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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
areas are characterized by less-demanding crops, such as jowar 
and pulses. Figure 5 depicts the correlations at a mandal level 
between CMI, CS and CON areas and irrigated areas and crops 
types. 
(b) Comparing the areas identified for CMI, CS and CON with 
terrain data 
Areas identified for CMI and CS occur significantly (52.4 and 
26.9%) in slope category 0-1%. This observation is in 
agreement with the idea that CMI- and CS-areas (basically 
identified for agriculture) should occur in flat land, while CON- 
Ag and CON-nonAg (identified for conservation) should occur 
in relatively more sloping land. A typical example of the latter 
is the Chapta series, showing visible signs of degradation, both 
on the remote sensing image and in our field investigations. 
(c) Comparison with soil properties 
Tables 3A,B,C show that within the areas identified for CON- 
Ag and CON-non Ag the vast majority is characterized by very 
sandy soils (sand 80-8894), whereas areas identified for CMI 
and CS have lower sand contents and relatively deeper topsoils. 
Areas identified for CS are positively correlated with clay 
content. An example is Madnur mandal where 48% of the 
agricultural area is identified for CS, and 76% of the area has 
clay contents of 38-49.6%. These are basically areas of black 
cotton soils, exhibiting workability problems during the Kharif 
season. The farmers use these soils for agriculture during the 
post-monsoon period on residual soil moisture, with limited 
supplementary irrigation. A variety of crops are grown, viz., 
rice (7.5%), jowar (22.4%), pulses (20.5%), sugarcane (0.1%), 
groundnut (1.0), cotton (26.4%) and other crops (22%). These 
characteristics support the conclusion that farmers in such areas 
(identified as CS) could benefit from advice on suitable crop 
selection. 
Tables 3A, B and C: Soil texture and depth of soil series in 
relation to the LUA Objectives 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
4A: CMI 
Sand Clay Silt Depth 
Soil Series (%) (%) (%) (cm) 
Bodhan 42 42 16 30 
Anksapuram 50 35 15 14 
Fateullapur 54 20 16 70 
Birkur 45 35 20 15 
Uppalvai 60 25 15 14 
4B: CS 
Sand Clay Silt Depth 
Soil Series (%) (%) (%) (cm) 
Mardi 49 42 9 18 
Maddalacheru 41 44 15 15 
Waddarpalli 54 29 17 16 
Chinnakodapgal 58 3l 11 14 
Masampalli 56 18 26 15 
Peddakodapgal 33 50 17 15 
4C: CON 
Sand Clay Silt Depth 
Soil Series (79) (%) (%) (cm) 
Bandapalli 80 11 9 15 
Chapta 88 8 4 10 
Pulkal-Il 77 13 10 12 
Sultanpet 86 7 7 14 
Kottur 86 10 4 10 
Bichkunda 82 12 6 15 
Kaulas 87 12 5 16 
  
  
  
  
  
  
  
Kallair | 81 | 12 L 7 | 10 
Yanglur | 78 | 13 | 9 | 18 
  
  
(d) Field visits and overview of farmers’ responses 
The field visits and interviews with farmers were conducted in 
eighteen villages across the six mandals of the study area (Figure 6). 
The procedure consisted of (i) identifying the CMI, CS and CON 
areas with the aid of a mobile GIS/GPS system and intervening 
farmers in the field. The questions related to farmers views on their 
soils, problems - as 
they perceived, 
suitability of their soils 
for crops, access to 
extension service, 
water availability. 
Based on our 
interviews with 
farmers, the purpose of 
which was to identify 
driving forces behind 
farmers’ decisions on 
land use, and own field 
observations, we can 
conclude that some of 
the reasons for either 
  
degradation or  sub- Figure 6: Field visit and interview 
optimal use of land are: . locations with farmers 
(1) presence of 
smallholder/subsistence farmers, (ii) insufficient water for irrigation, 
(iii) lack of or inadequate extension support, (iv) lack of funds to 
implement suggestions from the extension service and (v) specific 
dietary preferences for rice. 
S. CONCLUSIONS 
The results of this study show that different land use analysis 
objectives exist for different areas in the study area. The relationship 
between land (soil as an important land parameter) and land use can 
be used to differentiate such areas. These areas can be spatially 
depicted through application of GIS techniques. The results can be 
used to focus the efforts (when existing planning procedures are 
operational in an area) of planning and extension services in the area 
as follows: (a) Crop Management Improvement (CMI) areas are 
those that could benefit from improved management practices for 
higher yields. A detailed study of the management practices of 
farmers in the study area can help in identifying inadequacies in 
their current management and suggesting appropriate improvements. 
Methods, such as the Comparative Performance Analysis could be 
applied to identify yield gaps, in the present study this refers to rice 
cultivation. (b) Crop Selection (CS) areas are those that require 
advising farmers on suitable crop selection based on the constraints 
they face. Methods such as multiple goal optimisation techniques 
could be applied to generate cropping options, considering factors 
such as socio-economic conditions of the farmers, market 
opportunities and policy instruments and (c) Conservation areas 
present the most critical challenge to the resource managers. 
Questions as to why marginal lands are cultivated and why in some 
cases sub-optimal land use occurs have to be answered. The areas 
need specific alternatives in terms of a balance between land 
degradation and livelihoods of subsistence farmers. The resource 
managers need to identify alternatives to intense farming to prevent 
further degradation, while providing adequate livelihoods to local