Using LiDAR, RADAR, and Optical data to improve a NFMS in Kalimantan, Indonesia

Friday, 19 December 2014
Stephen C Hagen1, Sassan S Saatchi2, Bobby H Braswell Jr1, Michael W Palace3, William Salas1, Sarah Walker4, Dirk Hoekman5, Catherine Ipsan1, Sandra Brown4 and Franklin Sullivan6, (1)Applied Geosolutions, LLC, Durham, NH, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Complex System Research Center, Durham, NH, United States, (4)Winrock, Arlington, VA, United States, (5)Wageningen University, Wageningen, Netherlands, (6)University of New Hampshire Main Campus, Durham, NH, United States
Around the world, governments are establishing national forest monitoring systems (NFMS) that use a combination of remote sensing and ground-based forest carbon inventory approaches to estimate anthropogenic forest-related greenhouse gas emissions and removals. The NFMS forms the link between historical assessments and current/future assessments of forests, enabling consistency in the data and information to support the implementation of REDD+ activities. The creation of a reliable, transparent, and comprehensive NFMS is currently limited by a dearth of relevant data that are accurate, low-cost, and spatially resolved at subnational scales. With funding from a 3-year NASA Carbon Monitoring System project beginning in September 2013, we are developing, evaluating, and validating several critical components of an NFMS in Kalimantan, Indonesia, focusing on the use of LiDAR and radar imagery for improved carbon stock and forest degradation information. Here, we present results from an initial analysis of a spatially extensive set of LiDAR data collected across the Indonesian provinces on the island of Borneo together with RADAR and optical data. Our objectives are to evaluate sensor and platform tradeoffs systematically against in situ investments, as well as provide detailed tracking and characterization of uncertainty in a cost-benefit framework. Kalimantan is an ideal area to evaluate the use of remote sensing methods because measuring forest carbon stocks and their human caused changes with a high degree of certainty on the ground can be difficult. While our work focuses at the subnational scale for Kalimantan, we are targeting these methods for applicability across broader geographies and for implementation at various scales.