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AfPCA Proceedings 2024

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Ndlovu, S
Balaghi, R
Hegano, A
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Authors
Mahyou, H
Balaghi, R
Hegano, A
Ndlovu, S
Topics
Decision Support Systems
Proximal and Remote Sensing
Type
Oral
Year
2020
2022
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Filter results3 paper(s) found.

1. Crop monitoring and forecasting system based on cloud data and capabilities

Various systems for crop monitoring & forecasting, using satellite images and meteorological data, exist around the world. Their complexity differs from one system to another, according to the temporal and spatial scale and according to the objectives assigned to them. Among the well known are the European Monitoring Agricultural ResourceS system, the USDA system of the Foreign Agricultural Service, the Moroccan CGMS system, the Belgian CGMS system and the Chinese CropWatch system.  The...

2. Spatial soil loss risk assessment for proper intervention: a case of Neri watershed in Omo Gibe basin, Southwestern Ethiopia

Soil erosion is one of the biggest global environmental problems resulting in both on-site and offsite effects. It contributes negatively to agricultural production, quality of source water for drinking, ecosystem health in land and aquatic environments, and aesthetic value of landscapes. This study was conducted in Neri watershed, part of Omo Gibe basin with area of 465.46 km2. RUSLE model supported by a GIS framework is used to assess the average annual soil loss, and create a soil erosion hazard... A. Hegano

3. A Comparative Estimation of Maize Leaf Moisture Content on Smallholder Farming Systems Using Unmanned Aerial Vehicle (UAV) Based Proximal Remote Sensing

Understanding maize moisture conditions is necessary for crop monitoring and developing early warning systems to optimise agricultural production in smallholder farms. Therefore, this study evaluated the utility of UAV derived multispectral imagery and machine learning techniques in estimating maize leaf moisture indicators; equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables were... S. Ndlovu