Abstract
Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.
Highlights
Land use and land cover information is required for policy making, business and administrative purposes
Agriculture was found to be the dominant type of Land use classified which covers about 65.0% of the total study area, followed by Built-up areas while the least classified was Barren/bare land which accounts for 0.5%
The commission error is highest in case of built - up areas which meant that more number of points (31) which do not fall under this category are classified as built up areas
Summary
Land use and land cover information is required for policy making, business and administrative purposes. With their spatial details, the data are likewise crucial for environmental protection and spatial planning. M. Ndambuki 612 because it gives data which can be used as input for modeling, especially the one dealing with environment, for instance models deals with climate change and policies developments [1]. The combined LULC grant a comprehensive means of understanding the interaction of geo-biophysical, socioeconomic systems behaviors and interactions [2]. To provide more useful information in land cover, Remote Sensing is often paired with Geographic Information System (GIS) technique
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