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Detection of drought events using combination of satellite data and soil moisture modelling
Semerádová, Daniela ; Trnka, Miroslav ; Hlavinka, Petr ; Balek, Jan ; Bohovič, Roman ; Tadesse, T. ; Hayes, M. ; Wardlow, B. ; Žalud, Zdeněk
The use of satellite data offers a potentially well usable tool to accurate drought monitoring. The study examines the space-time possibility of agricultural drought detection using freely available data from the MODIS instrument onboard Terra and Aqua satellites that reflects vegetation condition. Vegetation greenness metrics used in this study are based on the spectral reflectance curves in the visible red and near-infrared part of the spectrum and are expressed in relation to the average for the period of 2000-2014. The results are presented in weekly time step for the whole area of the Czech Republic, and are compared to the drought monitor system, based on the SoilClim dynamic model for soil water content estimates. These data, as well as other parameters, such as soil properties and land use, are integrated at 500 meters spatial resolution.
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Remote sensing as support tool for agricultural drought assessment
Hlavinka, Petr ; Semerádová, Daniela ; Balek, Jan ; Žalud, Z. ; Tadesse, T. ; Hayes, M. ; Wardlow, B. ; Trnka, Miroslav
Very important information about vegetation condition within wide areas (through continents and states) or for local areas in resolution from hundreds to tens of meters could be obtained from satellites within remote sensing. The temporal and spatial continuity is big advantage of this method. Namely so-called vegetation indices are often used for vegetation cover condition assessment. The aim of submitted study is to present possibility of using EVI2 (Enhanced Vegetation Index) for assessment of drought impact within vegetation. The results for selected years of the period 2000-2015 achieved using MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite are included. The data in weekly time step and for the whole Czech Republic are presented.
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LINCOLN – an algorithm for filtering daily NDVI MODIS data and deriving the start of the season
Bohovič, R. ; Hlavinka, Petr ; Semerádová, Daniela ; Bálek, L. ; Tadesse, T. ; Hayes, M. ; Wardlow, B. ; Trnka, Miroslav
Monitoring drought has become an important tool for farmers and agriculture decision makers. This has increased efforts to create a monitoring system using satellite data that could provide an independent and current source of real information on vegetation condition. The aim of this study was to develop an algorithm for processing Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer. A software utility called LINCOLN was developed for this purpose. Its filtering output was further processed to yield a start of the season (SOS) metric. Different settings of the utility were tested and correlated to such phenological ground observations as the emergence of spring barley and the beginning of leaf sheath elongation in winter wheat. There was higher correlation observed in the case of winter wheat, probably due to its weaker dependence on crop sowing date. The matrix of coefficients of determination was applied to determine the optimal settings for the LINCOLN filter. The optimal absolute threshold NDVI value for SOS was set to 4,500.
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