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Prediction of crop yields using satellite remote sensing
Lukas, V. ; Trnka, Miroslav ; Semerádová, Daniela ; Rajdl, Kamil ; Balek, Jan ; Štěpánek, Petr ; Zahradníček, Pavel ; Hlavinka, Petr ; Žalud, Zdeněk
Knowledge of the crop yield with sufficient lead time prior to harvest is crucial for both the farm management and the agro-food sector policy. The aim of this study was to test feasibility of developing crop yield forecasting model in Czech Republic for winter wheat, spring barley and oilseed rape based on 2000-2014 database of vegetation indices Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI2) from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite in form of 16-days composites. An average yield data were collected for 14 selected districts in the Czech Republic that represent the regions with more intensive agricultural production among varying climate and topographic conditions. The viability of the concept was proven in years with significant yield decline i.e. 2000, 2003, 2006 and 2012, when yields of cereals were significantly affected by occurred drought periods. More stable regression results were achieved in the most productive areas such as Olomouc and Prerov, whilst models in highland regions were influenced by lower acreage of three modelled crops and higher prevalence of fodder crops. In most cases, EVI2 showed higher correlations to the crop yield together with using an average value of all composites during vegetation period.
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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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The agricultural drought monitoring and its users and correspondents
Bartošová, Lenka ; Trnka, Miroslav ; Semerádová, Daniela ; Hlavinka, Petr ; Štěpánek, Petr ; Zahradníček, Pavel ; Žalud, Z.
Drought monitoring in the Czech Republic is a key element in climate monitoring. The aim of this article is to describe the possible participation of agronomists, foresters and fruiterers in drought monitoring within the Integrated Drought Monitoring System. This system monitor drought occurence weekly on the base of various information (data from model SoiClim or outputs from satellite Aqua and Terra). One of the main pillar of the monitor is also information about drought impact on yields in the cooperation with especially farmers. Their expert assessment brings insight into actual situation in agricultural landscape in weekly time step. All results are free to download in www.intersucho.cz.
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Drivers of soil moisture trends in the Czech Republic between 1961 and 2012
Trnka, Miroslav ; Brázdil, Rudolf ; Balek, J. ; Semerádová, Daniela ; Hlavinka, Petr ; Možný, M. ; Štěpánek, Petr ; Dobrovolný, Petr ; Zahradníček, Pavel ; Dubrovský, Martin ; Eitzinger, Josef ; Fuchs, B. ; Svoboda, M. ; Hayes, M. ; Žalud, Zdeněk
Soil moisture dynamics and their temporal trends in the Czech Republic are forced by various drivers. Our analysis of temporal trends indicates that shifts in drought severity between 1961 and 2012 and especially in the April, May, and June period, which displayed such results as a 50% increase in drought probability during 1961–1980 in comparison to 2001–2012. We found that increased global radiation and air temperature together with decreased relative humidity (all statistically significant at p < 0.05) led to increases in the reference evapotranspiration in all months of the growing season; this trend was particularly evident in April, May, and August, when more than 80% of the territory displayed an increased demand for soil water. These changes, in combination with the earlier end of snow cover and the earlier start of the growing season (up to 20 days in some regions), led to increased actual evapotranspiration at the start of the growing season that tended to deplete the soil moisture earlier, leaving the soil more exposed to the impacts of rainfall variability. These results support concerns related to the potentially increased severity of drought events in Central Europe. The reported trend patterns are of particular importance with respect to expected climate change, given the robustness and consistency of the trends shown and the fact that they can be aligned with the existing climate model projections. Introduction
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Reliability of regional crop yield predictions in the Czech Republic based on remotely sensed data
Hlavinka, Petr ; Semerádová, Daniela ; Balek, Jan ; Bohovič, Roman ; Žalud, Zdeněk ; Trnka, Miroslav
Vegetation indices sensed by satellite optical sensors are valuable tools for assessing vegetation conditions including field crops. The aim of this study was to assess the reliability of regional yield predictions based on the use of the Normalized Difference Vegetation Index and the Enhanced Vegetation Index derived from the Moderate Resolution Imaging Spectroradiometer aboard the Terra satellite. Data available from the year 2000 were analysed and tested for seasonal yield predictions within selected districts of the Czech Republic. In particular, yields of spring barley, winter wheat, and oilseed winter rape during 2000–2014 were assessed. Observed yields from 14 districts were collected and thus 210 examples (15 years within 14 districts) were included. Selected districts differ considerably in soil fertility and terrain configuration and represent a transect across various agroclimatic conditions (from warm/dry to relatively cool/wet regions). Two approaches were tested: 1) using 16-day temporal composites of remotely sensed data provided by the United States Geological Survey, and 2) using daily remotely sensed data in combination with an originally developed smoothing method. Yields were predicted based on established regression models using remotely sensed data as an independent parameter. In addition to other findings, the impact of severe drought episodes within vegetation was identified and yield reductions at a district level were predicted. As a result, those periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above-normal yields of the tested field crops were predicted using the proposed method within the study region up to 30 days prior to harvest.
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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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Remotely sensed NDVI as a support tool for agricultural drouhgt assessment
Hlavinka, Petr ; Semerádová, Daniela ; Trnka, Miroslav ; Lukas, V. ; Bohovic, R. ; Balek, J. ; Wardlow, B. ; Hayes, M. ; Tseagaye, T. ; Žalud, Zdeněk
Th e main aim of the submitted study was to introduce how the remotely sensed NDVI (Normalized Diff erence Vegetation Index) could be used for agricultural drought assessment within the Czech Republic. Th e relationship between NDVI values and observed yields of spring barley and winter wheat was analyzed for selected districts. Moreover the ability of NDVI (at district level in the form of seasonal greenness – SG) to explain the water balance or drought occurrence and severity was tested. For this purpose a data mining technique was used. A relative form of the Palmer Drought Severity Index (rPDSI) was used as a dependent variable to indicate drought occurrence. A Standardized Precipitation Index (SPI), percentage of average SG (PASG), Start of Season Anomaly (SOSA) and district identifi cation were used as independent variables. MODIS (Moderate Resolution Imaging Spectroradiometer) observations from the Terra satellite were used as a source of NDVI. Th e situation within 6 selected districts (Olomouc, Přerov, Znojmo, Břeclav, Žďár nad Sázavou and Havlíčkův Brod) during the period from 2000 to 2012 was analyzed. Promising results were achieved, so practical use of this approach (e.g. for spatial and temporal assessment of drought stress within the vegetation) could be expected.
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Using remotely sensed NDVI for drought impact assessment within selected crops
Hlavinka, Petr ; Trnka, Miroslav ; Semerádová, Daniela ; Dobrovolný, P. ; Balek, J. ; Možný, M. ; Štěpánek, P. ; Hayes, M. ; Svoboda, M. ; Wardlow, B. ; Žalud, Zdeněk
The relationship between Normalized Difference Vegetation Index (NDVI) and selected agrometeorological parameters (yields of selected crops, water balance) was investigated. The source for NDVI was Spectroradiometer MODIS within satellite Terra and it was available for grids in resolution 500 x 500 m from 2000 to 2010. The analysis was conducted within 12 grids spread through Southern and Central Moravian region. The information about cultivated crops (including spring barley, winter wheat, maize for grains, sugar beet and winter rape) were collected from the farmers and water balance simulated using SoilClim model.
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