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 in | Mountain research and development Vol. 32; no. 2; pp. 213 - 225 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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 |
Subjects | |
Online Access | Get full text |
ISSN | 0276-4741 1994-7151 |
DOI | 10.1659/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. |
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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 |
Author_xml | – sequence: 1 givenname: Zhang surname: Zhiming fullname: Zhiming, Zhang organization: Institute of Ecology and Geobotany, Yunnan University, Kunming 650091, China – sequence: 2 givenname: Frieke surname: Van Coillie fullname: Van Coillie, Frieke organization: Laboratory of Forest Management and Spatial Information, Ghent University, Ghent 9000, Belgium – sequence: 3 givenname: Robert surname: De Wulf fullname: De Wulf, Robert organization: Laboratory of Forest Management and Spatial Information, Ghent University, Ghent 9000, Belgium – sequence: 4 givenname: Eva M surname: De Clercq fullname: De Clercq, Eva M organization: Agriculture and Veterinary Intelligence and Analysis, Zoersel 2980, Belgium – sequence: 5 givenname: Ou surname: Xiaokun fullname: Xiaokun, Ou organization: Institute of Ecology and Geobotany, Yunnan University, Kunming 650091, China |
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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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