Physics-based simulation of CHIME and LSTM data to support advanced agricultural monitoring

The upcoming Copernicus Expansion Missions CHIME and LSTM will offer new opportunities for agricultural monitoring, but algorithm development must begin before any data exist. Within the AgriCEM project, we address this gap by generating simulated CHIME and LSTM of sugar beet for monitoring applications development. A physically based end-to-end workflow couples the SCOPE model, which simulates VSWIR reflectance and emitted thermal radiance together with photosynthesis and energy fluxes, to the sensor and ground segment simulator RISE. Three seasonal datasets were produced: a scenario-based dataset representing healthy, drought-stressed and Cercospora-infected sugar beet, and two datasets parameterised from field campaigns in Poland and Italy. The products comprise CHIME-like L2A reflectance and LSTM-like L1C thermal radiance over a 4 km² agricultural area. First applications, including physically based retrieval of canopy water content, show that the simulated time series reproduce the expected spectral and thermal responses to abiotic and biotic stress. The datasets will be made available through the ESA Project Results Repository.

Authors

Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2026-10-08
DOI
https://doi.org/10.5194/isprs-archives-xlviii-m-12-2026-91-2026
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Physics-based simulation of CHIME and LSTM data to support advanced agricultural monitoring

Egor Prikaziuk, Matthias Wocher, Anne Schucknecht, Tian Hu et al.
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Remote Sensing in Agriculture
article

Physics-based simulation of CHIME and LSTM data to support advanced agricultural monitoring

Egor Prikaziuk, Matthias Wocher, Anne Schucknecht, Tian Hu, Żaneta Swacha, Marco Spagnolli, Zbigniew Kawalec
article en

Abstract

The upcoming Copernicus Expansion Missions CHIME and LSTM will offer new opportunities for agricultural monitoring, but algorithm development must begin before any data exist. Within the AgriCEM project, we address this gap by generating simulated CHIME and LSTM of sugar beet for monitoring applications development. A physically based end-to-end workflow couples the SCOPE model, which simulates VSWIR reflectance and emitted thermal radiance together with photosynthesis and energy fluxes, to the sensor and ground segment simulator RISE. Three seasonal datasets were produced: a scenario-based dataset representing healthy, drought-stressed and Cercospora-infected sugar beet, and two datasets parameterised from field campaigns in Poland and Italy. The products comprise CHIME-like L2A reflectance and LSTM-like L1C thermal radiance over a 4 km² agricultural area. First applications, including physically based retrieval of canopy water content, show that the simulated time series reproduce the expected spectral and thermal responses to abiotic and biotic stress. The datasets will be made available through the ESA Project Results Repository.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-M-12-2026(0)
Openalex Percentile: Top 15%
Remote Sensing in Agriculture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Physics-based simulation of CHIME and LSTM data to support advanced agricultural monitoring — Egor Prikaziuk, Matthias Wocher, et al. · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (2026) | TGRS Research Map | TGRS