John Odindi

Orcid: 0000-0002-4934-1346

According to our database1, John Odindi authored at least 25 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
A visual and spatial tool for tracking, mapping and forecasting the dispersal of biological control agents.
Softw. Impacts, 2024

The influence of biophysical characteristics on elephant space use in an African savanna.
Ecol. Informatics, 2024

The utility of Planetscope spectral data in quantifying above-ground carbon stock in an urban reforested landscape.
Ecol. Informatics, 2024

Multi-pronged abundance prediction of bee pests' spatial proliferation in Kenya.
Int. J. Appl. Earth Obs. Geoinformation, 2024

2023
Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural-Urban Continuum of eThekwini Municipality, South Africa.
Remote. Sens., December, 2023

State-of-the-Art Deep Learning Methods for Objects Detection in Remote Sensing Satellite Images.
Sensors, July, 2023

Assessing the Prospects of Remote Sensing Maize Leaf Area Index Using UAV-Derived Multi-Spectral Data in Smallholder Farms across the Growing Season.
Remote. Sens., March, 2023

2022
"Cool" Roofs as a Heat-Mitigation Measure in Urban Heat Islands: A Comparative Analysis Using Sentinel 2 and Landsat Data.
Remote. Sens., 2022

Determining the Influence of Long Term Urban Growth on Surface Urban Heat Islands Using Local Climate Zones and Intensity Analysis Techniques.
Remote. Sens., 2022

Determining the Capability of the Tree-Based Pipeline Optimization Tool (TPOT) in Mapping Parthenium Weed Using Multi-Date Sentinel-2 Image Data.
Remote. Sens., 2022

Determining the onset of autumn grass senescence in subtropical sour-veld grasslands using remote sensing proxies and the breakpoint approach.
Ecol. Informatics, 2022

2021
A Comparative Estimation of Maize Leaf Water Content Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV)-Based Proximal and Remotely Sensed Data.
Remote. Sens., 2021

The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape.
Remote. Sens., 2021

Estimating and Monitoring Land Surface Phenology in Rangelands: A Review of Progress and Challenges.
Remote. Sens., 2021

Basic and deep learning models in remote sensing of soil organic carbon estimation: A brief review.
Int. J. Appl. Earth Obs. Geoinformation, 2021

2020
A Hybrid Feature Method for Handling Redundant Features in a Sentinel-2 Multidate Image for Mapping Parthenium Weed.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

A Comparison of Two Morphological Techniques in the Classification of Urban Land Cover.
Remote. Sens., 2020

A quantitative framework for analysing long term spatial clustering and vegetation fragmentation in an urban landscape using multi-temporal landsat data.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Feature Selection on Sentinel-2 Multispectral Imagery for Mapping a Landscape Infested by Parthenium Weed.
Remote. Sens., 2019

2018
Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape.
Int. J. Appl. Earth Obs. Geoinformation, 2018

Predicting Urban Growth and Implication on Urban Thermal Characteristics in Harare, Zimbabwe.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Modelling Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations Using Sentinel 2 Msi Data.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Empirical Modeling of Leaf Chlorophyll Content in Coffee (Coffea Arabica) Plantations With Sentinel-2 MSI Data: Effects of Spectral Settings, Spatial Resolution, and Crop Canopy Cover.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models.
ISPRS Int. J. Geo Inf., 2017

Estimating Swiss chard foliar macro- and micronutrient concentrations under different irrigation water sources using ground-based hyperspectral data and four partial least squares (PLS)-based (PLS1, PLS2, SPLS1 and SPLS2) regression algorithms.
Comput. Electron. Agric., 2017


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