Usability of remote sensing methods for the assessment of development of spring barley
Janusz Igras, Rafał Pudełko, Krzysztof Kubsik
Institute of Soil Science and Plant Cultivation – State Research Institute, Puławy, Poland
Introduction
Remote sensing (teledection) methods make it possible to continuously analyze the spatial
variability of the processes taking place on the area being photographed. Contrary to traditional
methods based mainly on soil and plant sampling, these are non-invasive, quick and cheap methods.
By analyzing multispectral photographs it is likely to mark vegetation indexes that are associated with
plant development stages. The indexes are calculated by performing algebraic operations at different
light wavelengths. The paper deals with the assessment of spring barley development based on the
interpretation of teledetection data. Aerial photographs of the field were processed to the image of
vegetation index and then into unsupervised classification by the ISODATA method.
The aim of the paper was to estimate development stages of spring barley using aerial
photographs and compare vegetation indexes with soil variability in the field.
Material and methods
The studies were carried out on the experimental spring barley field located at the IUNG-PIB
Experimental Station (Wielkopolska – central part of Poland, 52,585oN 16,640oE). Distinctive features
of the region are high variability of soil conditions and the lowest precipitation in Poland (approx. 550
mm / year) – (Górski et al., 1999). High soil variability was also typical for spring barley field of 16 ha
– there are middle, light and very light soils, mainly loamy sands and light loams.
Aerial photographs of the stand were taken at the flag leaf stage of barley (37 according to
Zadoks) using non-metric digital camera at the flying height of 1000 m. Using the ERDAS Imagine
software the photographs were prepared as a map of standardized index of development. The index is
based on spectral differences in reflection in green and red bands, which are characteristic for plants
(Granzdorffer, 2003). Then the map was corrected by giving each pixel the most characteristic value
within an area with a radius of 10 m. To generalize the map there was its unsupervised classification
with the ISODATA method, obtaining the map of four classes of development index.
The assessment of field soil variability was performed using the map of granulometric
composition, in the scale of 1: 1000, based on the sampling in the grid resolution of 24 m.
Results
The analysis of aerial photographs made it possible to interpret the differentiation of spring
barley development within the experimental field. The field with its monotonous relief has height
differences not exceeding 2 m and height variability without any local discontinuities. As tillage
methods applied were not differentiated it is likely to conclude that the revealed variability of barley
development may be caused only by soil properties and especially by its granulometric composition.
As comparing soil map and development map it was proved that development stage within the field
was stronger differentiated than it should be expected when analyzing the variability of granulometric
composition of the soil based on soil map (Fig. 1). Table 1 shows that the following soil types
prevailed in particular classes of development index: first class - light loam and light loamy sand,
second class - light loamy sand and classes 3 and 4 proved to be similar with the light loamy sand
predominating. Percentages of the areas within particular classes show just general trends that do not
justify spatial and local differences in the development. The differences are most clear on the field
map where light loamy sands (pgl) occur. Class 1 and 2 prevail in the NW part of the field (left side of
the Fig. 1), whereas class 3 and 4 of development index are dominant in the middle and SE parts
(middle and right side of the Fig. 1).
Fig. 1. Comparison of the maps presenting crop development indexes and soil granulometric
composition; gl – light loam; pgl – light loamy sand, pgm – loamy sand; ps – slightly loamy sand
Tab. 1. Percentage of soil types distinguished in the classes of development index
Development index class
Soil type
1
2
3
4
gl
34
18
2
1
pgl
49
62
86
94
pgm
17
12
1
1
ps
0
8
11
4
Discussion and conclusions
The maps of crop development indexes indicate the high albedo variability in the cereal stand,
remarkably reflecting the state of plant development. Such a variability for the most part is caused by
soil conditions (Jadczyszyn, 2001). However, the analyses reveal that a real differentiation of soil
conditions is higher than it is showed on a mulitscale soil map based on analyzing granulometric soil
composition.
The studies justify the necessity to recognize a real variation of production fields with using
the remote sensing methods (for example teledetection methods), which are of higher accuracy than
point observations. This is particularly important on the areas with a high soil mosaic, including
Wielkopolska region.
Recognition of a real spatial variation of the field might be a direction to better adjust
agricultural measures to the present plant nutrition requirements (Granzdorffer, 2003). Use of the
cheap remote techniques is likely to improve traditional advisory systems as regards application of the
second nitrogen rate, what at the scale of big production fields might be of a significant economic
benefit.
The maps of development indexes can be also used to prepare irrigation strategies.
 Application of remote measurements methods indicated that there is a higher differentiation of
variability of crop development indexes than the variability assessed by a soil agricultural
map.
 Remote sensing measurement methods made it possible to determine a real field variation,
what may be used to adjust agricultural measures to the present crop development conditions.
References
Granzdorffer, G.J. 2003. Investigations on the use of airborne remote sensing for variable rate
treatments of fungicides, growth regulations and N-fertilisation. Precision Agriculture, Edited by
Stafford J., Werner A., Wageningen Academic Publishers: 241-247.
Górski, T., Krasowicz, St., Kuś, J. 1999. Soil and climatic potential of Poland in cereal grain
production, Pam. Puł. 114, 127 – 138.
Jadczyszyn T. 2001. Zmienność gleb, plonów i potrzeb nawozowych roślin w granicach pola
produkcyjnego. XI Międzynarodowa Konferencja Naukowa ”Problemy Inżynierii Rolniczej na progu
III Tysiąclecia: Technika-Środowisko-Człowiek”, 30.05-1.06.2001 Międzyzdroje: 163-167.
The studies have been supported by the Ministry of Science and Information Technology within the
research project LOTON P06R 041 27.