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See detailEstimating crop-specific evapotranspiration using remote-sensing imagery at various spatial resolutions for improving crop growth modelling
Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio et al

in International Journal of Remote Sensing (2013)

By governing water transfer between vegetation and atmosphere, evapotranspiration (ET) can have a strong influence on crop yields. An estimation of ET from remote sensing is proposed by the EUMETSAT ... [more ▼]

By governing water transfer between vegetation and atmosphere, evapotranspiration (ET) can have a strong influence on crop yields. An estimation of ET from remote sensing is proposed by the EUMETSAT ‘Satellite Application Facility’ (SAF) on Land Surface Analysis (LSA). This ET product is obtained operationally every 30 min using a simplified SVAT scheme that uses, as input, a combination of remotely sensed data and atmospheric model outputs. The standard operational mode uses other LSA-SAF products coming from SEVIRI imagery (the albedo, the downwelling surface shortwave flux, and the downwelling surface longwave flux), meteorological data, and the ECOCLIMAP database to identify and characterize the land cover. With the overall objective of adapting this ET product to crop growth monitoring necessities, this study focused first on improving the ET product by integrating crop-specific information from high and medium spatial resolution remote-sensing data. A Landsat (30 m)-based crop type classification is used to identify areas where the target crop, winter wheat, is located and where crop-specific Moderate Resolution Imaging Spectroradiometer (MODIS) (250 m) time series of green area index (GAI) can be extracted. The SVAT model was run for 1 year (2007) over a study area covering Belgium and part of France using this supplementary information. Results were compared to those obtained using the standard operational mode. ET results were also compared with ground truth data measured in an eddy covariance station. Furthermore, transpiration and potential transpiration maps were retrieved and compared with those produced using the Crop Growth Monitoring System (CGMS), which is run operationally by the European Commission’s Joint Research Centre to produce in-season forecast of major European crops. The potential of using ET obtained from remote sensing to improve crop growth modelling in such a framework is studied and discussed. Finally, the use of the ET product is also explored by integrating it in a simpler modelling approach based on light-use efficiency. The Carnegie–Ames–Stanford Approach (CASA) agroecosystem model was therefore applied to obtain net primary production, dry matter productivity, and crop yield using only LSA-SAF products. The values of yield were compared with those obtained using CGMS, and the dry matter productivity values with those produced at the Flemish Institute for Technological Research (VITO). Results showed the potential of using this simplified remote-sensing method for crop monitoring. [less ▲]

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See detailCombining remote sensing imagery of both fine and coarse spatial resolution to estimate crop evapotranspiration and quantifying its influence on crop growth monitoring
Sepulcre-Canto, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio et al

in Geophysical Research Abstracts (2010)

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the ... [more ▼]

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. This paper concerns the use of MSG geostationnary satellite data for the calculation of Actual Evapotranspiration and its integration into a crop growth model. [less ▲]

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See detailManaging climatic risks for enhanced food security : key information capabilities
Balaghi, Riad; Badjeck, M.-C.; Djaby, Bakary ULg et al

in Procedia Environmental Sciences (2010), 1

Food security is expected to face increasing challenges from climatic risks that are more and more exacerbated by climate change, especially in the developing world. This document lists some of the main ... [more ▼]

Food security is expected to face increasing challenges from climatic risks that are more and more exacerbated by climate change, especially in the developing world. This document lists some of the main capabilities that have been recently developed, especially in the area of operational agroclimatology, for an efficient use of natural resources and a better management of climatic risks. Many countries, including the developing world, now benefit from well-trained staff in the use of climate data, physical and biological information and knowledge to reduce negative climate impacts. A significant volume of data and knowledge about climate–agriculture relationships is now available and used by students, scientists, technicians, agronomists, decision-makers and farmers alike, particularly in the areas of climate characterization, land suitability and agroecological zoning, seasonal climate forecasts, drought early warning systems and operational crop forecasting systems. Climate variability has been extensively modelled, capturing important features of the climate through applied statistical procedures, agroclimatic indices derived from raw climatic data and from remote sensing. Predictions of climate at seasonal to interannual timescales are helping decision-makers in the agricultural sector to deal more effectively with the effects of climate variability. Land suitability and agroclimatic zoning have been used in many countries for agricultural planning, thanks to the availability of new and comprehensive methodologies; developments in climate, soil and remote sensing data collection and analysis; and improved applications in geographic information systems (GIS). Drought early warning systems are available worldwide at both national and international levels. These systems are helping decisionmakers and farmers to take appropriate decisions to adapt to short-term climatic risks. Also, operational crop forecasting systems are now becoming available at the regional and national levels. In some developed countries, several efficient and well tested tools are now available for optimizing on-farm decisions based on the combination of crop simulation models and seasonal forecasts. However, in developing countries few tools have been developed to efficiently manage crops at the farm level to cope with climate variability and climate risks. Climate change impacts on agriculture and food security have been assessed in international studies using specific and efficient methodologies and tools. Adaptation to climate change and variability can also be facilitated through effective planning and implementation of strategies at the political level. The role of technological progress, risk transfer mechanisms and financial instruments and their easy accessibility to rural people are critical elements of climate risk management. [less ▲]

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See detailExploring the potential of crop specific green area index time series to improve yield estimation at regional scale
Duveiller, Gregory; de Wit, Allard; Kouadio, Amani Louis ULg et al

in Sobrino, J. A. (Ed.) Proceedings of the 3rd International Symposium on Recent Advances in Quantitative Remote Sensing (RAQRS'III) (2010)

Crop status, such as the Green Area Index (GAI), can be retrieved from satellite observations by modelling and inverting the radiative transfer within the canopy. Providing such information along the ... [more ▼]

Crop status, such as the Green Area Index (GAI), can be retrieved from satellite observations by modelling and inverting the radiative transfer within the canopy. Providing such information along the growing season can potentially improve crop growth modelling and yield estimation. However, such approaches have proven difficult to apply on coarse resolution satellite data due to the fragmented land cover in many parts of the World. Advances in operational crop mapping will sooner or later allow the production of crop maps relatively early in the crop growth season, thereby providing an opportunity to sample pixels from medium/coarse spatial resolution data with relatively high cover fraction of a particular crop type to derive crop specific GAI time series. This research explores how to use such time series derived from MODIS to produce indicators of crop yield using two approaches over part of Belgium. The first method consists in looking at metrics of the decreasing part of the GAI curves when senescence occurs. Such metrics, like the position of the inflexion point, have been shown to be significantly correlated to yield. The second approach is to optimize the WOFOST model used in the European Crop Growth Monitoring System (CGMS) based on the GAI time series. Results show that, although the optimized model shows considerably better performance than the model running on the default parameter, the model is sometimes outperformed by the simpler metric approach. In all cases, indicators including remote sensing information provide better estimates that the average yield of previous years. [less ▲]

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