Project
Monitoring corn and soybean leaf area index and aboveground biomass from multisensor dataKeywords
corn, soybeans, leaf area index, Biomass, Canopy chlorophyll content, Parametric regression models, Machine learning regression models, Optical remote sensing images, Synthetic Aperture Radar images, Thermal imagesPublications
1- Mathematical Study of Monthly and Annual Rainfall Trends in Nasarawa State, NigeriaChibuike, EKWE, Michael, JOSHUA, Jonah Kunda, IGWE, Johnson Eze, OSINOWO, Adekunle Ayodotun
2014 IOSR Journal of Mathematics
2- Assessment of green parks cooling effect on Abuja urban microclimate using geospatial techniques
Chibuike, Ekwe Michael, Adedeji Oluwatola Ibukun, Ahmad Abbas, Joshua Jonah Kunda
2018 Remote Sensing Applications: Society and Environment
3- The effect of green spaces on the urban thermal environment during a hot-dry season: a case study of Port Harcourt, Nigeria
Ekwe, Michael C., Fatimah Adamu, Joseph Gana, Grace Chika Nwafor, Rabi Usman, Jemimah Nom, Ogonnaya D. Onu, Oluwatola Ibukun Adedeji, Shaba A. Halilu, Olaide M. Aderoju
2020 Environment, Development and Sustainability
4- Estimating rainfed groundnut’s leaf area index using Sentinel-2 based on Machine Learning Regression Algorithms and Empirical Models
Ekwe, Michael Chibuike, Oluseun Adeluyi, Jochem Verrelst, Angela Kross, Caleb Akoji Odiji
2024 Precision Agriculture
