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2 CROP PRODUCTION FORECASTING
CROP PRODUCTION FORECASTING
Crop production forecast is an important parameter in the
food security programme of a developing country.
Therefore, in order to apply remote sensing effectively the
following preconditions should be met:
- The availability of the data during the actual growing
season must be guaranteed. The acquisition of the
relevant satellite remote sensing data for crop
forecasting purposes in the vegetational season is one
of the major constraints facing the users in many parts
of Africa. This is mainly due to the lack of ground
receiving stations that cover the region between the
Sahara and Southern Africa. Moreover, the period
between the order and the delivery of the image data
lies between 4-8 weeks. There are at present serious
proposals regarding the introduction of mobile
receiving stations which could be used to support the
development projects in many developing countries.
- The data should be interpreted as early as possible. In
order to be able to deliver information well in time, an
immediate processing and analysis of the remote
sensing data is necessary. This requirement would be
genuinely fulfilled only if enough well-trained and
motivated personnel is available.
- The interpretation methods should take the regional or
the local conditions into consideration. Owing to the
fact that the derivation of information from remote
sensing data can be conducted in various methods such
as the visual image interpretation, digital image class
ification, or a combination of both, the choice of the
method of interpretation should suit the available
resources.
- The allocation of enough funds for this purpose should
be ensured. In order to establish an efficiently functio
ning crop forecasting programme, financial support
should be ensured for the technical and administrative
aspects. The drought affected countries suffer from
inadequate financial resources and the lack of skilled
man-power aggravates the situation. These make a
technical assistance either international or bilateral
character indispensable. However, this technical assis
tance should not be unnecessarily prolonged as is with
many development projects.
The components of crop production forecasting are the
identification of crop type and the estimation of crop area,
monitoring of crop condition, and the estimation of crop
yield.
2.1 Estimation of crop area
In most of the drought affected countries in Africa, dry
farming or animal rearing is the main occupation of the
rural population. The agricultural area is therefore very
vast and mostly dispersed over several provinces. The
pattern of cultivation is diversified and the fields are
irregular. Though the number of newly registered farms
increases yearly, the land in the traditional hands is usually
not included in the official statistics. However, in order to
conduct a sound crop forecasting the estimation of the
area under crop is essential. Ground field survey would
take a long time and is costly. The conventional aerial
survey, though accurate is expensive. Therefore the best
method is the derivation of information from satellite
images, aerial photographs and a limited ground field
survey (fig.l), in combination with the available ancilliary
data on soil, topography, and location.
2.2 Monitoring of crop condition and growth
The rainfall fluctuations - timing, frequency, quantity and
intensity - is very great in most of the arid and semi-arid
countries of Africa. The monitoring of crop condition and
crop growth is therefore an essential part for the estimati-
Figure 1. A simplified diagramme showing the estimation
of crop production using remote sensing data.
on of the eventual area under adversely affected
conditions. Crop condition monitoring is mainly confined to
cash-crop plantations.
This zone is also a fertile breeding area for the desert
locust which is a great hazard to the crops in the region if
not carefully and continuously monitored. Several experim
ents have been made with satellite remote sensing data to
locate the valleys which may serve as the locations for the
hatching locust eggs (Hielkma 1980).
2.3 Estimation of the crop yield
Crop yield, is among others a function of weather, soil and
the vigor of the plants. A crop production forecast can be
conducted early enough before the harvest if the yield
prospects per hectare are known. There are of course
several methods of estimation, namely:
- The forecast of the yield based on characteristics of
plant or crop, and relation-ships based on weather
experiences in the former years. This method has been
intensively described in the agrometeorological liter
ature.
- Estimation of the yield through the spectral values of
the plant using a digital spectrometer or densitometer.
The spectral reflectances of such a vegetation, water
or sand have different characteristics as shown in (fig.
2). This method is based on the concepts of the high
correlation between the density of biomass and the
ratio of the sunlight reflectance of infra-red and red
bands.
The Kenya Rangeland Ecological Monitoring Unit made
experiments in estimating maize yield in 1984 using a
digital photometer. Their results according to
(Peden,Mwenda 1984) were comparable with those of the
Ministry of Agriculture and Livestock Development.
However, there are certain limitations for mixed crops
where the seperation of the responses could be difficult; or
where the maize plants grow sparsely, as in (fig. 3),
particularly by the rainfed agricultural areas, in which the
