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

TL;DR

This paper presents a dataset from a field campaign in India that collected optical, thermal, and meteorological data over a rice crop during the monsoon season to study crop interactions with the atmosphere.

Contribution

The paper introduces a comprehensive, multi-sensor dataset with synchronized optical, thermal, and meteorological measurements for rice crops in a semi-arid region.

Findings

The dataset captures canopy temperature dynamics and optical reflectance across different crop growth stages.

It includes ancillary field data like LAI, plant height, and emissivity for detailed analysis.

The resource supports studies on directional anisotropy, radiative transfer, and agricultural water stress.

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.

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