Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery |
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| Institution: | 1. USDA Forest Service, PNW Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, United States;2. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, United States;3. USDA Forest Service, RMRS Research Station, 507 25th Street, Ogden, UT 84401, United States;4. College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, United States;5. Google Switzerland GmbH, Zurich, CH 8002, Switzerland.;1. Integrated Remote Sensing Studio, Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada;2. Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia V8Z 1M5, Canada;1. U.S. Geological Survey, Geosciences and Environmental Change Science Center, PO Box 25046, MS 980, Lakewood, CO 80225, USA;2. Stinger Ghaffarian Technologies, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, 47914 252nd Street, Sioux Falls, SD 57198, USA;3. U.S. Geological Survey, Core Science, Analytics, Synthesis, and Libraries, PO Box 25046, MS 302, Lakewood, CO 80225, USA;4. Department of Ecology & Evolutionary Biology, University of Colorado Boulder, Boulder, CO 80309-0334, USA;5. ASRC Federal InuTeq LLC, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, 47914 252nd Street, Sioux Falls, SD 57198, USA;6. U.S. Geological Survey, Earth Resources Observation and Science Center, 47914 252nd Street, Sioux Falls, SD 57198, USA |
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| Abstract: | Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area. |
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| Keywords: | Forest regeneration Vegetation recovery Very high spatial resolution imagery Hyperspectral imagery Object-based classification |
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