K. Ali

发表

Application of Landsat 8 OLI for monitoring the coastal waters of the US Virgin Islands

K. Kerrigan, K. Ali, Adem Ali, 2020, International Journal of Remote Sensing.

Application of a partial least-squares regression model to retrieve chlorophyll-a concentrations in coastal waters using hyper-spectral data

K. Ali, K. Ryan, 2016, Ocean Science Journal.

Application of Aqua MODIS sensor data for estimating chlorophyll a in the turbid Case 2 waters of Lake Erie using bio-optical models

K. Ali, J. Ortiz, Nick Bonini, 2016 .

Multivariate approach to estimate colour producing agents in Case 2 waters using first-derivative spectrophotometer data

K. Ali, J. Ortiz, D. Witter, 2014 .

Multivariate approach for chlorophyll-a and suspended matter retrievals in Case II type waters using hyperspectral data

K. Ali, J. Ortiz, 2013 .

Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie

K. Ali, J. Ortiz, D. Witter, 2014, Environmental Earth Sciences.

Machine Learning Classification of Fused Sentinel-1 and Sentinel-2 Image Data towards Mapping Fruit Plantations in Highly Heterogenous Landscapes

E. Adam, K. Ali, Yingisani Chabalala, 2022, Remote. Sens..

Application of a PLS-Augmented ANN Model for Retrieving Chlorophyll-a from Hyperspectral Data in Case 2 Waters of the Western Basin of Lake Erie

W. Moses, K. Ali, 2022, Remote. Sens..

Field Spectroscopy as a Tool for Enhancing Water Quality Monitoring in the ACE Basin, SC

Caitlyn C. Mayer, Khalid A. Ali, K. Ali, 2017 .

Potential role of acid mine drainage management towards achieving sustainable development in the Johannesburg region, South Africa

K. Ali, T. Abiye, 2022, Groundwater for Sustainable Development.

Evaluating multiple colour-producing agents in Case II waters from Lake Erie

Joseph D. Ortiz, Khalid Adem Ali, Michael Duff, 2013 .

Semi-analytical inversion modelling of Chlorophyll a variability in the U.S. Virgin Islands

D. Flanagan, T. Smith, K. Ali, 2023, Frontiers in Remote Sensing.

Exploring the Effect of Balanced and Imbalanced Multi-Class Distribution Data and Sampling Techniques on Fruit-Tree Crop Classification Using Different Machine Learning Classifiers

E. Adam, K. Ali, Yingisani Chabalala, 2023, Geomatics.

Exploring the Potential of Feature Selection Methods in the Classification of Urban Trees Using Field Spectroscopy Data

Marcus J. Byrne, Elhadi Adam, Simbarashe Jombo, 2020 .