Mapping and Analysis of Vegetation Spectral Reflectance in Oil and Gas Seepage Polluted Zones Using Six Vegetation Indices

The growth and health of vegetation may be adversely influenced by oil and gas pollution or leakage.  Thus, when an environment is contaminated with oil and gas pollution, growing vegetation often exhibit signs of stress.  Satellite remote sensing has proven to be an effective tool and approach to detect and monitor vegetation health and status in oil and gas polluted zones.  Previous studies have adopted vegetation indices which are obtained from remotely sensed satellite data to monitor vegetation health.  This study is aimed at demonstrating the potential of vegetation spectral techniques for detecting and monitoring of oil and gas pollution from Landsat 8 OLI/TIRS remotely sensed data.  To determine the influence of oil and gas pollution on vegetation reflectance, few polluted sites were analyzed and their reflectance were compared in all the TM bands against the non – polluted sites.  The mean and standard deviation reflectance of each of the bands in two groups of sites and t – test are calculated to determine if there are any significant differences between the reflectance from the polluted and non – polluted sites.  Thus, the study shows that in all the spectral bands, the vegetation reflectance from polluted and non – polluted areas exhibit small significant difference with a p-value >0.005. To further analyze the impacts of oil and gas on vegetation, six spectral indices including NDVI, SRI, MSAVI2, SAVI, ARVI2 and EVI2 were utilized.  SRI, SAVI and EVI2 showed no significant relationship between polluted and non-polluted areas with a p-value >0.05 higher than the alpha level of 0.05 and the calculated t - test value is lower than the t-critical value of 2.09 while NDVI, MSAVI2 and ARVI2 showed a significant relationship between the polluted and non-polluted areas. Keywords: oil and gas pollution, Ground Truthing, Vegetation Indices, Landsat 8 OLI/TIRS, Remote Sensing and Vegetation Cover. DOI: 10.7176/JEES/9-7-05 Publication date:July 31st 201

Spatial-Temporal Mapping and Delineating of Agulu Lake Using Remote Sensing and Geographic Information Science for Sustainable Development

Water is a crucial component of ecosystems and a critical resource that cannot be replaced for social progress or human life. In this study, Agulu Lake, an inland water body located in Anambra, southeast Nigeria, was mapped, classified, and delineated with remotely sensed data so as to monitor the spatial-temporal changes that occurred in the lake’s surface water every 15 years, in 1985, 2000, and 2015, in order to achieve sustainable development by 2030. The Sustainable Development Goals (SDGs) of the United Nations emphasize the need to manage the marine environment. Some of the goals of the SDGs have some connection to open surface water, but goal 6a and indicator 6.6.1 are significant to this study. The study adopted Landsat 5 TM (1985), ETM+ (2000), Landsat 8 OLI (2015), ArcGIS 10.5 software, and the maximum likelihood classifier to create various classification maps. The Google Earth image (2015) was also used to show the general overview of Agulu Lake and its environs. The findings demonstrate that during the study period, the land surface class grew while the water surface class (Agulu Lake) shrank