Evaluating various energy balance aggregation schemes in cotton using Unoccupied Aerial Systems (UAS)-based latent heat flux estimates

Authors: NEELY, HALY - Washington State University; MORGAN, CRISTINE - Soil Health Institute; MAHONTY, BINAYAK - Texas A&M University; Yang, Chenghai

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/20/2025
Publication Date: 10/29/2025
Citation: Neely, H., Morgan, C., Mahonty, B., Yang, C. 2025. Evaluating various energy balance aggregation schemes in cotton using Unoccupied Aerial Systems (UAS)-based latent heat flux estimates. Remote Sensing. 17. https://doi.org/10.3390/rs17213579.
DOI: https://doi.org/10.3390/rs17213579

Interpretive Summary: Unoccupied aerial systems (UASs) are being proposed as a means to monitor crop water use or evapotranspiration (ET) and crop stress augmenting satellite-based methods and thus have the potential to improve irrigation efficiencies within production fields. This information is critical, particularly for irrigated agriculture which exists in many water-limited drought-prone regions and consumes 70 to 80% of freshwater resources. UAS imagery can be collected when satellite imagery is unavailable and at important crop phenological stages. UAS imagery offers additional advantages in terms of spatial detail, with imagery distinguishing crop plants from surrounding soil. This study evaluated the impact of spatially aggregating distributed ET from UAS imagery using the Two-Source Energy Balance (TSEB) model to coarser pixel resolutions collected by occupied aircraft and satellite remote sensing platforms for irrigated cotton in Texas. UAS ET estimates using TSEB, despite its data complexity, were found to be a reliable source of high spatial resolution ET and has the potential for evaluating coarser resolution ET products from occupied aircraft and satellite systems. UAS can also potentially provide ET maps over targeted fields at critical stages in crop development when satellite data may be unavailable. With the rapid development of UAS sensor technology and becoming more economical flying over longer distances, there is real potential for operational applications of UASs for ET monitoring that can improve the frequency and reliability of satellite-based ET products.

Technical Abstract: Daily evapotranspiration (ET) estimated from an Unoccupied Aerial System (UAS) could help improve irrigation practices, but its spatial resolution is often too detailed for such applications. Therefore, UAS imagery needs to be upscaled to coarser pixel resolutions before applying surface energy balance models. However, a proper aggregation workflow has not been defined for UAS imagery. Therefore, the purpose of this study was to evaluate the impact of various energy balance-based aggregation schemes on generating spatially distributed latent heat flux (LE), and in comparison, to existing occupied aircraft and satellite remote sensing platforms. In 2017, UAS multispectral and thermal imagery, along with ground truth data, were collected at various cotton growth stages. These data sources were combined to model LE using a Two-Source Energy Balance Priestley-Taylor (TSEB-PT) model. Several UAS aggregation schemes were tested, including the mode of aggregation (i.e. input image and output flux), as well as the averaging scheme (i.e. simple aggregation vs. Box-Cox). Results indicate that output flux aggregation with Box-Cox averaging (termed Out-BC) produced the lowest relative upscaling pixel-scale variability in LE and lowest absolute prediction errors (relative to eddy covariance flux tower measurements). Out-SA was also more accurate in reproducing LE from occupied aircraft and satellite imagery, when compared to flux tower measurements. Therefore, UAS LE estimates can be reliably aggregated to coarser pixel resolutions, which makes for faster image processing for operational applications.