Using remote sensing technologies to enhance resource conservation and agricultural productivity in underutilized lands of South Asia

Satisfying the food demands of an ever-increasing population, preserving the natural resource base, and improving livelihoods are major challenges for South Asia. A large area of land in the Middle and Lower Gangetic Plains of South Asia remains either uncultivated or underused following the rice harvest in the kharif (wet) season. The area includes "rice-fallow," estimated at 6.7 million ha, flood-prone riversides ("diara lands," 2.4 million ha), waterlogged areas (4.9 million ha), and salt-affected soils (2.3 million ha). Bringing these lands under production could substantially improve the food supply and enhance livelihoods in the region. This paper describes a methodological case study that targeted resource-conserving technologies in underused lands of the Ballia District of eastern Uttar Pradesh (India) using multispectral remote-sensing images. Classification of temporal satellite data IRS-P6 in combination with Spot VGT 2 permitted the identification of all major categories of underused land during the post-rainy rabi/winter season, with an average accuracy of 89%. Based on three-year averages of field demonstrations, farmers gained an additional income of $63 ha(-1) by introducing raised beds in salt-affected soils; $140 and $800 ha(-1) by introducing deepwater rice varieties (monsoon) and boro rice (winter) in waterlogged areas; and $581 ha(-1) by introducing zero-till lentil (winter) in rain-fed fallow lowland. Timely wheat planting through zero-tillage implies an additional income of $147 ha(-1) and could increase wheat production by 35,000-65,000 tons in the district. The methodologies and technologies suggested in the study are applicable to more than 15 million ha of underutilized lands of the Indo-Gangetic Plains of South Asia. If the technologies are precisely applied, they can result in more than 3000 million US $ of additional income every year to these poverty prone areas. (C) 2011 Elsevier Ltd. All rights reserved.