scholarly journals Extent and Rate of Deforestation and Forest Degradation (1986–2016) in West Bugwe Central Forest Reserve, Uganda

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fatuma Mutesi ◽  
John Robert Stephen Tabuti ◽  
David Mfitumukiza
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Forest Degradation ◽  
Land Cover Changes ◽  
Income Generation ◽  
Forest Reserve ◽  
Average Change ◽  
Interview Survey ◽  
Key Drivers ◽  
Restoration Strategies

Understanding the extent of land cover change and the forces behind land cover changes is essential in designing appropriate restoration strategies. Land cover changes at local scales or the factors that lead to cover change have not been documented for much of Uganda. We undertook this study in West Bugwe Central Forest Reserve (WBCFR) to fill this gap. We used remote sensing to determine land cover changes for a 30-year period, 1986–2016, and an interview survey to investigate the drivers of these changes. Our results show that the forest in this reserve has declined extensively by over 82% from 1,682 ha to 311 ha corresponding to an average change of −1.18% per year. The wetland has also been extensively degraded. Both the forest and wetland have transitioned into shrub land. The key drivers that have been highlighted by the survey are poverty (86%), population growth (56%), and associated harvesting of woody products (86%) for subsistence and income generation. We conclude that the forest in WBCFR has been extensively and rapidly deforested and degraded by humans.

scholarly journals Land-use/Land-cover Changes and Deforestation in Effan Forest Reserve, Kwara State, Nigeria

2021 ◽  
Author(s):  
Adesoji Akinwumi Adeyemi ◽  
Farouq Maku Owolabi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Tree Species ◽  
Land Cover Changes ◽  
Indigenous Species ◽  
Land Use Land Cover ◽  
Vitellaria Paradoxa ◽  
Forest Protection ◽  
Forest Reserve

Remote sensing/GIS techniques are a versatile tool for x-raying serial forest structural changes in retrospect. It would be impossible to evaluate past occurrences and changes in forest extents in past decades at Effan Forest Reserve without non-conventional means. Therefore, we adopted remote sensing technology using Landsat images to evaluate land-use change and degradation rates in the area with a view to ascertaining causal factors for possible minimization of forest degradation in Effan Forest Reserve. Land-use/land-cover changes were analyzed using USGS-Landsat TM and ETM images of 1987, 2002, 2014 and 2019. Field-data were collected using handheld GPS receiver and spatial statistical analyses were conducted using the ground control points (GCPs). For inventory data, a systematic sampling technique was adopted using ten 1.05 km-transects at 500 m intervals. A total of 50 sample plots of 50 × 50 m were used. All tree species with Dbh ≥10 cm were enumerated. Nineteen tree species in ten families were encountered with Vitellaria paradoxa as the most-frequently occurring species in the area. IUCN-listed endangered Pterocarpus erinaceus, hitherto abundant in the area, was rarely encountered during the survey, while Vitellaria paradoxa is gradually shrinking, going the relative abundance in the area. The result further showed that primary and secondary forests decreased considerably by 258.03 ha (46.72%) and 9.18 ha (3.63%), respectively, with a total forest loss of 50.3% in 32 years (8.4 hayr-1, 1.6% per annum). While forest plantation size doubled by 369.72 ha within the period. This is worrisome as the remaining fragmented forests appeared to be on the decline, except the riparian vegetation, due to inaccessibility to the riparian by loggers. It thus appeared that forest protection approaches were ineffective. Increased protection efforts could save this forest reserve, and the concerned authority should consider a focused-enrichment planting involving indigenous species for ecosystem-repair.

Remote sensing and GIS forest landscape assessment for sustainable forest management

2021 ◽  
Vol 17 (1) ◽  
pp. 12-26
Author(s):  
A.F. Chukwuka ◽  
A. Alo ◽  
O.J. Aigbokhan
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Forest Cover ◽  
Sustainable Forest Management ◽  
Markov Chain Model ◽  
Remote Sensing Data ◽  
Chain Model ◽  
Spatial Metrics ◽  
Forest Reserve ◽  
Land Cover Types

This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment. Keyword: Landscape, Spatial metrics, sustainable forest and Environment

scholarly journals Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

2014 ◽  
Vol XL-8 ◽  
pp. 613-616 ◽  
Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Remote Sensing And Gis ◽  
Clear Understanding ◽  
Forest Reserve ◽  
Landsat Satellite

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

scholarly journals Land Use/Land Cover Changes in a Disturbed River Watershed Kenya

2019 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
Zachary Gichuru Mainuri ◽  
John M. Mironga ◽  
Samuel M. Mwonga
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Human Needs ◽  
Observation Systems ◽  
Erdas Imagine ◽  
Remote Sensing Image Processing

Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two land use/land cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. In 2000 – 2014 shrub land reduced by-45%, and forestry reduced by -64%. Forestry and shrub land were found to be consistently reducing.

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