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Remote sensing for resources development and environmental management
Damen, M. C. J.

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986
Multitemporal analysis of LANDSAT Multispectral Scanner (MSS)
and Thematic Mapper (TM) data to map crops in the Po valley
(Italy) and in Mendoza (Argentina)
M.Menenti & S.Azzali
Institute for Land and Water Management Research (ICW), Wageningen, Netherlands
D.A.Collado & S.Leguizamon
Instituto de Investigaciones Aplicadas en Ciencias Espaciales (HACE), Mendoza, Argentina
ABSTRACT: Practical applications of LAUDSAT Multispectral Scanner (MSS) and Thematic Mapper (TM) images in
digital format to crop monitoring are presented. Image availability and timeliness are dealt with in relation
with phenological variability and intercropping. Crop identification and mapping is done by establishing a
indices and overpass dates. A.n application of this method is presented. Out of the different vegetation in
dices, the transformed vegetation index (TVI) is chosen to assess the statistical significance of observed
differences. It is concluded that the accuracy of the TM sensor onboard LANDSAT 5 is sufficient to guarantee
pixels or more give statistically significant differences in TVI-values. Independent of the number of pixels,
relative differences of about 4% are not significant.
multitemporal discrimination scheme which makes use of crop labels defined in terms of different vegetation
the accuracy of observed and significant differences in vegetation index values. MSS or TM image samples of 5
Identification and mapping of agricultural crops with
LANDSAT data is a classic piece of remote sensing
research and application. In the first decade of
monitoring of earth resources by satellites the ap
pealing theoretical elegance of numerical classifica
tion methods stimulated much research into crop map
ping with single-date LANDSAT imagery.
In the last years a clear trend seems to emerge
(Crist 1984, Jackson et al. 1983, Miller et al. 1984,
Hinzman et al. 1984), which emphasizes multitemporal
analysis of satellite imagery to map crops. In our
opinion this is due to the recognition of the limits
of automatic classification methods and to the need
of reducing the amount of processing required for
each scene. The latter is a particularly important
issue when one tries to use operationally satellite
imagery in digital form. The potential of satellites
to provide frequent and regular information on agri
cultural crops within large areas can be spoiled by
excessive costs and the processing time required for
actually available images, i.e. those present in the
Earthnet archive, and of suitable images, i.e. those
available within the period most suited to crop
identification (Azzali 1986) are relatively low. In
1985, for example, only 17.5% of overpasses gave
suitable images for our purpose. It should also be
noted that 1985 was the best year in the time span
1980-1985 (Table 1). Table 1 shows that applications
requiring 3 suitable images per year were feasible
in each year except 1983. Anderson (1986) underscored
the commercial potential of crop monitoring by means
of LANDSAT applications requiring 4 and 5 suitable
MSS-images per year. Table 1 shows that such applica
tions would not be operationally reliable, since 5
MSS suitable images were available for only two
years out of six for both irrigation districts.
2.2 Phenological variability
The practical aspects of crop mapping by means of
satellites, therefore, are not only details to be
dealt with after having developed a technique, but
should be considered beforehand to establish which
methodology best suits the operational requirements.
In general terms one has to consider the practical
aspects of image availability and processing and of
agricultural reality, e.g. phenological variability
within each crop and intercropping.
The feasibility of crop mapping by means of multi
temporal LANDSAT imagery relies entirely on accurate
knowledge of crop phenology. It is especially impor
tant to estimate precisely the period of occurrence
of each phenological stage. Agricultural practices,
such as choice of variety, seeding date and applica
tion of fertilizers, increase the spread in the
period of occurrence of phenological stages in in
dividual fields where the same crop is being grown
(Crist 1984).
In this paper the approach and its application are
briefly presented. We will focus on the underlying
scientific issue of the statistical significance of
the observed differences. Out of the seven TM-bands
only two, i.e. TM 3 and TM 4, are applied because of
the comparison with MSS 7 and MSS 5 and of the need
to leave TM 5, TM 6 and TM 7 available for detection
of crop-specific effects, e.g. water stress.
Phenological observations in some 80 plots were
collected in the two Italian irrigation districts
during the growing season 1985. For each crop and
phenological stage, a graph has been constructed of
a function a (t) giving the area, on any given date,
where that particular stage occurs. Then the function:
2.1 Actually available and suitable LANDSAT images
We can, therefore, define a period of time
with t2 being the last date of observed occurrence
of each stage. The period [t^, 12] is, therefore,
directly obtained from the field observations. The
is calculated to obtain the total area where the par
ticular stage has occurred before day = t. The day =
t^ is the first date of occurrence according to the
phenological field observations.
is the first date of occurrence according to the
The application of LANDSAT data to crop monitoring
does in principle benefit from high temporal resolu
tion. As Table 1 shows, however, the percentages of