JAPRS & SIS, Vol.34, Part 7, “Resource and Environmental Monitoring”, Hyderabad, India, 2002 
LAND EVALUATION FOR MANGO ORCHARD SUITABILITY ANALYSIS USING 
REMOTE SENSING AND G.LS. 
Narendra Kumar **, Arvind Tripathi *, S.K. Saha ^, Udai Raj *, 
P.C.Gupta * & A.N.Singh * 
"Remote Sensing Applications Centre, U.P.,Lucknow, India. 
rsacup @sancharnet.in 
"Indian Institute of Remote Sensing, Dehradun, India. 
sksaha@iirs.gov.in 
KEY WORDS: FAO framework, ARC/INFO, Land evaluation, Soil suitability for mango, IRS LISS-III. 
ABSTRACT: 
Agricultural resource management has acquired a new dimension in the new millenium. The increasing demand for fruit crops need 
proper management of existing orchards and selection of areas for developing new orchards. A study was conducted in Siyana block, 
which is declared as a fruit belt, in Bulandshahr district of U.P., India. The study used satellite data and GIS technique for assessing the 
acreage under mango orchard in different villages and for land evaluation for plantation of mango. Land suitability criteria for mango 
orchard was developed based on soil and terrain qualities and their rating for mango. FAO framework of land evaluation has been 
employed to assess the potential soil suitability of mango orchard and site suitability maps were generated using GIS. 
Using IRS, LISS-III satellite data, mango orchard under two major age groups viz., more than 15 years and 5 to 15 years were 
classified using maximum likelihood algorithm. Orchards having trees less than 5 years age could not be separated due to maximum 
soil exposure. Village-wise mango area was estimated using GIS.Geo-referenced classified map showing mango orchards and the land 
evaluation map were overlaid using GIS to find out new areas available for expansion of mango orchard. The study showed that IRS 
LISS-III data is useful for discrimination of mango orchard on the basis of age groups and for village-wise mango crop distribution 
inventory. Using FAO framework for land evaluation, new suitable sites for mango orchard were identified in the study area, which 
may be helpful for Horticulture Dept. in their mango intensification programme. 
1. INTRODUCTION 
Mango (Mangifera indica L.), the most important fruit crop of 
India is known as the king of fruits of this country. Covering 
about 1.28 million ha area, its total annual production is 10.9 
million tonnes (Sharma and Sharma, 2002). Out of total area 
under fruit crops, mango occupies 43%. Uttar Pradesh ranks 
second in mango area and production in the country. Although, 
India contributes 56% in the world mango production, the 
productivity in India (9.25 t/ha) is much lower than some other 
countries namely Israel, South Africa, Philippines and Cambodia 
with 11-27 t/ha (Ram, et al. 2001) Satellite based remote sensing 
is operationally being used for area estimation of major crops 
such as rice, wheat, sugarcane, mustard and cotton etc. 
(Navalgund et al., 1991). Efforts for discrimination, mapping and 
acreage estimation of major horticultural crops using remote 
sensing techniques have also been made (Gupta and Sharma, 
1990 and Ravindran et al, 1997). The National Horticultural 
Conference held at New Delhi during December 1993 has 
identified that the weak database on area, production and 
productivity of horticultural crops is one of the major constraints 
in the development of Indian horticulture. In Bulandshahr district 
of Uttar Pradesh, India, two 
mango fruit belts have been declared by the state Govt. viz, 
Siyana and Unchagaon. The Govt. is providing subsidy and 
technical support to farmers for development of new orchards in 
  
these areas. Due to this, area of mango orchard has been increased 
but poor quality of existing information system has failed to 
provide the information on mango orchard area and suitable sites 
accurately for developing new orchard. Keeping this in view, the 
present study was taken up with the objectives of estimating the 
acreage of mango orchards under different age groups and 
selecting new sites for mango orchards using F.A.O. framework 
of land evaluation in Siyana block of Bulandshahr district. 
2. DATA USED 
Following data were used in the study: 
l. IRS-ID, LISS-III digital data of 3 May, 2000 for Path — 
Row 97-51. 
Survey of India Toposheets on 1:50,000 scale. 
Directorate of census village map of the study area. 
Soil map of Siyana Block. 
Field data in the form of ground truth information. 
nA FM 
3. STUDY AREA 
The study area is Siyana Block of Bulandshahr district, Uttar 
Pradesh, India. This area falls between geographic coordinates 
of Latitude 28° 32’ to 28° 41’ and Longitude 77°11’ to 78°11’ 
(fig. 1), and is covered by 53H/14 and 53L/2 Survey of India 
    
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