Physical and Environmental Geography Commons^™

Prototype For Monitoring And Forecasting Fall Foliage Coloration In Real Time From Satellite Data, Xiaoyang Zhang, Mitchell D. Goldberg, Yunyue Yu

GSCE Faculty Publications

While determining vegetation phenology from the time series of historical satellite data has been widely investigated throughout the last decade, little effort has been devoted to real-time monitoring and short-term forecasting. The latter is more important for numerical weather modeling, ecosystem forecasting, forest and crop management, and health risk warning. In this study we developed a prototype approach for the real-time monitoring and short-term forecasting of fall foliage status (including low coloration, moderate coloration, near-peak coloration, peak coloration, and post-peak coloration) using temporal satellite observations. The algorithm combined the climatology of vegetation phenology and temporally available satellite observations to establish …

Remote Sensing-Based Time Series Models For Malaria Early Warning In The Highlands Of Ethiopia, A. Midekisa, G. Senay, G. M. Henebry, P. Semuniguse, M. C. Wimberly

Natural Resource Management Faculty Publications

Background

Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. …

Sensitivity Analysis Of The Gems Soil Organic Carbon Model To Land Cover Land Use Classification Uncertainties Under Different Climate Scenarios In Senegal, Amadou M. Dieye, David P. Roy, N. P. Hanan, S. Lui, M. Hansen, A. Toure

GSCE Faculty Publications

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat …

Alternative Methods To Predict Actual Evapotranspiration Illustrate The Importance Of Accounting For Phenology: The Event Driven Phenology Model Part Ii, V. Kovalskyy, G. M. Henebry

Natural Resource Management Faculty Publications

Evapotranspiration (ET) flux constitutes a major component of both the water and energy balances at the land surface. Among the many factors that control evapotranspiration, phenology poses a major source of uncertainty in attempts to predict ET. Contemporary approaches to ET modeling and monitoring frequently summarize the complexity of the seasonal development of vegetation cover into static phenological trajectories (or climatologies) that lack sensitivity to changing environmental conditions. The Event Driven Phenology Model (EDPM) offers an alternative, interactive approach to representing phenology. This study presents the results of an experiment designed to illustrate the differences in ET arising from various …

A New Concept For Simulation Of Vegetated Land Surface Dynamics: The Event Driven Phenology Model Part I, V. Kovalskyy, G. M. Henebry

Natural Resource Management Faculty Publications

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing …