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Clement Adjorlolo
Clement Adjorlolo
African Union Development Agency (AUDA-NEPAD); University of KwaZulu-Natal (UKZN)
Verified email at nepad.org - Homepage
Title
Cited by
Cited by
Year
Evaluating the robustness of models developed from field spectral data in predicting African grass foliar nitrogen concentration using WorldView-2 image as an independent test …
O Mutanga, E Adam, C Adjorlolo, EM Abdel-Rahman
International Journal of Applied Earth Observation and Geoinformation 34 …, 2015
802015
Spectral resampling based on user-defined inter-band correlation filter: C3 and C4 grass species classification
C Adjorlolo, O Mutanga, MA Cho, R Ismail
International Journal of Applied Earth Observation and Geoinformation 21 …, 2013
622013
Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape
M Kganyago, J Odindi, C Adjorlolo, P Mhangara
International journal of applied earth observation and geoinformation 67, 10-19, 2018
602018
Challenges and opportunities in the use of remote sensing for C3 and C4 grass species discrimination and mapping
C Adjorlolo, O Mutanga, MA Cho, R Ismail
African Journal of Range & Forage Science 29 (2), 47-61, 2012
542012
Predicting C3 and C4 grass nutrient variability using in situ canopy reflectance and partial least squares regression
C Adjorlolo, O Mutanga, MA Cho
International Journal of Remote Sensing 36 (6), 1743-1761, 2015
422015
Optimizing spectral resolutions for the classification of and grass species, using wavelengths of known absorption features
C Adjorlolo, MA Cho, O Mutanga, R Ismail
Journal of Applied Remote Sensing 6 (1), 063560-063560, 2012
422012
Estimation of canopy nitrogen concentration across C3 and C4 grasslands using WorldView-2 multispectral data
C Adjorlolo, O Mutanga, MA Cho
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014
402014
Estimating crop biophysical parameters using machine learning algorithms and Sentinel-2 imagery
M Kganyago, P Mhangara, C Adjorlolo
Remote Sensing 13 (21), 4314, 2021
292021
Evaluating the potential of the red edge channel for C3 (Festuca spp.) grass discrimination using Sentinel-2 and Rapid Eye satellite image data
C Otunga, J Odindi, O Mutanga, C Adjorlolo
Geocarto International 34 (10), 1123-1143, 2019
262019
Selecting a subset of spectral bands for mapping invasive alien plants: a case of discriminating Parthenium hysterophorus using field spectroscopy data
M Kganyago, J Odindi, C Adjorlolo, P Mhangara
International Journal of Remote Sensing 38 (20), 5608-5625, 2017
262017
Integrating remote sensing and geostatistics to estimate woody vegetation in an African savanna
C Adjorlolo, O Mutanga
Journal of Spatial Science 58 (2), 305-322, 2013
252013
Mapping the spatial distribution of Lippia javanica (Burm. f.) Spreng using Sentinel-2 and SRTM-derived topographic data in malaria endemic environment
OE Malahlela, C Adjorlolo, JM Olwoch
Ecological Modelling 392, 147-158, 2019
162019
Sugarcane: a way out of energy poverty
JGDB Leite, MRLV Leal, LAH Nogueira, LAB Cortez, BE Dale, ...
Biofuels, Bioproducts and Biorefining 10 (4), 393-408, 2016
152016
Assessing the spatial patterns of crop damage by wildlife using GIS
C Mutanga, Onisimo & Adjorlolo
Alternation 15 (1), 222-239, 2008
112008
Estimating woody vegetation cover in an African Savanna using remote sensing and geostatistics.
C Adjorlolo
92008
Exploring transferable techniques to retrieve crop biophysical and biochemical variables using sentinel-2 data
M Kganyago, C Adjorlolo, P Mhangara
Remote Sensing 14 (16), 3968, 2022
82022
Predicting the distribution of C3 (Festuca spp.) grass species using topographic variables and binary logistic regression model
C Otunga, J Odindi, O Mutanga, C Adjorlolo, J Botha
Geocarto International 33 (5), 489-504, 2018
82018
Estimating canopy nitrogen concentration across C3 and C4 grasslands using WorldView-2 multispectral data and the random forest algorithm
C Adjorlolo, O Mutanga, MA Cho
2013 Second International Conference on Agro-Geoinformatics (Agro …, 2013
82013
Optical remote sensing of crop biophysical and biochemical parameters: An overview of advances in sensor technologies and machine learning algorithms for precision agriculture
M Kganyago, C Adjorlolo, P Mhangara, L Tsoeleng
Computers and Electronics in Agriculture 218, 108730, 2024
72024
Evaluating efficacy of landsat-derived environmental covariates for predicting malaria distribution in rural villages of Vhembe District, South Africa
OE Malahlela, JM Olwoch, C Adjorlolo
EcoHealth 15, 23-40, 2018
72018
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