domestic product). Results presented in this study provide valuable insights into the pattern and processes of forest fragmentation and present direct implications for the protection and reasonable utilization of forest resources.

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Section: Limitations and Further Studiesmentioning

confidence: 99%

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

Section: Forest Fragmentation Processes At Pixel Levelmentioning

confidence: 99%

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