GRD Journals | Global Research and Development Journal for Engineering | Emerging Research and Innovations in Civil Engineering (ERICE - 2019) | February 2019
e-ISSN: 2455-5703
Application of Remote Sensing and GIS in Cropping Pattern Mapping: A Case Study of Olpad Taluka, Surat 1Kakadiya
Bhumika 2Babulal M. Vadher 3P. G. Agnihotri P. G. Student 2Principal and Professor 3Professor 1 Department of Civil Engineering 1,2 Government Engineering College, Surat, Gujarat, India 3Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat, India 1
Abstract India is an agricultural dominated country. Agriculture is a backbone of India. Nearly 65% of population is dependent on this sector. Hence study of crops and cropping pattern play a vital role to increase the crop production. In this study an attempt will be made to map the different cropping pattern followed in Olpad taluka of Surat, Gujarat. A multidate Landsat satellite data from USGS will be used to generate cropping pattern and study of crop rotation during Kharif and Rabi will be carried out. To accomplish this Arc GIS software of (ESRI) will be used. This map is validated by taking the ground truth data using GPS receiver in the study area to improve the accuracy of the mapping. Various vegetation indices will be calculated using GIS and RS to access the efficiency of cropping system. Keyword- Cropping Pattern, GIS, Remote Sensing, Vegetation Indices __________________________________________________________________________________________________
I. INTRODUCTION With the increasing population the pressure on the limited agricultural resource is ever increasing. The total population in India is projected to be 1.62 billion by 2050. Consequently, the question before us which needs to be answered is how to use rapidly shrinking per capita land resources in a sustainable manner. Agriculture and allied sectors contribute 13.9 per cent of Gross Domestic Product (GDP) and play a vital role in the Indian economy where nearly 65 per cent of the rural households depend on agriculture. Cropping pattern is a spatial phenomenon and refers to sequence and arrangements of crops in an area at a point of space and time. The cropping patterns and intensity of a region are closely influenced by a spectrum of factors including geoclimatic, socio-economic, historical and political factors. Cropping pattern analysis is essential for studying the sustainability of agriculture. Remote sensing and Geographical Information System (GIS) has become very useful tools for the management of dynamic agricultural resource. Satellite imagery has made it possible to map croplands and identify crop types at local, regional and global level. In recent times satellite data has proved to be a valuable source to acquire timely, cost effective and precise information (M.P.Sharma 2014) in spatial domain about the existing cropping systems. Various authors have revealed the usefulness of satellite data for cropping pattern analysis. Analysis of cropping pattern using field observation is very laborious so satellite imagery gives us better option for analysis of cropping pattern. So, this study is carried out to find how effectively we can use satellite imagery for cropping pattern mapping.
II. STUDY AREA Olpad is agriculturally prosperous taluka of Surat Gujarat. The study area (Olpad Taluka) is bounded by 20° 0' 0" to 21° 7' 48" north latitude and 72° 22' 48" to 74° 13' 48" east longitude region of south Gujarat. Population is about 2 lakh is Surat district's the 6th least populous sub district, located in Surat district of the state Gujarat in India. There are 104 villages in the Olpad as shown in fig 1, among them Olpad is the most populous village with population of about 16 thousand and Thothab is the least populous village with population of 170. A. Topography Olpad taluka’s total area is 560 km², and the density of Olpad taluka was 360 per sq.km at the 2011 Census. Dandi is the biggest village in the sub district with an area of 69 km2 and Bhagwa is the smallest with 1 km2. 70% of area of taluka has deep to medium black soil. 30% area is coastal zone which has deep, fine texture, salt affected soil.
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