Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Part 1)

Gauhar Re bin an. Senior Engineer 
Abdul Fatah Shaikh. Senior Technician 
M. A. Sanjrani, Principal Scientific Officer 
Space & Upper Atmosphere Research Commission. Karachi, Pakistan 
UN/FAO irrigation suitability land classification provided the working model of base relationships in an 
irrigated area of Pakistan to predict the present potential of land use under intensive farming. The 
mostly demonstrative study, undertaken by the national space agency (SUPARCO). aimed at exploring the 
utility of SPOT XS & P coverage for aiding in the selection of test sites for field sutvey. The three- 
step approach, leading to preparation of maps delineating polygonal association foi irrigation suitability 
primarily consisted of a) selecting sample t.est sites through image enhancement. I>) preparation of a general 
landuse map through digital classification, and processing tire agronomic, management, environmental and 
socioeconomic details through a PC-based neural network for ultimate suitability selections. The results 
have been encouraging in terms of 'what if assessments for qualitative uses of land against prevailing 
cultural practices. Economic returns based on farm budgets for principal cash crops were evaluated using 
B/C ratios in terms of prevailing market considerations. 
Allahabad Pilot Project is une of a series of pub 
lic sector land reclamation programs initiated by 
the Federal Government under the name of salinity 
and reclamation programs (SCARPs) throughout irri 
gated landscape of the country. SCARP-VI in Rahim 
Yar Khan covers nearly 0.09 Mha and is buttressed 
between the Cholistan Desert to the east and river 
Indus on the west. There are two major inundation 
canal systems running across the length of the area 
after originating from the Punjnad Headworks on 
river Indus. The intensively farmed region produc 
es two major cash crops, i.e. cotton in the summer 
season of plentiful water supply, and wheat in the 
winter season. The well spread-out gravity distri 
bution network of water channels is plagued by 
seepage and percolation losses that in the recent 
past contributed to the rise of the groundwater 
level endangering the agroeconomy of the area. 
Although the public sector vertical drainage has 
succeeded in lowering the ' water table to safer 
levels, the pumpage from saline/alkaline pockets 
within the aquifer has contributed towards soil 
degradation. There is no predictable pattern to 
this land affliction, and within vast locales under 
considerable variant farming practices, it becomes 
a herculean task to keep track of unproductive 
land, let alone determine the stress on productive 
lands reverting to substance earnings. While .satel 
lite imagery had reasonably sufficed for quantita 
tive declarations on unproductive land, it failed 
to afford justifications ou underlying causes for 
the temporal offsets of surface behavior. However, 
its versatility lends itself to much more plausible 
reasoning if feature interpretability is sustained 
with detailed field surveys. A step furthe1 would 
be the estimation of the economic potential of the 
laud in terms of deliverables that directly address 
farm-level benefit-to-cost ratios. UN/FAO had 
modelled just, such a scheme in 1985. based un its 
"A Framework for Land Evaluation" presented in 
1976, to assess the suitability of land for it- 
rigated agriculture. The model matches the pre 
valent characteristics with the intended land use 
to arrive at suitability scales like SI, S3, N1, and 
N2 denoting decreasing suitability for the above in- 
tei actions. Prescribes to classification determin 
ing factors could include crop requirements, manage 
ment practices, land improvements, conservation 
activities, and of course socioeconomic trends. 
The national space agency of Pakistan, in extension 
of its stressed land monitoring engagements, at 
tempted a limited area sampling within the Allahabad 
Pilot Project (fig. 1) in conformance with the 
UN/FAO classification scheme for land suitability 
Inferencing for Land I'vaJ.uation 
Historically, the match-up of existing land cover 
types to selections prevailing on intended land use 
has been done at the human operator level, on a for 
mat. proposed within the UN/FAO publication No. 55. 
lire tabulal descriptions allow land characteristics 
to be weighed, though qualitatively, against options 
for irrigated land use. The recursive exercise, more 
benignly imagined as a matrixed correlation between 
the existing and the desired, relies on operator- 
level expertise in assigning the levels of signifi 
cance to each interaction. The procedure is inhe 
rently subjective because of factors 1 ike nonconfor 
mance in concluding evidence across a varying land 
scape, error containment at observation level, and 
inadvertent remissions in recording of data elements 
that tend to make the decisions bordering on the 
rul e-of-t hiimh knowledge. Arrival at this decision 
making can he automated towards offsetting these 
hindrances, however the unconventional approaches 
are less satisfactory and even impractical. Natural 
resource categorizations are not always given to 
discrete separations, and rather the result is » 
compromise of sorts a weighted approach along pre- 
establ i shed d iscr im i na t.ion . 
Rolf? of Neural Networks 
The growth of interest in neural networks during the 
1930s has been one of the fastest for any field- in

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