ArticleNational science review2019
A perspective on Gaussian processes for Earth observation.
Article in National science review, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Probabilistic machine learning for noisy labels in Earth observation.Scientific reports · 2025Article
- Bio-Master: Design and Validation of a High-Throughput Biochemical Profiling Platform for Crop Canopies.Plant phenomics (Washington, D.C.) · 2023Article
- Retrieval of carbon content and biomass from hyperspectral imagery over cultivated areas.ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) · 2022Article
- Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data.Remote sensing · 2022Article
- Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery.Remote sensing · 2021Article
- Mapping landscape canopy nitrogen content from space using PRISMA data.ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) · 2021Article
- Predicting regional coastal sea level changes with machine learning.Scientific reports · 2021Article
- Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine.Remote sensing · 2021Article
- Retrieval of aboveground crop nitrogen content with a hybrid machine learning method.International journal of applied earth observation and geoinformation : ITC journal · 2020Article
- Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks.Global change biology · 2020Article
- Gaussian processes retrieval of LAI from Sentinel-2 top-of-atmosphere radiance data.ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) · 2020Article
- Deep Gaussian processes for biogeophysical parameter retrieval and model inversion.ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) · 2020Article
- Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions.Remote sensing of environment · 2020Article
- Optimizing Gaussian Process Regression for Image Time Series Gap-Filling and Crop Monitoring.Agronomy (Basel, Switzerland) · 2020Article
- Kernel methods and their derivatives: Concept and perspectives for the earth system sciences.PloS one · 2020Article
- Fusing optical and SAR time series for LAI gap fillingwith multioutput Gaussian processes.Remote sensing of environment · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.