We propose to use NASA data, models and analysis techniques to enhance the decision capabilities concerning avian influenza (AI) and pandemic influenza risks at partner and end-user organizations. The DoD Global Emerging Infection Surveillance and Response System (GEIS) and the U.S. Naval Medical Research Unit-2 (NAMRU-2) are partner as well as end-user organizations. Our specific objectives are to enhance the capabilities for assessing AI risks for poultry farms and humans, and the capabilities for early detection of pandemic influenza. In particular, we will generate the spatio-temporal risks of H5N1 outbreaks for selected districts in Indonesia and Laos, plus short-term and mid-term influenza-like illness (ILI) forecasts for selected regions in Indonesia, Laos and the United States. We will use 14 NASA Earth sciences data products and model results. Neural network methods, textural-contextual classifier, and other analytic techniques currently used in a project funded by NASA Public Health Application Program will be adopted by this project for risk assessments. Controlling AI outbreaks brings substantially more benefits to the society than just the farms where the outbreaks occur. It spares extensive culling, preserves the livelihood of small farmers, and protects food security and biodiversity. The world is presently in Phase 3 of the Pandemic Alert Period; reducing poultry infection will significantly reduce human infection. Most importantly, it reduces the likelihood of genetic reassortment in co-infection and the appearance of pandemic causing virus strains. This proposal is related to NASA Strategic Sub-goal 3A -- study Earth from space to advance scientific understanding and meet societal needs. It contributes to the progress in expanding and accelerating the realization of societal benefits from Earth system science. The proposed work is in the category of Public Health Applications, and is also of significance for the Disaster Management and Homeland Security Applications.