Detecting Land Use Modi Cation and Its in Uence on Resident Communities

Detecting Land Use Modication And Its Inuence on Resident Communities Tesfahun Admas Endalew ( [email protected] ) Lecturer at Salale University Research Keywords: Acacia Decurrens, Tree Plantation, Land Use, Change Detection, Supervised Classication Posted Date: September 17th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-71557/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/13 Abstract Background The study intended to detecting the land use land cover changes, trends and their magnitude between 1986 and 2019 years by using GIS and remote sensing in Fagita Lekoma District, Amhara region, Ethiopia. Three satellite data set of Landsat Thematic Mapper for 1986, Enhanced Thematic Mapper Plus for 2002 and Operational Land Imager for 2019 were used generate land use and land cover maps of the study area. Post classication comparison changed detection method was employed to identify gains and losses between Land Use Land Cover classes. Socioeconomic survey, key informant interview and eld observation were also used conclude the encouragement of land use /land cover change in the study area. Results The result shows that cultivated land and wetland similarly decline in the entire study periods. In the 33 years, forest lands expanded by upon 200% of the original forest cover what was existed on the base year. Whereas, a result of the socioeconomic analysis the expansion of Acacia decurrens tree plantations and agricultural land are main causes of land use land cover change in the study area. The impact of this land use land cover change is more signicant on the livelihood condition and status of the study area. Conclusion The land use system of the study area highly converted cultivation land into forest/tree plantation. Mainly, the expansion of Acacia decurrens tree plantation on farmland is increasing the income of local residence when compare with the previous living condition in the study area. Background Global land use and land cover has signicantly changed from the past decades. Historically, the driving force for the majority of land use land cover change is population growth, although there are several interaction factors involved .The growing population has increased demand for land, trees, and water, which, coupled with tenure insecurity or the absence of clear property rights, has resulted in the overexploitation of these natural resources, and this in turn has threatened the sustainable development of agriculture, forestry, and livestock sectors (Dean, 2003). There were signicant global historical changes in LULC between 1700 and 1990, when the area of cropland expanded from about 3.5 million km2 to some 16.5 million km2 (Lambin & Geist, 2002). Even though the net loss of the global forest area had reduced signicantly due to a large scale of afforestation reported in some countries, such as China and Vietnam, tropical deforestation has continued into the 21st century, the world was the past (2000/2005) experienced about 0.073 million km2 of net annual deforestation, largely due to agricultural expansion (FAO, 2010). It was experienced in feature of the poorer countries and the average annual deforestation rate, between 1990 and 2005, in low income countries was 0.5% while deforestation is lower (0.2%) in middle income countries (World Bank, 2007). Of course agricultural activities in sub-Saharan Africa are dependent on variable climate and land use land cover change. In addition to this, farmers in Africa live on small hectare of farmland so it creates a great opportunity to divert one land use system to another. Decimation of farm size accelerates and hence obstacle efforts to increase farm productivity. Therefore, in line with augmenting agricultural productivity, looking for other way out has been put forward as an equally potent strategy for addressing household food security (Briassoulis, 2019). Through time such changes have benecial while inversely they have had detrimental and adverse impacts on the environment and people’s economic activities (Briassoulis, 2019). Studies of rates, patterns, and implications of LULC dynamics at local level can help to design appropriate land management practices, strategies and policies (Daniel, 2008). Gathering information about Land Use Land Cover changes is fundamental for a better understanding of the Page 2/13 relationships and interactions between humans and the natural environment. Remote sensing data have been one of the most important data sources for studies of LULC spatial and temporal changes (Mesn, 2016). Land use change status was happened through time processes. Then this change has impacts on livelihood of the people and environmental condition (Daniel, 2008). In the study area the recent history through the intervention of government and the intentionally of communities started to cover their land by vegetation especially Accacian decurrens and Eucalyptus tree plantation as local people investment at the district level. These expansions of tree plantation taken as the initial issue of land use land cover change and have impacts on the socioeconomic activities of the local people. Therefore, this study analyses historical patterns of land use/cover and consequences that occurred between over a period of three decades (1986–2019) in the study area. Methods And Materials Geographical location Fagita Lekoma district is one part of the Awi Zone in Amhara region Northwestern of Ethiopia. Fagita Lekoma is bordered on the south by Banja Shekudad, on the west by Guangua, on the north by Dangila, and on the east by the Mirab Gojjam Zone. Towns in Fagita Lekoma include Addis Kidam and Fagita Lekoma woreda is located between10°57’23’’-11°11’21’’North latitude and 36°40’01’’-37°05’21’’ longitude, in Awi Zone of Amhara National Regional State. It is situated about 460 km northwest of Addis Ababa and 100 km southwest of Bahir Dar, the capital city of Amhara regional state. Data acquisition and image classication approach In order to cover the intended period of study, different types of imageries originating from different types of sensors were used. The images were obtained from United States Geological Survey (www.USGS.gov). Data type Year Data acquisition Sensor Path and Row Resolution Source of data Months Landsat 1986 Jan 01 ETM 170/52 30M USGS Landsat 2002 Jan 05 ETM+ 170/52 30M USGS Landsat 2019 Jan 16 OLI 170/52 30M USGS Tabe.1 The satellite data source characteristics Images from different time periods were used for the classication of LULC of the study area. That is multi temporal raw satellite data has been imported to Erdas Imagine 2010 image processing software. Image processing consists of processes aimed at the geometric and radiometric correction, standardization of imagery to improve our ability to interpret qualitatively and quantitatively image components. Since the United States Geological Survey (USGS) freely offers the Landsat Orthorectied data which consists of a global set of high-quality, relatively cloud-free Orthorectied TM, ETM+ and OLI imagery therefore there is no need for geometric correction but check the position. After all, land use land cover change maps and land cover statistics were generated to compare the temporal change of the study area for the past three decades by using ArcGIS 10.4 and ERDAS Imagine 2010 integrally. Development of a Classication Scheme Based on the prior knowledge of the study area and a brief reconnaissance survey a classication scheme was develop for the study area as following in the table 2 Based on denitions of LULC types given above are a modication of Anderson’s classication scheme in 1976. Page 3/13 LULC Description class Cultivated Includes annual rain fed and irrigated cultivation. Lands mostly used for cereal production in subsistence land farming and mixed with bushes. Grassland Predominantly covered by small grasses with a small proportion of shrub and trees. Tree Includes densely growth trees forming closed canopy. The predominant species are Bahirzaf (Eucalyptus tree), plantation Chigegn (Acacia decurrens) and Kerkeha (Arundinaria alpine) or Bamboo forest. Note that, sparsely natural forests which are found in the study area including under tree plantations. Because which haven’t a known ratio to differentiate from one others. Wetland Represents most plains areas with frequent ooding event during the rainy season and water table is at, near, or above the land surface for a signicant part of most years. settlement Area occupied by small town and settlement including market places, roads, and institution Table 2 the land use land covers class and their descriptions. Methods of Supervised Classication and Data Analysis To perform the classication the maximum likelihood supervised classier was employed. Training areas for all spectral classes were developed composing each information class to be identied by the classier. Since there was more than one spectrally different signature found for each information class. The researcher used more than thirty training samples for each classication. A recode function was used to merge spectrally different classes to generate nal information classes. The post classication approach was used for mapping detailed LULC determination. This approach is generally considered the most obvious approach to change detection. It requires the comparison of independently classied images of the same study area acquired over two different time periods. One advantage of using post-classication change detection is that data normalization for atmospheric and sensor differences between two date is not required, since images acquired for two dates are classied separately (Singh, 1989). Change statistics were computed by comparing values of area of one data set with the corresponding value of the second data set in each period. Percentage change to determine the trend of change can then be calculated by dividing observed change by sum of changes multiplied by 100 (Puyravaud, 2003). Results And Discussions Cultivated land, grassland, wetland, forest and urban area are the major LULC classes for the study area and periods.

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