Land Use/Land Cover Changes of Ago-Owu Forest Reserve, Osun State, Nigeria Using Remote Sensing Techniques

Abstract

Remote sensing (RS) and GIS are important methods for land use assessment and land cover transition. In this study, land use/land cover changes in the Ago-Owu Forest Reserve, Osun State, Nigeria have been assessed. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were acquired for 1986, 2002 and 2017 respectively. The three scenes corresponded to path 190 and row 055 of WRS-2 (Worldwide Reference System). The processing of the imagery was preceded by the clipping of the study area from the satellite image. The boundary of the reserve was carefully digitized and used to clip the imagery to produce an image map of the forest reserve. Using the supervised image classification procedure, training sites were used to produce land use/land cover maps. The same classification scheme was used for the 1986, 2002 and 2017 images to facilitate the detection of change. The differences in the area covered by the different polygons between the three sets of images were measured in km 2. The results show that during 1986 and 2017, there is a dramatic increase of build-up areas with a change of 55.65 km 2 and sparse vegetation (farmland and grassland) with a change of 53.97 km 2 , while a dramatic decrease of dense vegetation (forest areas) with a change of 109.61 km 2. The consequence of these results is that over the years, the population of people living in the forest reserve has increased and many of them are engaged in farming, leading to an increase in farmland. In addition, logging activities continued unabated in the forest reserve, as demonstrated by a sharp increase in the deforested area within the reserve. The maps produced in this study will serve as a planning tool for the Osun State Forestry Department to plan reforestation activities for the forest reserve.

Enhancing Forest Landscape Spatial Data Modeling through Cloud-Based Approaches: A Case of Oluwa Forest Reserve, Ondo State, Nigeria

“…Due to cultivation and the rising demand for wood resources, plantations and natural forests underwent deforestation, degradation, and exploitation as a result of the development of agricultural land and grassland. Because the majority of the soils in the Reserve are nutrient-rich and excellent for agricultural production, the rich soils are more vulnerable to agricultural growth (Meshach et al 2020).…”

“…Plantations and natural forests endured destruction, degradation, and exploitation due to cultivation and the increasing need for wood resources as a result of the creation of agricultural land and grassland. Rich soils are more susceptible to agricultural growth because the majority of the Reserve's soils are nutrient-rich and ideal for agricultural output (Meshach et al 2020). To assure the preservation of the natural forest, for instance, fifty seedlings of the same species as those that were cut down might be planted, but this raises the possibility of losing further indigenous species.…”

The study of land use and land cover (LULC) dynamics and the perception of local people in Aykoleba, Northern Ethiopia

“…A study by Wubie et al (2016) reported that increased demand for fuel wood in the absence of alternative sources of energy has led to devastation of forests. Similarly, persistent logging activities in the forest reserve resulted in its loss in Nigeria (Aderele et al, 2020). Deforestation by the local people for different purposes caused land use change in southern part of the country (Mathewos, 2019).…”

“…This could have been due to a speedy annual population growth in the area by 2.7% (CSA, 2007), which probably required extra agricultural land. Similar, a study from Nigeria shows that the raise in the number of human population living in the forest reserve led many of them to be employed in farming, leading to an increase in farmland at the expense of forestland (Aderele et al, 2020). The land use policy changes, mainly land reform proclamations in the country between 1975 and 1997, and the loss of land productivity due to unsustainably farming have also significantly aided for the decline in the forest cover.…”

Land Use Classification Method of Remote Sensing Images for Urban and Rural Planning Monitoring Using Deep Learning

“…In recent years, with the continuous development of China's economy and the accelerated pace of urbanization, a large amount of land has been continuously developed and requisitioned. Especially in the eastern coastal areas, buildings and road networks extend to rural areas and primitive forest areas, and a large proportion of vegetation has been destroyed, resulting in Earth shaking changes in the original land cover [2,3]. erefore, using remote sensing technology to obtain high-resolution images of land cover to classify and study the surface is not only conducive to environmental protection but also conducive to the steady improvement of the national economy and the healthy development of urban and rural areas [4].…”