International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 06 | Jun 2024
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p-ISSN: 2395-0072
Analysis of Land Use and Land Cover Changes in Buraimi City of Oman Using Remote Sensing and GIS Wael Albawwab1, Tauseef Ahmad Ansari2, Assistant Professor1, University of Buraimi, Oman. Assistant Professor2, University of Buraimi, Oman. -------------------------------------------------------------------------***-----------------------------------------------------------------------Abstract: The study of Land Use (LU)/ Land Cover (LC) dynamics in the face of climate change is critical for better long-term ecological management. This study aimed to detect the changes occurred in the LU/LC from 2002 to 2022 in Buraimi city of Oman. The satellite images for the years 2002 and 2022 were taken from Google Earth Pro. In this study, four types of LU/LC (i.e. vegetation cover, built-up areas sparse built-up and open lands) are estimated. This study shows that built-up area, vegetation area and sparse built-up area has been increased by 7.64 km2, 0.787 km2 and 15.23 km2 respectively, while the open land area has decreased by 23.65 km2. This study will help understand the urban development in the city and manage the land use for sustainable development.
Key Words: Land Use (LU)/ Land Cover (LC), Remote Sensing and GIS, Google Earth Pro, Sustainable Development etc. Introduction: The terms land use and land cover are frequently used together. However, they have quite distinct meanings. Any surface cover on the ground such as vegetation, urban infrastructure, water, bare soil, or other ground surface covers can all be referred to as land cover. When it comes to global monitoring studies, resource management, and planning activities it is important to identify, delineate and map land cover. Land cover identification creates a foundation out of which monitoring operations may be conducted, as well as providing ground cover data for baseline thematic maps. The purpose that the land serves is being known as land use. Subsequent monitoring and baseline mapping are both involved in applications that are used by land use because it is required to know what type of land is used and in what quantity to identify the changes on land use from year to year. This is done by the timely information gathered. This information will aid in the creation of plans to balance conservation, competing uses, and development pressures. The loss or disruption of fertile land, urban expansion, and forest depletion are all issues that are driving land use research. According to (Lopez et al. 2001), the huge increase in population is the most important element in the global shift of land use. Previous research has found a direct link between LU/LC and anthropogenic impacts, salinization, groundwater availability and quality, and hydro-meteorological parameters (Dias et al. 2015). The use of remote sensing and hydrological datasets in a GIS framework has been proven to be a good way to examine the effects of LU/LC change on groundwater quantity and quality on a broad scale at a cheap cost and with improved precision (Zampella et al. 2007). Because of their excellent georeferencing processes, digital format suited for computer processing, and recurrent data collecting, satellite remote sensing and GIS are the most used approaches for quantification, mapping, and detection of LU/LCC trends (Lu et al. 2004). Nuez et al. 2008; Rahman et al. 2011). Chen et al. 2005; Nuez et al. 2008; Rahman et al. 2011). To estimate land cover changes in central and southern lake areas using Landsat data, Shalaby and Tateishi (2007) found different forms of LU/LC in Egypt's coastal zone. Gao and Liu (2010) managed to discover a soil erosion trend in central China that occurred over a 10-year period owing to soil contamination and flash floods. It labels information from numerous dates separately; therefore, proper comparison of multi-date dataset does not quite necessitate any adjustments (Singh 1989; Rivera 2005; Zhou et al. 2008; Warner and Campagna 2009). Mohammed Feras Baig (2022) made a study to assess changes to LU/LC and predict any further changes that can happen to Selangor, Malaysia. The study was done by using satellite images that were used to develop maps by SVM (support vector machine) from the year 1991 to the year 2021. Validation metrics were used to show that the spectral analysis mapper did not perform as good as the support vector machine did. There were six LU/LC classification used to base the images used in this study on, namely are water, development, barren, forest, agriculture, and wetlands. The satellite imagery has shown an area increase in developed, barren and water lands. However, there was a decrease in areas of agricultural, forest and wet lands.
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