Integrating small-scale landscape elements into land use/cover: The impact on landscape metrics’ values |
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| Institution: | 1. Key Laboratory of Remote Sensing of Gansu Province, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;2. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China;3. State Key Laboratory of Resources & Environmental Information System, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, A11, Datun Road, Beijing 100101, China;4. Heihe Water Resources and Ecological Protection Research Center, Heihe River Bureau, Yellow River Conservancy Commission of the Ministry of Water Resources, Lanzhou 730000, China;1. Campus of Sorocaba – São Paulo State University, 511, Três de Março Av., Alto da Boa Vista, 18087-180 Sorocaba, SP, Brazil;2. National Soil Erosion Research Laboratory, West Lafayette, IN, USA;3. International Center for Tropical Agriculture (CIAT), Av. La Molina 1581, La Molina, Lima, Peru;4. Center for Water and Air Quality, Florida A&M University, USA;5. Northeastern Illinois University, USA;1. Department of Landscape Architecture, Warsaw University of Life Sciences - SGGW, Nowoursynowska 159 St., 02-776 Warsaw, Poland;2. Department of Geoinformatics - Z_GIS, Schillerstr. 30, Building 15, 3rd Floor, 5020 Salzburg, Austria;1. College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai Street, Haidian, Beijing, 100875, PR China;2. Department of Geography, University of Cambridge, Downing Place, Cambridge CB2 3EN, UK;3. School of Environment, Tsinghua University, Haidian, Beijing 100084, PR China |
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| Abstract: | Over the last 30 years the use and misuse of landscape metrics has been widely studied. However, there has been less attention on incorporating small-scale landscape elements into landscape analysis. Data type used in the analysis can be either vector or raster, while the raster format is more widely used. However, using large-scale topographical vector databases has several advantages – they cover whole countries with very detailed and accurate topographical data. Despite the high level of detail, their amount in Mb is small, which allows simultaneously to analyse large areas. The peculiarity of vector data is that small-scale landscape elements are mapped as point elements or lines. For calculating landscape metrics, the integration of these features and LULC (land use/cover) polygons is needed. In the current study we investigated how integration of point and linear elements into polygon layers affects the values of landscape metrics. Adding line buffers influenced metrics’ values more than adding point elements. The ensemble of point and linear objects is similar to linear objects. Our study revealed that integrating small-scale landscape elements into land use/cover layers by using buffers gives more realistic values if the buffer size is in compliance with the size of the phenomena in the real world and suitable landscape metrics are chosen. However, the metrics that responded to adding small-scale landscape elements in correspondence with their real world impact on landscape metric values might not always be the best ecological indicators in terms of small-scale landscape elements. Another issue is that values of landscape metrics depend directly on the number of classes determined in the data specification, and on the data model. If the number of mappable point and linear objects changes, or the data model of the linear objects changes, the values of landscape metrics differ. |
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| Keywords: | Landscape metrics Topographic vector data Data model Data integration Uncertainties Small-scale landscape elements |
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