Dynamic land cover information: bridging the gap between remote sensing and natural resource management
Richard Thackway, School of Geography, Planning and Environmental Management, The University of Queensland
Leo Lymburner, National Earth Observation Group, Geoscience Australia
Juan Pablo Guerschman, Environmental Earth Observation Group, CSIRO Land and Water
Full Text: HTML
Environmental decision-makers are increasingly demanding detailed spatial coverages with high temporal frequency to assess trends and changes in the extent and condition of wetlands, species habitats, farmlands, forests, rangelands, soil, water, and vegetation. Dynamic land cover information can substantially meet these requirements. Access to satellite-based time series information provides an unprecedented opportunity to better focus natural resource management (NRM) in Australia. Opportunities include assessing the extent and condition of key assets, prioritizing investment in key localities and time periods, improving targeting of scarce public funding, and monitoring and evaluating the outcome of this investment to assist land managers in improving land management practices to meet wider community social, economic, and environmental goals. We illustrate how these key “decision points” can be enhanced by linking dynamic land cover information to a stepped “cycle” model. We use the stepped cycle model to present two case studies, the management of fire and soil erosion, which demonstrate the application of dynamic land cover information to improve NRM decision-making across three broad stakeholder groups (national, regional, local). We use the case studies to highlight how accurate dynamic land cover information has been used to improve the design and reporting of national NRM programs.
dynamic land cover; fractional ground cover; imagery archives; land management practices; natural resource management outcomes; on-ground actions, remote sensing
Copyright © 2013 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution-NonCommercial 4.0 International License. You may share and adapt the work for noncommercial purposes provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.