International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
If in a soil series the land use classes Kharif, Rabi and Kharif + 
Rabi occupy seventy five percent or more of the area, the 
inference is that the local farmers consider the land as ‘suitable’ 
for agriculture. If a soil-series/sub-group is distributed evenly 
TTT TEI = 
  
  
  
  
  
  
  
Figure 4B: Conservation 
Figure 4A : Crop Management Improvement 
among agricultural and non-agricultural land use classes, that 
could be interpreted as either an indication of pressure on land 
(land less suitable for agriculture being used fer agriculture) or 
of a limitation by (an)other constraint(s) (land suitable for 
agriculture, but not used). This interpretation forms the basis 
for identification of broad land use analysis objectives: Crop 
Management Improvement, Conservation, and Crop Selection. 
  
Based on the above PR 
discussion, selection of the Nu. S 
land use analysis objectives is 
formulated as (Table 
3:A,B,C; Figure 4:A,B,C)): 
If soil series S, is overlain by 
> 15% "er TI^ and 
predominantly a single crop, 
then the priority LUA 
objective is "Crop 
Management | Improvement 
(CMI)". If soil series S, is 
overlain by > 75% of LU. in 
the area and multiple crops of 
cultivated, then the priority 
LUA objective is “Crop Selection (CS)". If the soil series S; 
and LU,, relationship is, 2596 « soil series S, « 75%, then the 
priority LUA objective is “Conservation (CON)”, especially 
when the land has a poor cover (no scrubs). When Soil series S, 
overlain by < 25% LU. then no priority is set with respect to 
LUA objectives. 
  
  
Figure 4C: Crop-Selection 
4.2 Validation of results 
The results from the foregoing analysis have been validated 
with reference to the following independent sources: (a) 
statistical data obtained from the District Planning Office, (b) 
Physical and chemical properties of the soils, (c) Terrain data in 
the form of a slope map, (d) Field visits and interviews with 
farmers. 
a) Statistical data 
Two sets of data available with the District Planning Office on 
extent of the irrigated area and areal extent of crops, aggregated 
  
  
to mandal level, have been used. Therefore, the areas covered by the 
three land use analysis objectives have been calculated at mandal 
level for comparison. The comparisons (Table 1) focus on the 
percent area covered by each of the land use analysis objectives in a 
mandal with (a) percent area under irrigation in the mandal and (b) 
percent area of a particular crop in the mandal. Percent areas have 
been used for ease of comparison. It can be seen from the Table 1, 
that Kotgir and Birkur mandals (where the Bodhan, Anksapuram, 
Birkur and Uppalvai series occur) have significant areas covered by 
CMI (85 and 87% of the mandal agricultural area, respectively). 
Table 1: Extent of LUA Objectives (percent of total area) versus 
area (ha) devoted to major crops (percent area) in the study area 
    
    
   
     
     
      
       
  
rrig 
Cotton 
12.30 
Birkur 12.50 
Bichkunda | 33. 16.40 
Madnur 22.00 
       
    
     
Jukal 21 0 19.30 
   
        
    
7.4 6.50 
  
Pitlam 4.40 49. 
The irrigated area in these mandals is 42.8% and 57%, respectively. 
Rice cultivation in these mandals covers respectively 42.35 and 70% 
of the agricultural area. Sugarcane is the next dominant crop with 16 
and 7.2%. These data support the analysis that in areas characterized 
by a single dominant crop the main objective is improved crop 
management for higher yields. Alternatively, in Jukal mandal a 
  
1.5 
CMI 
cs 
L1 CON-Ag 
  
  
  
  
Figure 5: Correlations at mandal level between CMI, CS and CON 
areas and irrigated areas and crop types 
higher percentage of the area is diagnosed for CS. Tt has a very small 
area under irrigation (2.5% of the agricultural area) and there is no 
dominant crop. Similar situations are found in other mandals, like 
Pitlam characterized by a significant area identified for CS. Here, in 
contrast to the areas identified for Crop Management Improvement 
(with predominantly rice cultivation), farmers grow a wide variety 
of crops. This is supported by data in Table |, where crops such as 
jowar, pulses, sugarcane, groundnuts, cotton and others cover an 
average 78% of the agricultural area. These statistical data support 
the identification as CS areas, characterized by multiple cropping 
systems with restricted irrigation facilities. Farmers here could 
benefit from advice from the extension service on suitable crop 
selection. Note further that mandals with higher percentages of CMI 
areas are characterized by highly demanding crops, such as rice and 
sugarcane, while mandals with higher percentages of CS and CON 
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