Large-scale digital mapping of topsoil total nitrogen using machine learning models and associated uncertainty map

F Parsaie, A Farrokhian Firouzi, SR Mousavi… - Environmental …, 2021 - Springer
Understanding the spatial distribution of soil nutrients and factors affecting their
concentration and availability is crucial for soil fertility management and sustainable land …

Delineating smallholder maize farms from Sentinel-1 coupled with Sentinel-2 data using machine learning

Z Mashaba-Munghemezulu, GJ Chirima… - Sustainability, 2021 - mdpi.com
Rural communities rely on smallholder maize farms for subsistence agriculture, the main
driver of local economic activity and food security. However, their planted area estimates are …

Smallholder maize area and yield mapping at national scales with Google Earth Engine

Z Jin, G Azzari, C You, S Di Tommaso, S Aston… - Remote sensing of …, 2019 - Elsevier
Accurate measurements of maize yields at field or subfield scales are useful for guiding
agronomic practices and investments and policies for improving food security. Data on …

Spatial management strategies for nitrogen in maize production based on soil and crop data

E Cordero, L Longchamps, R Khosla… - Science of the total …, 2019 - Elsevier
Nitrogen (N) fertilisation determines maize grain yield (MGY). Precision agriculture (PA)
allows matching crop N requirements in both space and time. Two approaches have been …

Nitrogen estimation for wheat using UAV-based and satellite multispectral imagery, topographic metrics, leaf area index, plant height, soil moisture, and machine …

J Yu, J Wang, B Leblon, Y Song - Nitrogen, 2021 - mdpi.com
To improve productivity, reduce production costs, and minimize the environmental impacts of
agriculture, the advancement of nitrogen (N) fertilizer management methods is needed. The …

Influence of soil properties on maize and wheat nitrogen status assessment from Sentinel-2 data

A Crema, M Boschetti, F Nutini, D Cillis, R Casa - Remote Sensing, 2020 - mdpi.com
Soil properties variability is a factor that greatly influences cereals crops production and
interacts with a proper assessment of crop nutritional status, which is fundamental to support …

Comparison of Machine Learning Methods for Predicting Soil Total Nitrogen Content Using Landsat-8, Sentinel-1, and Sentinel-2 Images

Q Zhang, M Liu, Y Zhang, D Mao, F Li, F Wu, J Song… - Remote Sensing, 2023 - mdpi.com
Soil total nitrogen (STN) is a crucial component of the ecosystem's nitrogen pool, and
accurate prediction of STN content is essential for understanding global nitrogen cycling …

A Machine Learning Framework for Mapping Soil Nutrients with Multi-Source Data Fusion

K Das, N Twarakavi, N Khiripet… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
One of the major considerations in precision agriculture is optimizing fertilization to ensure
maximum crop productivity. The principle behind this precision fertilization is to adjust the …

Land parcel-based digital soil mapping of soil nutrient properties in an alluvial-diluvia plain agricultural area in China

W Dong, T Wu, J Luo, Y Sun, L Xia - Geoderma, 2019 - Elsevier
The ability to accurately and precisely perform soil nutrient mapping over large areas is
essential in the decision-making processes for precision agriculture. However, existing grid …

Exploiting the capabilities of Sentinel-2 and RapidEye for predicting grass nitrogen across different grass communities in a protected area

Y Chabalala, E Adam, Z Oumar, A Ramoelo - Applied Geomatics, 2020 - Springer
The primary indicator of forage quality in any rangeland environment is grass nitrogen.
Remote sensing has been used to map grass quality by predicting nitrogen in order to …