Abstract
Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.
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Acknowledgments
The research reported in this paper was partially supported by Department of Geography, Florida State University and College of Health, Environment and Science, Slippery Rock University of Pennsylvania. We thank Basil Savitsky, Christine Ambrose, Joe Noble, and Jim Cox for their assistance in field-based reference data collection and data processing and analysis. We also thank Frances James, James Elsner, Jon Anthony Stallins and Mark Horner for their help in this work. Acknowledgements are due to Shawn Lewers for providing computer support, Ann Johnson and Chengxia You for their help in interpreting aerial photos, Jean-Paul Calixte and Mary Litrico for providing hydrological data, and Stuart Jackson for providing the information about forests in the study area. Last, we thank the three anonymous referees for their time and effort in reviewing the earlier version of the manuscript, which helped improve its scholarly quality.
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Wang, J., Yang, X. A Hierarchical Approach to Forest Landscape Pattern Characterization. Environmental Management 49, 64–81 (2012). https://doi.org/10.1007/s00267-011-9762-9
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DOI: https://doi.org/10.1007/s00267-011-9762-9