Abstract
Abstract. Land cover mapping using remote-sensing imagery has attracted significant attention in recent years. Classification of land use and land cover is an advantage of remote sensing technology which provides all information about land surface. Numerous studies have investigated land cover classification using different broad array of sensors, resolution, feature selection, classifiers, Classification Techniques and other features of interest from over the past decade. One, Pixel based image classification technique is widely used in the world which works on their per pixel spectral reflectance. Classification algorithms such as parallelepiped, minimum distance, maximum likelihood, Mahalanobis distance are some of the classification algorithms used in this technique. Other, Object based image classification is one of the most adapted land cover classification technique in recent time which also considers other parameters such as shape, colour, smoothness, compactness etc. apart from the spectral reflectance of single pixel.At present, there is a possibility of getting the more accurate information about the land cover classification by using latest technology, recent and relevant algorithms according to our study. In this study a combination of pixel-by-pixel image classification and object based image classification is done using different platforms like ArcGIS and e-cognition, respectively. The aim of the study is to analyze LULC pattern using satellite imagery and GIS for the Ahmedabad district in the state of Gujarat, India using a LISS-IV imagery acquired from January to April, 2017. The over-all accuracy of the classified map is 84.48% with Producer’s and User’s accuracy as 89.26% and 84.47% respectively. Kappa statistics for the classified map are calculated as 0.84. This classified map at 1:10,000 scale generated using recent available high resolution space borne data is a valuable input for various research studies over the study area and also provide useful information to town planners and civic authorities. The developed technique can be replicated for generating such LULC maps for other study areas as well.
Highlights
Land cover mapping using remote-sensing imagery has attracted significant attention in recent years
The aim of the study is to analyze Land use/ Land cover (LULC) pattern using satellite imagery and Geographical Information System (GIS) for the Ahmedabad district in the state of Gujarat, India using a LISS-IV imagery acquired from January to April, 2017
The over-all accuracy of the classified map is 84.48% with Producer’s and User’s accuracy as 89.26% and 84.47% respectively
Summary
Land use/ Land cover (LULC) plays an important role in global climate as well as topographic change. The spatial distribution of land use/ land cover changes over a large area can be studied using Remote Sensing techniques and Geographic Information Systems. Land use / Land Cover mapping methods have become more advanced and more informative with high resolution dataset in recent time period These methods are dependent on images interpretation and ground survey. There are two Traditional types of classification procedure and each of these types finds application in the processing of remote sensing images: one is referred to as supervised classification and the other one is unsupervised classification These can be used as alternative approaches, but are often combined into hybrid methodologies using more than one method (Richards and Jia, 2006) but Object-oriented image classification methods provide a promising tool for mapping detailed land cover (Mori et al, 2004)
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