Tag Archives: Remote sensing

xxx K. Křížová and J. Kumhálová
Comparison of selected remote sensing sensors for crop yield variability estimation
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Comparison of selected remote sensing sensors for crop yield variability estimation

K. Křížová¹* and J. Kumhálová²

¹Czech University of Life Sciences in Prague, Faculty of Engineering, Department of Agricultural Machines, Kamýcká 129, CZ165 21 Prague, Czech Republic
²Czech University of Life Sciences in Prague, Faculty of Engineering, Department of Machinery Utilization, Kamýcká 129, CZ165 21 Prague, Czech Republic
*Correspondence: krizovak@tf.czu.cz

Abstract:

Currently, spectral indices are very common tool how to describe various characteristics of vegetation. In fact, these are mathematical operations which are calculated using specific bands of electromagnetic spectrum. Nevertheless, remote sensing sensors can differ due to the variations in bandwidth of the particular spectral channels. Therefore, the main aim of this study is to compare selected sensors in terms of their capability to predict crop yield by NDVI utilization. The experiment was performed at two locations (Prague-Ruzyně and Vendolí) in the year 2015 for both locations and in 2007 for Prague-Ruzyně only, when winter barley or spring barley grew on the plots. The cloud-free satellite images were chosen and normalised difference vegetation indices (NDVI) were calculated for each image. Landsat satellite images with moderate spatial resolution (30 m per pixel) were chosen during the crop growth for selected years. The other data sources were commercial satellite images with very high spatial resolution – QuickBird (QB) (0.6 m per pixel) in 2007 and WorldView-2 (WV-2) (2 m per pixel) in 2015 for Prague-Ruzyně location; and SPOT-7 (6 m per pixel) satellite image in 2015 for Vendolí location. GreenSeeker handheld crop sensor (GS) was used for collecting NDVI data for both locations in 2015 only. NDVI calculated at each of images was compared with the yield data. The data sources were compared with each other at the same term of crop growth stage. The results showed that correlation between GS and yield was relatively weak at Ruzyně. Conversely, significant relation was found at Vendolí location. The satellite images showed stronger relation with yield than GS. Landsat satellite images had higher values of correlation coefficient (in 30 m spatial resolution) at Ruzyně in both selected years. However, at Vendolí location, SPOT-7 satellite image has significantly better results compared to Landsat image. It is necessary to do more research to define which sensor measurements are most useful for selected applications in agriculture management.

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055–068 J.A. Domínguez, J. Kumhálová and P. Novák
Assessment of the relationship between spectral indices from satellite remote sensing and winter oilseed rape yield
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Assessment of the relationship between spectral indices from satellite remote sensing and winter oilseed rape yield

J.A. Domínguez¹, J. Kumhálová²* and P. Novák³

¹UNED Department of Mathematical and Fluid Physics, Science Faculty,
C/Senda del Rey, nº9, ES280 40 Madrid, Spain
²Czech University of Life Sciences Prague, Faculty of Engineering, Department of
Machinery Utilization, Kamýcká 129, CZ165 21 Prague, Czech Republic
³Czech University of Life Sciences in Prague, Faculty of Engineering, Department of
Agricultural Machines, Kamýcká 129, CZ165 21 Prague, Czech Republic
*Correspondence: kumhalova@seznam.cz

Abstract:

Winter oilseed rape (Brassica napus L.) belongs among the most common and strategic
crops in the Czech Republic. Growth and vitality status, yield potential and yield prediction of
oilseed rape on plots of different sizes can be effectively examined using remote sensing. That is
why the main aim of this study was to discuss a possibility of deriving spectral indices for an
assessment which spectral index is more adequate to forecast oilseed winter rape development
and consequent yield in the Czech Republic. Information about the winter oilseed rape growth
and yield was collected in three years – 2004, 2008, 2012. A relationship between grown crops
and selected vegetation indices was evaluated. The Landsat 7 satellite images were selected as a
source for deriving spectral indices. The relationship between each spectral index and yield was
analysed in 2012 only. Five images on different dates during the whole life of winter oilseed rape
were found during this year. The images from the years 2004 and 2008 were cloudier. The spectral
indices showing the best relationship with yield from 2012 were then analysed in the images from
2004 and 2008. The results showed that Enhanced Moisture Stress Index is the most acceptable
index from the selected indices used in this study. From an agronomical point of view no available
index was found to be suitable for the winter rape growth evaluation due to dependence on
precipitation conditions. For monitoring of the yield components in winter oilseed rape in
conditions of the Czech Republic, it seems necessary to develop a new vegetation index which
will reliably describe the winter oilseed rape growth stages during the whole vegetation season.

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