ALEX ONOJEGHUO

Publications

• Wetland mapping with multi-temporal sentinel-1 & -2 imagery (2017 – 2020) and LiDAR data in the grassland natural region of alberta
• Protected Area Monitoring in the Niger Delta Using Multi-Temporal Remote Sensing
• Mapping forest transition trends in Okomu reserve using Landsat and UK-DMC-2 satellite data
• Dynamics of Forest Landscape Transition across Protected Areas in the Niger Delta from 1986 to 2014
• Habitat Suitability Modeling of Endangered Primates in Nigeria: Integrating Satellite Remote Sensing and Spatial Modeling Techniques
• Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data
• Exploiting High Resolution Multi-Seasonal Textural Measures and Spectral Information for Reedbed Mapping
• Characterising Reedbed habitat quality using Leaf-off LiDAR Data
• Mapping reedbed habitats using texture-based classification of QuickBird imagery
• Optimising the use of hyperspectral and LiDAR data for mapping reedbed habitats
• Understanding the multi-seasonal spectral and biophysical characteristics of reedbed habitats in the UK
• Spatial Data Infrastructure in the Management of the Lagos Lagoon
• Upstream flows drive the productivity of floodplain ecosystems in tropical Queensland
• What if the rains do not come?
• Forest transition in an ecologically important region: Patterns and causes for landscape dynamics in the Niger Delta
• Characterising Reedbeds Using LiDAR Data: Potential and Limitations
• Delonix regia and Casuarina equisetifolia as passive biomonitors and as bioaccumulators of atmospheric trace metals
• Influence of global climate on freshwater changes in Africa's largest endorheic basin using multi-scaled indicators
• Fusion of Landsat 8 OLI and Sentinel-2 MSI Data
• Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series
• Mapping paddy rice fields by applying machine learning algorithms to multi-temporal Sentinel-1A and Landsat data
• Enhancing Spatio-Temporal Fusion of MODIS and Landsat Data by Incorporating 250 m MODIS Data
• Deep ResU-Net Convolutional Neural Networks Segmentation for Smallholder Paddy Rice Mapping Using Sentinel 1 SAR and Sentinel 2 Optical Imagery