Emerging geospatial science and technology for sustainable bioenergy

Abstract

With recent national emphasis on increasing biofuel development for reducing dependency on foreign oil and reducing carbon emissions from energy production and consumption, the agricultural land cover and land use patterns in the United States and many other regions of the world are expected to change in the coming years. Although remote sensing data analysis is a well recognized approach for addressing bioenergy sustainability, biomass monitoring over large geographic regions using remote sensing images poses several scientific and technical challenges.Data Challenges. There is great need for continuous coverage of high-temporal data with moderate to fine spatial resolution. Panel will discuss data challenges in monitoring biomass at regional and global scales, takes a view on current and future satellite programs.Analytical Challenges: Conventional techniques are either inadequate or do not scale well for continuous biomass monitoring over large geographic regions. Panel will discuss the recent advances in spatiotemporal data mining, especially the techniques that exploit the subtle multidimensional signals through the joint use of high temporal resolution (MODIS) data and moderate-and fine-spatial resolution satellite images for extracting multi-temporal biomass change information, including crop types and their conditions. Computational Challenges: Scaling spatiotemporal data mining techniques for large geographic regions is a computationally challenging task. Panel will discuss the challenges in embracing modern computing infrastructure, especially distributed and cloud computing for biomass and bioenergy monitoring and simulation needs.In addition, this panel discusses recent government programmatic initiatives in the area of biomass and bioenergy.