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Remote Sensing analysis of Agroforestry in Bathinda and Patiala districts of Punjab using sub-pixel method and medium resolution data

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Title Remote Sensing analysis of Agroforestry in Bathinda and Patiala districts of Punjab using sub-pixel method and medium resolution data
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Creator R.H. Rizvi
Ram Newaj
P.S. Karmakar
A. Saxena
S.K. Dhyani
 
Subject Mapping, Remote Sensing, Sub-pixel,
 
Description This paper is an outcome of NICRA project.
Agroforestry is a land use where trees are deliberately grown with agricultural crops either within the field or on the bunds/ boundary. There are innumerable examples of this traditional land use practices in many parts of the world and has long tradition in India too. In the state of Punjab, farmers prefer to grow tree species like Eucalyptus and Populus on their fields with agricultural crops. Reason for adopting these species by the farmers is their fast growth and use of wood in paper and plywood industries. These agroforestry systems are not only remunerative to the farmers but also improve soil fertility of agricultural fields.
Area under agroforestry in Bathinda and Patiala districts has been assessed by applying pixel and sub-pixel classifiers on medium resolution LISS III data. In case of pixel based classification, area under agroforestry was estimated to be 7.09 and 4.95 per cent in the two districts, respectively. Whereas, area under agroforestry come out to be 14.76 and 13.25 per cent, respectively in case of sub-pixel based classification. Improved results were obtained in case of sub-pixel classifier with more than 85 per cent accuracy. Hence, sub-pixel classifier may be used with medium resolutions data for accurate assessment of area under agroforestry.
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Date 2017-07-22T05:11:11Z
2017-07-22T05:11:11Z
1001-01-01
 
Type Research Paper
 
Identifier Rizvi, R.H., Newaj, R., Karmakar, P.S., Saxena, A. and Dhyani, S.K. 2016. Remote Sensing analysis of Agroforestry in Bathinda and Patiala districts of Punjab using sub-pixel method and medium resolution data. J. of the Indian Society of Remote Sensing 44(4): 657-664.
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http://krishi.icar.gov.in/jspui/handle/123456789/4915
 
Language English
 
Relation Not Available;
 
Publisher Current Science Association