Introduction
In the state of Uttar Pradesh, nearly 1.2 million hectares area is under saline and sodicland (logically 'USAR'). For reclamation of sodicland in the 10 districts of Uttar Pradesh viz., Aligarh, Allahabad, Etah, Etawah, Hardoi, Fatehpur, Mainpuri, Pratapgarh, Raebareli and Sultanpur, a pilot project was taken up with the assistance of the World Bank. Selection of villages for reclamation in each district through conventional methods is time consuming and involves lot of calculations. Collaborative decision problems such as site selection can be analyzed and supported efficiently with user-friendly computer systems, combining remote sensing, GIS multicriteria analysis techniques and environmental modeling (Greetman & Toppen 1990, Fedra & Jamieson 1996, Fedra et al 1996). Remote sensing and GIS have emerged as powerful tools in isolating favorable zones from unfavorable ones. Spatial data generated on vegetation, land cover, soils, geology and hydrogeology using remote sensing can be effectively used in conjunction with ground information in GIS domain for different reclamation activities such as site selection, soil monitoring, groundwater monitoring in a more scientific manner. Because GIS has capability to capture, store, manipulate and analyze various types of spatial & non-spatial information into a single spatial framework, which is very important for any further monitoring and analysis.
The present paper describes how effectively GIS has been utilized in selection of suitable site for sodicland reclamation activities to be carried out based on certain criteria. The analysis work was done for Raebareli district for optimum selection of villages for sodic land reclamation.
Different thematic map layers viz. Sodicland (land use/Wasteland), Drainage, Electrical Conductivity (EC), Residual Sodium Carbonate (RSC), Depth to Groundwater and Village boundary have been converted to Arc/Info GIS coverages. Each of these layers in GIS was analyzed based on set criteria by assigning a weight and suitable rank values. Cumulative weightage was calculated by multiplying the weight values with multiplication factor decided based on rank. Outputs of all the five maps were integrated to produce the final output, which indicates the villages satisfying, set criteria in four ranges. These ranges indicate the priority of villages for reclamation.
Criteria Table
| | | | Suitability Ranking | | | |
| S.No | Description | Weight | Rank1 | Rank2 | Rank3 | Rank4 |
| 1. | Sodic area (percentage) | 2 | >30 | 25-30 | 15-25 | <15 |
| 2. | Stream network distance (km) | 2 | 0-0.5 | 0.5-1 | 1-2.0 | >2.0 |
| 3. | Electrical conductivity (dS/cm) | 2 | £2.0 | -- | -- | >2.0 |
| 4. | Residual Sodium Carbonate (meq/l) | 2 | £1.5 | -- | -- | >1.5 |
| 5. | Depth to groundwater (m) | 2 | 3-8 | 8-10 | 2-3 | <2& >10 |
| | Multiplication factor (MF) | 3 | 2 | 1 | 0 | |