Seasonal collection of in situ optical and thermal images dataset and meteorological measurements over an Indian semi-arid rice crop

This article describes a multi-sensor dataset collected during the TIRAMISU (Thermal InfraRed Anisotropy Measurements in India and Southern eUrope) campaign at the Nawagam research site in Gujarat, India, during the 2023 monsoon season. The objective was to acquire continuous ground-based optical and thermal measurements over a homogeneous rice canopy across different crop growth stages. The dataset integrates several complementary components. Thermal data were acquired with an Optris longwave infrared camera (8-14 µm) at high temporal resolution, capturing canopy temperature dynamics throughout the diurnal cycle. Optical data were obtained with a Micasense RedEdge-M multispectral sensor, providing imagery in Blue, Green, Red, RedEdge, and Near-Infrared bands with radiometric corrections. An Apogee radiometer supplied reference radiometric temperature. Meteorological measurements included air temperature, humidity, wind speed and direction, and net radiation. Ancillary field measurements comprised Leaf Area Index (LAI), plant height, emissivity sampling, hyperspectral observations, and crop stage information. The datasets are provided with metadata and processing workflows, including calibration procedures for optical reflectance and thermal radiance. Together, these components form a comprehensive record of canopy-atmosphere interactions over a homogeneous rice field. The datasets can support research on optical and thermal directional anisotropy, canopy radiative transfer, emissivity characterization, and crop biophysical parameter estimation. In addition, they are relevant for applications in vegetation monitoring, agricultural water stress assessment, and surface energy balance studies. By combining optical, thermal, and meteorological observations, the resource is suited for multidisciplinary investigations in remote sensing, agronomy, and environmental sciences.

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Publication Details

Journal
Data in Brief
Published
2026-03-03
DOI
https://doi.org/10.1016/j.dib.2026.112646
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
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article

Seasonal collection of in situ optical and thermal images dataset and meteorological measurements over an Indian semi-arid rice crop

Ayan Das, Chandrika Pinnepalli, Rucha Dave, Mark Irvine et al.
Data in Brief
Remote Sensing in Agriculture
article

Seasonal collection of in situ optical and thermal images dataset and meteorological measurements over an Indian semi-arid rice crop

Ayan Das, Chandrika Pinnepalli, Rucha Dave, Mark Irvine, Marc Oliver-Soulayrol, Bimal K. Bhattacharya, Rahul Nigam, Jean-Louis Roujean
article en

Abstract

This article describes a multi-sensor dataset collected during the TIRAMISU (Thermal InfraRed Anisotropy Measurements in India and Southern eUrope) campaign at the Nawagam research site in Gujarat, India, during the 2023 monsoon season. The objective was to acquire continuous ground-based optical and thermal measurements over a homogeneous rice canopy across different crop growth stages. The dataset integrates several complementary components. Thermal data were acquired with an Optris longwave infrared camera (8-14 µm) at high temporal resolution, capturing canopy temperature dynamics throughout the diurnal cycle. Optical data were obtained with a Micasense RedEdge-M multispectral sensor, providing imagery in Blue, Green, Red, RedEdge, and Near-Infrared bands with radiometric corrections. An Apogee radiometer supplied reference radiometric temperature. Meteorological measurements included air temperature, humidity, wind speed and direction, and net radiation. Ancillary field measurements comprised Leaf Area Index (LAI), plant height, emissivity sampling, hyperspectral observations, and crop stage information. The datasets are provided with metadata and processing workflows, including calibration procedures for optical reflectance and thermal radiance. Together, these components form a comprehensive record of canopy-atmosphere interactions over a homogeneous rice field. The datasets can support research on optical and thermal directional anisotropy, canopy radiative transfer, emissivity characterization, and crop biophysical parameter estimation. In addition, they are relevant for applications in vegetation monitoring, agricultural water stress assessment, and surface energy balance studies. By combining optical, thermal, and meteorological observations, the resource is suited for multidisciplinary investigations in remote sensing, agronomy, and environmental sciences.

Data in BriefVol. 66
Indian Space Research Organisation (IN), Centre National de la Recherche Scientifique (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Université de Montpellier (FR), Anand Agricultural University (IN), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Biologie du Fruit et Pathologie (FR), Institut de Recherche pour le Développement (FR)
Zero hunger, Climate action
Openalex Percentile: Top 46%
Remote Sensing in Agriculture
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