Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model

Evapotranspiration (ET) can be derived from satellite data using surface energy balance principles. METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) is one of the most widely used models available in the literature to estimate ET from satellite imagery. The Simplified Surface Energy Balance (SSEB) model is much easier and less expensive to implement. The main purpose of this research was to present an enhanced version of the Simplified Surface Energy Balance (SSEB) model and to evaluate its performance using the established METRIC model. In this study, SSEB and METRIC ET fractions were compared using 7 Landsat images acquired for south central Idaho during the 2003 growing season. The enhanced SSEB model compared well with the METRIC model output exhibiting an r2 improvement from 0.83 to 0.90 in less complex topography (elevation less than 2000 m) and with an improvement of r2 from 0.27 to 0.38 in more complex (mountain) areas with elevation greater than 2000 m. Independent evaluation showed that both models exhibited higher variation in complex topographic regions, although more with SSEB than with METRIC. The higher ET fraction variation in the complex mountainous regions highlighted the difficulty of capturing the radiation and heat transfer physics on steep slopes having variable aspect with the simple index model, and the need to conduct more research. However, the temporal consistency of the results suggests that the SSEB model can be used on a wide range of elevation (more successfully up 2000 m) to detect anomalies in space and time for water resources management and monitoring such as for drought early warning systems in data scarce regions. SSEB has a potential for operational agro-hydrologic applications to estimate ET with inputs of surface temperature, NDVI, DEM and reference ET.Evapotranspiration Energy balance Surface temperature NDVI METRIC

Agricultural Landscape Dynamics and Its Response in Seasonal Vegetation Activities in the Loess Plateau, Northern Shaanxi, China

Part 1: GIS, GPS, RS and Precision FarmingInternational audienceThe ecological and environmental conditions in semiarid areas are closely linked to landscape dynamics. This study examined the seasonal vegetation activities of landscape classes and dynamics in the Loess Plateau in North Shaanxi Province, China. Landscape dynamics were studied by comparing Landsat images in 1987 and 2007, and classified as landscape transitions, landscape variations and unchanged landscape. The characteristics of seasonal vegetation activities, such as dates for onset-of-greenness, peaks, and onset-of-senescence for landscapes were determined using Moderate Resolution Imaging Spectroradiometer (MODIS) 10-day vegetation index composite products (2002–2009). The landscape dynamics showed that some sloping croplands were converted to woodlands and grasslands. Vegetation activities responded diversely and seasonally to landscape classes and dynamics. Temporal analysis of the Normalized Difference Vegetation Index (NDVI) showed that the time of onset-of-greenness and onset-of-senescence were similar for all major landscape classes, while the time of peak vegetation activity was longer for tree than grass species. The analysis of seasonal vegetation activities and landscape dynamics indicated that seasonal vegetation activities were not only relative to landscape classes, but also affected by landscape dynamics

Remote Sensing for Monitoring Surface Water Quality Status and Ecosystem State in Relation to the Nutrient Cycle: A 40-Year Perspective

Delineating accurate nutrient fluxes and distributions in multimedia environments requires the integration of vast amounts of information. Such nutrient flows may be related to atmospheric deposition, agricultural runoff, and urbanization effect on surface and groundwater systems. Two types of significant undertakings for nutrient management have been in place for sustainable development. While many environmental engineering technologies for nutrient removal have been developed to secure tap water sources and improve the drinking water quality, various watershed management strategies for eutrophication control are moving to highlight the acute need for monitoring the dynamics and complexities that arise from nutrient impacts on water quality status and ecosystem state, both spatially and temporally. These monitoring methods and data are associated with local point measurements, air-borne remote sensing, and space-borne satellite images of spatiotemporal nutrient distributions leading to the generation of accurate environmental patterns. Within this context, several key water quality constituents, including total nitrogen, total phosphorus, chlorophyll-a concentration, colored dissolved organic matter (dissolved organic carbon or total organic carbon), harmful algal blooms (e.g., cyanobacterial toxins or microcystin concentrations), and descriptors of ecosystem states, such as total suspended sediment (or turbidity), transparency (e.g., Secchi disk depth), and temperature, will be of major concern. Considering the advancements, challenges, and accomplishments related to remote sensing technologies in the past four decades, we present a thorough literature review of contemporary state-of-the-art technologies of remote sensing platforms and sensors that may be employed to support essential scientific missions, and provide an in-depth discussion and new insight into various inversion methods (or models) to improve the estimation accuracy. In this study, the spectrum of these remote sensing technologies and models is first divided into groups based on chronological order associated with different platforms and sensors, although some of them may be subject to mission-oriented arrangements. Case-based and location-based studies were cited, organized, and summarized to further elucidate tracks of application potential that support future, forward-looking, cost-effective, and risk-informed nutrient management plans. The comprehensive reviews presented here should echo real-world observational evidence by using integrated sensing, monitoring, and modeling techniques to improve environmental management, policy analysis, and decision making