[HTML][HTML] Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review
Remote detection and monitoring of the vegetation responses to stress became relevant for
sustainable agriculture. Ongoing developments in optical remote sensing technologies have …
sustainable agriculture. Ongoing developments in optical remote sensing technologies have …
Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
A survey on active learning: State-of-the-art, practical challenges and research directions
Despite the availability and ease of collecting a large amount of free, unlabeled data, the
expensive and time-consuming labeling process is still an obstacle to labeling a sufficient …
expensive and time-consuming labeling process is still an obstacle to labeling a sufficient …
Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery
The recently launched and upcoming hyperspectral satellite missions, featuring contiguous
visible-to-shortwave infrared spectral information, are opening unprecedented opportunities …
visible-to-shortwave infrared spectral information, are opening unprecedented opportunities …
[HTML][HTML] Map** landscape canopy nitrogen content from space using PRISMA data
Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently
launched and upcoming science-driven missions, eg PRecursore IperSpettrale della …
launched and upcoming science-driven missions, eg PRecursore IperSpettrale della …
[HTML][HTML] Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data
J Estévez, M Salinero-Delgado, K Berger… - Remote sensing of …, 2022 - Elsevier
The unprecedented availability of optical satellite data in cloud-based computing platforms,
such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval …
such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval …
Inversion of maize leaf area index from UAV hyperspectral and multispectral imagery
The accurate estimation of Leaf area index (LAI) is of great importance for evaluating crop
growth in precision agriculture. Although previous studies have confirmed great advantages …
growth in precision agriculture. Although previous studies have confirmed great advantages …
[HTML][HTML] Monitoring cropland phenology on Google Earth Engine using gaussian process regression
Monitoring cropland phenology from optical satellite data remains a challenging task due to
the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to …
the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to …
Improved chlorophyll and water content estimations at leaf level with a hybrid radiative transfer and machine learning model
Accurate and robust quantifications of leaf chlorophyll and water contents facilitate a better
understanding of plant water and nutrient needs. Besides simplified spectral indices, other …
understanding of plant water and nutrient needs. Besides simplified spectral indices, other …
Prior knowledge and active learning enable hybrid method for estimating leaf chlorophyll content from multi-scale canopy reflectance
Real-time and accurate assessment of leaf chlorophyll content (C ab) will be significant for
monitoring plant physiological status. Development of hybrid methods advances the …
monitoring plant physiological status. Development of hybrid methods advances the …