Rapid population growth and increasing economic activities have resulted in unsustainable exploitation and rapid decline in the spatial extent of forest reserves in Nigeria. Studying land use dynamics of these forest ...Rapid population growth and increasing economic activities have resulted in unsustainable exploitation and rapid decline in the spatial extent of forest reserves in Nigeria. Studying land use dynamics of these forest reserves is essential for analysing various ecological and developmental consequences over time. Land use/land cover mapping, change detection and prediction are essential for decision-making and implementing appropriate policy responses relating to land uses. This paper aims at assessing and predicting changes in land use/land cover at Gambari forest reserve, Nigeria using remote sensing and GIS techniques. The study determined the magnitude, rate and dynamics of change in the spatial extent of the forest reserve between 1984 and 2014 using multi-temporal datasets (Landsat TM 1984 and 2000 and OLI/TIRS 2014). The imageries were classified using ArcGIS 10.0 version with support of ground truth data and Land use Change Modeller (LCM) and Markovian processes were employed to analyse the pattern and trend of change. Prediction of 2044 scenario carried out using neural network, which is a built-in module in the Idrisi. The study revealed dramatic decline in the extent of the forest reserve as both the plantation of exotic tree species (Tectona grandis and Gmelina) and the indigenous stands have been logged in several places for timber and to make way for cultivation of crops. In addition, pressures from other land uses like settlements have also led to increased non-forest uses particularly bare grounds. The study concluded that increasing loss of the indigenous forest and plantation would continue thus having implications for biodiversity conservation in the study area. There is the need for participation of different stakeholders and sectors to solve conflicting demands on limited forest resources and ensure ecosystem integrity.展开更多
Between 1981 and 1994, Nigeria lost 3.7 million hectares of its forests. It is estimated that less than 4% of Nigeria’s rainforest cover is left. Reckless use and abuse of the forest reserves in Nigeria lead to degra...Between 1981 and 1994, Nigeria lost 3.7 million hectares of its forests. It is estimated that less than 4% of Nigeria’s rainforest cover is left. Reckless use and abuse of the forest reserves in Nigeria lead to degradation. However, the relationship between forest degradation and climate variability has not been clearly elucidated. This study assesses the trend of forest degradation between 1986, 2002 and 2014 in the study area and also examines the correlation between forest degradation and climate variability using temperature and rainfall parameters. Classification of Landsat images (TM 1986, ETM+ 2002, and OLI 2014) and change analysis using NDVI values of three-timed period were performed to observe forest degradation in the study area. NDVI values were calculated by combining bands 4 (near infrared) and 3 (visible red) for Landsat TM and ETM+ and bands 5 (near infrared) and 4 (visible red) for Landsat OLI using the spatial analysis extension in ArcGIS environment Linear regression statistical analysis was employed to determine the correlation between forest degradation and climate variability. The results show a fluctuation in the trend of forest degradation, while a positive correlation coefficient of 0.58 shows that there is a relationship between forest degradation and temperature and rainfall variability. The study concludes that though there is a positive correlation between forest degradation and climate variability in the study area, the relationship is weak and not strong enough to make generalizations.展开更多
文摘Rapid population growth and increasing economic activities have resulted in unsustainable exploitation and rapid decline in the spatial extent of forest reserves in Nigeria. Studying land use dynamics of these forest reserves is essential for analysing various ecological and developmental consequences over time. Land use/land cover mapping, change detection and prediction are essential for decision-making and implementing appropriate policy responses relating to land uses. This paper aims at assessing and predicting changes in land use/land cover at Gambari forest reserve, Nigeria using remote sensing and GIS techniques. The study determined the magnitude, rate and dynamics of change in the spatial extent of the forest reserve between 1984 and 2014 using multi-temporal datasets (Landsat TM 1984 and 2000 and OLI/TIRS 2014). The imageries were classified using ArcGIS 10.0 version with support of ground truth data and Land use Change Modeller (LCM) and Markovian processes were employed to analyse the pattern and trend of change. Prediction of 2044 scenario carried out using neural network, which is a built-in module in the Idrisi. The study revealed dramatic decline in the extent of the forest reserve as both the plantation of exotic tree species (Tectona grandis and Gmelina) and the indigenous stands have been logged in several places for timber and to make way for cultivation of crops. In addition, pressures from other land uses like settlements have also led to increased non-forest uses particularly bare grounds. The study concluded that increasing loss of the indigenous forest and plantation would continue thus having implications for biodiversity conservation in the study area. There is the need for participation of different stakeholders and sectors to solve conflicting demands on limited forest resources and ensure ecosystem integrity.
文摘Between 1981 and 1994, Nigeria lost 3.7 million hectares of its forests. It is estimated that less than 4% of Nigeria’s rainforest cover is left. Reckless use and abuse of the forest reserves in Nigeria lead to degradation. However, the relationship between forest degradation and climate variability has not been clearly elucidated. This study assesses the trend of forest degradation between 1986, 2002 and 2014 in the study area and also examines the correlation between forest degradation and climate variability using temperature and rainfall parameters. Classification of Landsat images (TM 1986, ETM+ 2002, and OLI 2014) and change analysis using NDVI values of three-timed period were performed to observe forest degradation in the study area. NDVI values were calculated by combining bands 4 (near infrared) and 3 (visible red) for Landsat TM and ETM+ and bands 5 (near infrared) and 4 (visible red) for Landsat OLI using the spatial analysis extension in ArcGIS environment Linear regression statistical analysis was employed to determine the correlation between forest degradation and climate variability. The results show a fluctuation in the trend of forest degradation, while a positive correlation coefficient of 0.58 shows that there is a relationship between forest degradation and temperature and rainfall variability. The study concludes that though there is a positive correlation between forest degradation and climate variability in the study area, the relationship is weak and not strong enough to make generalizations.
