Naheem AdebisiBoise State University | BSU · Department of Geosciences
Naheem Adebisi
About
8
Publications
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Publications
Publications (8)
The goal of this study is to understand the pattern of snow distribution over mountain ranges and the capability of L-band Synthetic Aperture Radar (SAR) data to retrieve snow depth. Ground-based snow records and Airborne Lidar and SAR data collected as part of NASA's snow expedition over Mores Creek Summit in 2021 were employed for this study. The...
In sub-Saharan Africa, mass rural-urban migration negatively affectthe agriculture sector that accounts for about 23% of the GDP and employs over 60% of the population. Together with a rapidly changing climate, unplanned urbanization poses serious threats to Africa’s agriculture sector with the risk of chronic food shortages in the future. To stem...
Air pollution is a global geo-hazard with significant implications, including deterioration of health and premature death. Climatic variables such as temperature, rainfall, wind, and humidity impact air pollution by affecting the strength, transportation, and dispersion of pollutants in the atmosphere. Emerging data science tools, particularly Mach...
Spatial modelling and analysis can assist in improving the decision-making process of mitigating bad air quality. One of Malaysia's most harmful air pollutants is particulate matter (PM), which has been used to denote the Air Pollutant Index (API) for over 20 years. The spatial prediction of particulate matter less than 10 μm (PM10) hotspots is cru...
Rising sea level is generally assumed and widely reported to be the significant driver of
coastal erosion of most low-lying sandy beaches globally. However, there is limited data-driven evidence of this relationship due to the challenges in quantifying shoreline dynamics at the same temporal scale as sea-level records. Using a Google Earth Engine (...
In this study, we conducted a holistic evaluation of current and future trend in coastal sea level at the 21 stations along Malaysia’s coastline. For sea level prediction, univariate and 3 scenarios of multivariate Long Short Term Memory (LSTM) neural networks were trained with absolute sea level data and ocean-atmospheric variables. The result fro...
Significant developments have been made in the observation systems and techniques of estimating sea level towards meeting the standard accuracy requirement of Global Climate Observation Systems (GCOS). This study undertakes a systematic review of the current advances in estimating sea level change in the context of the 4th industrial revolution. Tr...
This study aims to integrate a broad spectrum of ocean-atmospheric variables to predict sea level variation along West Peninsular Malaysia coastline using machine learning and deep learning techniques. 4 scenarios of different combinations of variables such as sea surface temperature, sea surface salinity, sea surface density, surface atmospheric p...
Questions
Question (1)
I am doing shoreline mapping and change analysis. I have the shorelines mapped already and I have calculated the required statistics such as Net shoreline movement, end point rate etc using DSAS. However, to account for the different stages of tides at the times of image acquisition, it is recommended to apply a linear tidal correction using measured water levels and characteristics beach slope. How do I do this correction. Your kind suggestions are highly appreciated.
Thanks.
Regards.
