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Proximal and Remote Sensing

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Authors

AYERDI-GOTOR, A

Anberbir, T

Anin-Adjei, E

Badu-Marfo, G

Dabi, A

Dumont, B

EL-MEJJAOUY, Y

Hanyabui, E

Hobart, M

LEBRINI, Y

Majozi, N

Mamo, G

Mercatoris, B

Nardjes, H

Ndlovu, S

Oukarroum, A

Persson, K

Schiller, N

Schirrmann, M

Söderström, M

Vermeulen, P

Yagoubi, M

Topics

Proximal and Remote Sensing

Type

Oral

Poster

Year

2022

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Filter results8 paper(s) found.
1. An Open Source Multispectral Camera for Crop Monitoring Precision agriculture is one of the most important economic issues of the 21st century because it will make it possible to respond to the new challenges of agriculture, which are population growth, global warming, global epidemics, and inflation, to name a few. Remote sensing makes it possible to monitor the plantation from a distance and makes it possible to know the level of growth and the state of health and hydration of the plants. This paper outlines an affordable and open-source multisp... H. Nardjes, M. Yagoubi Download paper
2. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat Leaves The assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium conte... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris Download paper
3. From Drone to Satellite – Does It Work? Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sens... M. Söderström, K. Persson Download paper
4. Performance of Remote Sensing Data and Machine Learning for Wheat Disease Detection The use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main re... Y. Lebrini, A. Ayerdi-gotor Download paper
5. Unmanned Aerial Vehicles (UAVs) for Phenotypic Traits Estimation & Yellow Rust Disease Severity Assessment in Small-scale Wheat Breeding Trials in Ethiopia Remote Sensing (RS) platforms; like the Unmanned Aerial Vehicles (UAVs) are recently gaining traction in agricultural data collection systems and used for various phenotyping of breeding field trials and capturing different biophysical, biochemical and sanitary traits which can be used to predict and explain the resulting yield and selecting better verities. Compared to the conventional phenotyping usually done by visual scoring and manual measurements which is time consuming/back breakings, ... T. Anberbir, G. Mamo , A. Dabi
6. Photogrammetrically Assessed Smallholder Pineapple Fields in Ghana Using Small Unmanned Aircraft Systems Ultra-high-resolution imagery taken by small unmanned aircraft systems (sUAS, drones) has been proven beneficial for the monitoring of agricultural crops in conventional farming especially in the context of precision farming. For smallholder pineapple cultivation, the use of sUAS imagery is still sparsely evaluated. However, technical developments in low cost sUAS-sensor combinations make assessments of agricultural areas by service providers more and more affordable for Africa. In this study... M. Hobart, E. Anin-adjei, E. Hanyabui, G. Badu-marfo, M. Schirrmann, N. Schiller Download paper
7. Application of Remote Sensing Technologies for Monitoring within Field Soil and Crop Growth Variability ... N. Majozi
8. 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 ... S. Ndlovu Download paper

Filter results8 paper(s) found.

1. An Open Source Multispectral Camera for Crop Monitoring

Precision agriculture is one of the most important economic issues of the 21st century because it will make it possible to respond to the new challenges of agriculture, which are population growth, global warming, global epidemics, and inflation, to name a few. Remote sensing makes it possible to monitor the plantation from a distance and makes it possible to know the level of growth and the state of health and hydration of the plants. This paper outlines an affordable and open-source multisp... H. Nardjes, M. Yagoubi

Download paper

2. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat Leaves

The assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium conte... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris

Download paper

3. From Drone to Satellite – Does It Work?

Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sens... M. Söderström, K. Persson

Download paper

4. Performance of Remote Sensing Data and Machine Learning for Wheat Disease Detection

The use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main re... Y. Lebrini, A. Ayerdi-gotor

Download paper

5. Unmanned Aerial Vehicles (UAVs) for Phenotypic Traits Estimation & Yellow Rust Disease Severity Assessment in Small-scale Wheat Breeding Trials in Ethiopia

Remote Sensing (RS) platforms; like the Unmanned Aerial Vehicles (UAVs) are recently gaining traction in agricultural data collection systems and used for various phenotyping of breeding field trials and capturing different biophysical, biochemical and sanitary traits which can be used to predict and explain the resulting yield and selecting better verities. Compared to the conventional phenotyping usually done by visual scoring and manual measurements which is time consuming/back breakings, ... T. Anberbir, G. Mamo , A. Dabi

6. Photogrammetrically Assessed Smallholder Pineapple Fields in Ghana Using Small Unmanned Aircraft Systems

Ultra-high-resolution imagery taken by small unmanned aircraft systems (sUAS, drones) has been proven beneficial for the monitoring of agricultural crops in conventional farming especially in the context of precision farming. For smallholder pineapple cultivation, the use of sUAS imagery is still sparsely evaluated. However, technical developments in low cost sUAS-sensor combinations make assessments of agricultural areas by service providers more and more affordable for Africa. In this study... M. Hobart, E. Anin-adjei, E. Hanyabui, G. Badu-marfo, M. Schirrmann, N. Schiller

Download paper

7. Application of Remote Sensing Technologies for Monitoring within Field Soil and Crop Growth Variability

... N. Majozi

8. 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 ... S. Ndlovu

Download paper