Ibadan has experienced a rapid urbanization over the past few decades due to heavy influx of people from different parts of the country as a result of improved economy of the region. This development induced a great c...Ibadan has experienced a rapid urbanization over the past few decades due to heavy influx of people from different parts of the country as a result of improved economy of the region. This development induced a great change in land use and land cover over the region which has become a major environmental concern recently. This study assessed Land Surface Temperature (LST) and its spatio-temporal relationship with land cover type over Ibadan. Land use/Land cover dynamics were assessed using index maps generated from Landsat Satellite data (TM, ETM+ and OLI) of Ibadan. The corrected thermal Infrared bands of the Landsat data were used to retrieve LST. The results revealed a notable increase in built-up areas from 5.64% of the total land cover area in 1984 to 14.05% in 2014. This change has caused increase in surface temperature of Ibadan from 3.56?C to 8.54?C between 1984 and 2014 respectively. The study recorded a continuous decrease in the vegetal part of Ibadan (from 43.28% in 1984 to 14.76 in 2014) which could be attributed to anthropogenic activities as the vegetated land area lost was been converted to other form of land use. The change was found to be positively correlated to the surface temperature intensity over the region with correlation coefficient, r value of 0.9251, 0.8256 and 0.7017 in 1984, 2000 and 2014 respectively. It is recommended that Policies should be considered for planting trees, new guidelines for urban landscape design and construction.展开更多
Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of m...Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.展开更多
Land use Land cover (LULC) has undergone progressive changes worldwide over the years. However, there is limited information available about these changes in Oba Hills Forest Reserve, Nigeria. The existing spatial ana...Land use Land cover (LULC) has undergone progressive changes worldwide over the years. However, there is limited information available about these changes in Oba Hills Forest Reserve, Nigeria. The existing spatial analysis of the forest excluded important land use classes like settlements. Therefore, this study aimed at assessing the dynamics of LULC in Oba Hills Forest Reserve between 1987 and 2019. Images from Landsat 5, Landsat 7, and Landsat 8 for the years 1987, 2001, 2013, and 2019 were obtained and subjected to preprocessing and classification using the maximum likelihood algorithm, change detection, and Normalized Differential Vegetation Index (NDVI). The coordinates of specific benchmark locations and other points were acquired for ground-truthing and developing Digital Elevation Model (DEM). Three distinct LULC classes were identified: forest, bare land (including open spaces, agriculture, rocks, and grasslands), and built-up areas. The forest cover in the reserve gradually decreased from 56% in 1987 to 47% in 2019, resulting in a total area loss of 455.4 hectares. Correspondingly, the other LULC classes experienced exponential expansion. Bare land increased from 44% in 1987 to 52% in 2019, while the built-up area expanded by 57.28 hectares. These changes are attributed to prevalent anthropogenic activities such as agriculture, grazing, logging, firewood collection, and population growth within the catchment area. The declining NDVI values in the forest reserve, from 0.52 to 0.44 within the years of assessment, further substantiated the substantial loss of forest cover. The DEM and topographical map highlighted notable steep slopes and elevations of up to over 550 m above sea level (asl) within the reserve, which have implications for forest growth and dynamics. In conclusion, this study reveals extensive rates of forest cover changes into bare land, primarily for agriculture, and settlements, and offers further recommendations to reverse the trend.展开更多
文摘Ibadan has experienced a rapid urbanization over the past few decades due to heavy influx of people from different parts of the country as a result of improved economy of the region. This development induced a great change in land use and land cover over the region which has become a major environmental concern recently. This study assessed Land Surface Temperature (LST) and its spatio-temporal relationship with land cover type over Ibadan. Land use/Land cover dynamics were assessed using index maps generated from Landsat Satellite data (TM, ETM+ and OLI) of Ibadan. The corrected thermal Infrared bands of the Landsat data were used to retrieve LST. The results revealed a notable increase in built-up areas from 5.64% of the total land cover area in 1984 to 14.05% in 2014. This change has caused increase in surface temperature of Ibadan from 3.56?C to 8.54?C between 1984 and 2014 respectively. The study recorded a continuous decrease in the vegetal part of Ibadan (from 43.28% in 1984 to 14.76 in 2014) which could be attributed to anthropogenic activities as the vegetated land area lost was been converted to other form of land use. The change was found to be positively correlated to the surface temperature intensity over the region with correlation coefficient, r value of 0.9251, 0.8256 and 0.7017 in 1984, 2000 and 2014 respectively. It is recommended that Policies should be considered for planting trees, new guidelines for urban landscape design and construction.
基金Under the auspices of National Natural Science Foundation of China(No.41230751,41101547)Scientific Research Foundation of Graduate School of Nanjing University(No.2012CL14)
文摘Hyperspectral data are an important source for monitoring soil salt content on a large scale. However, in previous studies, barriers such as interference due to the presence of vegetation restricted the precision of mapping soil salt content. This study tested a new method for predicting soil salt content with improved precision by using Chinese hyperspectral data, Huan Jing-Hyper Spectral Imager(HJ-HSI), in the coastal area of Rudong County, Eastern China. The vegetation-covered area and coastal bare flat area were distinguished by using the normalized differential vegetation index at the band length of 705 nm(NDVI705). The soil salt content of each area was predicted by various algorithms. A Normal Soil Salt Content Response Index(NSSRI) was constructed from continuum-removed reflectance(CR-reflectance) at wavelengths of 908.95 nm and 687.41 nm to predict the soil salt content in the coastal bare flat area(NDVI705 < 0.2). The soil adjusted salinity index(SAVI) was applied to predict the soil salt content in the vegetation-covered area(NDVI705 ≥ 0.2). The results demonstrate that 1) the new method significantly improves the accuracy of soil salt content mapping(R2 = 0.6396, RMSE = 0.3591), and 2) HJ-HSI data can be used to map soil salt content precisely and are suitable for monitoring soil salt content on a large scale.
文摘Land use Land cover (LULC) has undergone progressive changes worldwide over the years. However, there is limited information available about these changes in Oba Hills Forest Reserve, Nigeria. The existing spatial analysis of the forest excluded important land use classes like settlements. Therefore, this study aimed at assessing the dynamics of LULC in Oba Hills Forest Reserve between 1987 and 2019. Images from Landsat 5, Landsat 7, and Landsat 8 for the years 1987, 2001, 2013, and 2019 were obtained and subjected to preprocessing and classification using the maximum likelihood algorithm, change detection, and Normalized Differential Vegetation Index (NDVI). The coordinates of specific benchmark locations and other points were acquired for ground-truthing and developing Digital Elevation Model (DEM). Three distinct LULC classes were identified: forest, bare land (including open spaces, agriculture, rocks, and grasslands), and built-up areas. The forest cover in the reserve gradually decreased from 56% in 1987 to 47% in 2019, resulting in a total area loss of 455.4 hectares. Correspondingly, the other LULC classes experienced exponential expansion. Bare land increased from 44% in 1987 to 52% in 2019, while the built-up area expanded by 57.28 hectares. These changes are attributed to prevalent anthropogenic activities such as agriculture, grazing, logging, firewood collection, and population growth within the catchment area. The declining NDVI values in the forest reserve, from 0.52 to 0.44 within the years of assessment, further substantiated the substantial loss of forest cover. The DEM and topographical map highlighted notable steep slopes and elevations of up to over 550 m above sea level (asl) within the reserve, which have implications for forest growth and dynamics. In conclusion, this study reveals extensive rates of forest cover changes into bare land, primarily for agriculture, and settlements, and offers further recommendations to reverse the trend.
