Comparison of Surface and Planimetric Landscape Metrics for Mountainous Land Cover Pattern Quantification in Lancang Watershed, China

Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically mean...

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Published inMountain research and development Vol. 32; no. 2; pp. 213 - 225
Main Authors Zhiming, Zhang, Van Coillie, Frieke, De Wulf, Robert, De Clercq, Eva M, Xiaokun, Ou
Format Journal Article
LanguageEnglish
Published Centre for Development and Environment (CDE), Institute of Geography, University of Bern Hallerstrasse 10, CH–3012 Bern, Switzerland The International Mountain Society 01.05.2012
International Mountain Society
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Online AccessGet full text
ISSN0276-4741
1994-7151
DOI10.1659/MRD-JOURNAL-D-10-00119.1

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Abstract Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically meaningful terrain structures like terrain shape or elevation are not taken into account and valuable information is lost for further analysis. A method to compute LPIs in a surface structure has been developed by Hoechstetter et al, who calculated landscape patch surface area and surface perimeter from digital elevation models. In this paper, Hoechstetter's set of LPIs was used and extended. A parametric t-test was used to assess the differences between the commonly used planimetric metrics and the surface landscape metrics for quantification of a mountain vegetation pattern at 3 levels (patch, category, and landscape) and for natural and anthropogenic categories in the Lancang (Mekong) watershed in China. The results show that the surface-based metrics for area, perimeter, shape, and distance to nearest-neighbor metrics were significantly larger than the same metrics derived by a planimetric approach for patch, category, and landscape levels in 2 different mountainous areas. However, diversity and evenness metrics did not feature significant differences between the surface-based landscape and the landscape represented in the planar maps. When comparing the area metrics for natural and for anthropogenic categories, significantly larger differences between these categories were found when the surface approach was used. The common planimetric method may underestimate the differences between natural and anthropogenic categories on areas and mean patch area in steep mountain areas.
AbstractList Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically meaningful terrain structures like terrain shape or elevation are not taken into account and valuable information is lost for further analysis. A method to compute LPIs in a surface structure has been developed by Hoechstetter et al, who calculated landscape patch surface area and surface perimeter from digital elevation models. In this paper, Hoechstetter's set of LPIs was used and extended. A parametric t-test was used to assess the differences between the commonly used planimetric metrics and the surface landscape metrics for quantification of a mountain vegetation pattern at 3 levels (patch, category, and landscape) and for natural and anthropogenic categories in the Lancang (Mekong) watershed in China. The results show that the surface-based metrics for area, perimeter, shape, and distance to nearest-neighbor metrics were significantly larger than the same metrics derived by a planimetric approach for patch, category, and landscape levels in 2 different mountainous areas. However, diversity and evenness metrics did not feature significant differences between the surfacebased landscape and the landscape represented in the planar maps. When comparing the area metrics for natural and for anthropogenic categories, significantly larger differences between these categories were found when the surface approach was used. The common planimetric method may underestimate the differences between natural and anthropogenic categories on areas and mean patch area in steep mountain areas.
Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically meaningful terrain structures like terrain shape or elevation are not taken into account and valuable information is lost for further analysis. A method to compute LPIs in a surface structure has been developed by Hoechstetter et al, who calculated landscape patch surface area and surface perimeter from digital elevation models. In this paper, Hoechstetter's set of LPIs was used and extended. A parametric t-test was used to assess the differences between the commonly used planimetric metrics and the surface landscape metrics for quantification of a mountain vegetation pattern at 3 levels (patch, category, and landscape) and for natural and anthropogenic categories in the Lancang (Mekong) watershed in China. The results show that the surface-based metrics for area, perimeter, shape, and distance to nearest-neighbor metrics were significantly larger than the same metrics derived by a planimetric approach for patch, category, and landscape levels in 2 different mountainous areas. However, diversity and evenness metrics did not feature significant differences between the surfacebased landscape and the landscape represented in the planar maps. When comparing the area metrics for natural and for anthropogenic categories, significantly larger differences between these categories were found when the surface approach was used. The common planimetric method may underestimate the differences between natural and anthropogenic categories on areas and mean patch area in steep mountain areas. [PUBLICATION ABSTRACT]
Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is represented by a planar map, which depicts the projection of a nonflat surface into a 2-dimensional Cartesian space. As a result, ecologically meaningful terrain structures like terrain shape or elevation are not taken into account and valuable information is lost for further analysis. A method to compute LPIs in a surface structure has been developed by Hoechstetter et al, who calculated landscape patch surface area and surface perimeter from digital elevation models. In this paper, Hoechstetter's set of LPIs was used and extended. A parametric t-test was used to assess the differences between the commonly used planimetric metrics and the surface landscape metrics for quantification of a mountain vegetation pattern at 3 levels (patch, category, and landscape) and for natural and anthropogenic categories in the Lancang (Mekong) watershed in China. The results show that the surface-based metrics for area, perimeter, shape, and distance to nearest-neighbor metrics were significantly larger than the same metrics derived by a planimetric approach for patch, category, and landscape levels in 2 different mountainous areas. However, diversity and evenness metrics did not feature significant differences between the surface-based landscape and the landscape represented in the planar maps. When comparing the area metrics for natural and for anthropogenic categories, significantly larger differences between these categories were found when the surface approach was used. The common planimetric method may underestimate the differences between natural and anthropogenic categories on areas and mean patch area in steep mountain areas.
Author Van Coillie, Frieke
Zhiming, Zhang
De Wulf, Robert
De Clercq, Eva M
Xiaokun, Ou
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Snippet Landscape pattern structure can be quantified by landscape pattern indices (LPIs). One major drawback of the commonly used LPIs is that the landscape is...
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SubjectTerms Aerial photography
anthropogenic category
Anthropogenic factors
Ecology
Elevation
Environmental protection
Land cover
land cover pattern quantification
Land use
Landscape
Landscape ecology
Landscapes
Mountain areas
Mountain regions
MountainResearch
Mountains
natural category
planimetric landscape pattern index
Quantification
Remote sensing
Research and development
River ecology
Software packages
Studies
Surface areas
surface landscape pattern index
Sustainable agriculture
Systems knowledge
Vegetation
Vegetation patterns
Watersheds
Wildlife conservation
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Title Comparison of Surface and Planimetric Landscape Metrics for Mountainous Land Cover Pattern Quantification in Lancang Watershed, China
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