e parameters
ability class.
reclassifying
'om A, B, C,
n capability
oil loss map
|, E2, E3 &
integrating
ich contains
re land use
nd possible
determining
prepared by
' to obtain
needs soil
vhere soil
ich can be
suggested
ed above.
8 % have
1Servation
blic land)
itably for
ed within
isures for
lave been
hange of
Table-2).
IAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002
3. O+ Seriously over used. 126.13 0.42
4. O Over Used. 437.29 1.86
5. U+ Under used which can be adjusted for 3670.16 12.25
better used
6. U Under used. 3437.65 11.47
7, Others. 1028.91 3.41
Total 29,965.91
Table 2. Different Land use Adjustment Class and its Areal Extent
CONCLUSIONS ACKNOWLEDGEMENT
Remote Sensing offers a quick and efficient way to study land
use/land cover and other land features. These data can be
integrated through GIS required for various modelling so as to
enable quantification of erosional soil loss, soil map, land
capability map, etc ultimately leading to generation of the land
use adjustment map essential for making decisions on land use
planning.
REFERENCES
All Indian Soil and Land Use Survey, IARI New Delhi, Soil
Survey Manual, 1978.
Singh, G., Babu, R., and Chandras, 1981. Soil Loss Prediction
Research in India — Central Soil & Water Conservation
Research & Training Institution Dehradun.
Saha, S.K., Kudrat, M., Bhan, S.K., 1991. Erosion, Soil Loss
Prediction, Using Digital Satellite and USLE - Soil Loss
Mapping on Swalik Hills in India.
Suleiman, Z.,Fook, L.k., Saedin, IL, Ramli, K.M.N.H.K. and
Islami, A.H.- Soil Erosion Risk Assessment using RS and GIS
Technologies.
Authors are thankful to Agriculture and Soils Division of IIRS
Dehradun and Orissa Remote Sensing Application Center,
Bhubaneswar for providing technical assistance to the
Dissertation as part of P.G. Diploma course.
APPENDIX
EO = Nil erosion, E1 = Slight erosion, E2 = Moderate erosion,
E3 = Severe erosion, E4 = Very severe erosion.
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