Comparison of selected remote sensing sensors for crop yield variability estimation
Laen...
Kuupäev
2017
Kättesaadav alates
Autorid
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Abstrakt
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.
Kirjeldus
Article
Märksõnad
remote sensing, crop yield, satellite images, Greenseeker, NDVI, articles