- Related Research Areas
- Carbon Cycle & Ecosystems
The spatial arrangement of forest structure (structural heterogeneity) has been linked to habitat availability for several taxa making it of particular interest for biodiversity conservation through the sustainable management of tropical forests. Our project has two different objectives with complementary approaches, methods, and expected outcomes. First, we seek to extend, evaluate, and refine our protocol for linkage passive optical imagery with changes in biodiversity indicators as a function of forest management. This first objective is much needed translational science within the context of sustainable tropical forest management and will focus on passive optical data that are readily available to forest managers. We propose to take advantage of a unique confluence of extensive geospatial data on forest stand management with a rich set of passive optical data to establish algorithms and operational protocols to relate the spatial and spatio-temporal heterogeneity quantifiable within optical imagery with diversity measures of key forest health indicator groups. We will use of both repeated observations at particular locations and space-for-time substitutions to exploit to full advantage available imagery and ground data. Second, we seek to explore and assess the efficacy of advanced lacunarity analyses applied to lidar and radar data to characterize tropical forest spatial heterogeneity. This second objective is discovery science or basic research and looks to the kinds of active sensor data that may routinely available in the middle of the next decade on a platform such as the DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice) mission that is currently being scoped out by NASA and the earth science community. We propose to investigate the use of advanced lacunarity analyses to characterize and assess the spatial heterogeneity of tropical forest structure as capture through active optical (LiDAR) and active microwave (RaDAR) data. While the passive optical analyses will focus on 2D heterogeneities through time, the analyses of active sensor data will concentrate on exploiting the various possible slices of 3D data both at single and multiple dates. These analyses will also benefit from access to the geospatial data regarding forest stand management and similarly use space-for-time substitution to leverage extant data. This project focuses on a well-studied ecosystem: the tropical forests along the Atlantic Slope of Costa Rica. We leverage the considerable and growing archive of spaceborne and airborne imagery with geospatial forest management data from (1) FUNDECOR, a well-respected Costa Rican NGO that works with private landholders and the government of Costa Rica on the implementation of sustainable forestry, (2) the Tropical Agronomic Research and Higher Education Center (CATIE), and (3) the recently established Costa Rican National Natural Forests Permanent Plots Network.
Project PI: Geoffrey M. Henebry/South Dakota State University
Geographic Information Science Center of Excellence (GIScCE) 1021 Medary Ave., Wecota Hall Box 506B, Brookings, SD 57007
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