Transfer learning in environmental remote sensing
Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
Can yield prediction be fully digitilized? A systematic review
Going beyond previous work, this paper presents a systematic literature review that explores
the deployment of satellites, drones, and ground-based sensors for yield prediction in …
the deployment of satellites, drones, and ground-based sensors for yield prediction in …
Crop type classification by DESIS hyperspectral imagery and machine learning algorithms
N Farmonov, K Amankulova, J Szatmári… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Developments in space-based hyperspectral sensors, advanced remote sensing, and
machine learning can help crop yield measurement, modelling, prediction, and crop …
machine learning can help crop yield measurement, modelling, prediction, and crop …
Wheat yield estimation using remote sensing data based on machine learning approaches
Accurate predictions of wheat yields are essential to farmers' production plans and to the
international trade in wheat. However, only poor approximations of the productivity of wheat …
international trade in wheat. However, only poor approximations of the productivity of wheat …
Globally quantitative analysis of the impact of atmosphere and spectral response function on 2-band enhanced vegetation index (EVI2) over Sentinel-2 and Landsat-8
The 2-band enhanced vegetation index (EVI2) was developed as an alternative to the
enhanced vegetation index (EVI) for sensors that lack a blue band or for observing bright …
enhanced vegetation index (EVI) for sensors that lack a blue band or for observing bright …
Out-of-year corn yield prediction at field-scale using Sentinel-2 satellite imagery and machine learning methods
Crop yield prediction for an ongoing season is crucial for food security interventions and
commodity markets for decisions such as inventory management, understanding yield …
commodity markets for decisions such as inventory management, understanding yield …
[HTML][HTML] Assessment of PRISMA water reflectance using autonomous hyperspectral radiometry
F Braga, A Fabbretto, Q Vanhellemont… - ISPRS Journal of …, 2022 - Elsevier
Hyperspectral remote sensing reflectance (Rrs) derived from PRISMA in the visible and
infrared range was evaluated for two inland and coastal water sites using above-water in …
infrared range was evaluated for two inland and coastal water sites using above-water in …
Improved prediction of rice yield at field and county levels by synergistic use of SAR, optical and meteorological data
Timely and accurate rice yield prediction over large regions is imperative to making informed
decisions on precision crop management and ensuring regional food security. Previous …
decisions on precision crop management and ensuring regional food security. Previous …
Prototyping crop traits retrieval models for CHIME: Dimensionality reduction strategies applied to PRISMA data
In preparation for new-generation imaging spectrometer missions and the accompanying
unprecedented inflow of hyperspectral data, optimized models are needed to generate …
unprecedented inflow of hyperspectral data, optimized models are needed to generate …
Improving the Transferability of Deep Learning Models for Crop Yield Prediction: A Partial Domain Adaptation Approach
Over the past few years, there has been extensive exploration of machine learning (ML),
especially deep learning (DL), for crop yield prediction, resulting in impressive levels of …
especially deep learning (DL), for crop yield prediction, resulting in impressive levels of …