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Remote Sensing Application in Augmenting Water and Fertilizer Utilization for...
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Remote Sensing Application in Augmenting Water and Fertilizer Utilization for Sustainable Agriculture

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Nutrition".

Deadline for manuscript submissions: closed (30 June 2025) | Viewed by 215

Special Issue Editors

Prof. Dr. Junying Chen

E-Mail Website
Guest Editor
College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
Interests: application of remote sensing technology in agriculture; reclaimed water irrigation; water-saving agriculture
Dr. Wenquan Gu

E-Mail Website
Guest Editor
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Interests: intelligent regulation of water resources system; uncertainty and risk analysis of water resources system; agricultural remote sensing; hydrological model
Dr. Xiaochun Zhang

E-Mail Website
Guest Editor
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Interests: remote sensing data fusion modelling; remote sensing evapotranspiration and disaster monitoring

Special Issue Information

Dear Colleagues,

The growth of the global population and the intensification of climate change have resulted in water scarcity and ecological degradation becoming significant constraints to sustainable agricultural development. The scientific and efficient utilization of water and fertilizer in agricultural production to ensure the stability and sustainability of agricultural production has become a prominent area of global research.

Remote sensing technology, as a non-destructive monitoring technology, can provide large-scale, real-time and continuous observations for monitoring crop health and the physicochemical properties of soil, assessing the impact of soil moisture and nutrients on crop yields and the regional environment, and optimizing on-farm irrigation and fertilizer application strategies to ensure food security and environmentally compatible development.

We welcome contributions regarding the innovative application of remote sensing technology in sustainable agricultural practices, with a particular focus on the efficient use of water and fertilizer. The objective is to investigate the potential use of remote sensing technology in advancing precision agriculture and enhancing the sustainability and efficiency of resource use.

Prof. Dr. Junying Chen
Dr. Wenquan Gu
Dr. Xiaochun Zhang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • remote sensing
  • water and fertilizer utilization
  • sustainable agriculture
  • crop growth condition

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Published Papers (1 paper)

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Research

22 pages, 6134 KiB  
Article
The Evaluation of Small-Scale Field Maize Transpiration Rate from UAV Thermal Infrared Images Using Improved Three-Temperature Model
by Xiaofei Yang, Zhitao Zhang, Qi Xu, Ning Dong, Xuqian Bai and Yanfu Liu
Plants 2025, 14(14), 2209; https://doi.org/10.3390/plants14142209 (registering DOI) - 17 Jul 2025
Abstract
Transpiration is the dominant process driving water loss in crops, significantly influencing their growth, development, and yield. Efficient monitoring of transpiration rate (Tr) is crucial for evaluating crop physiological status and optimizing water management strategies. The three-temperature (3T) model has potential for rapid [...] Read more.
Transpiration is the dominant process driving water loss in crops, significantly influencing their growth, development, and yield. Efficient monitoring of transpiration rate (Tr) is crucial for evaluating crop physiological status and optimizing water management strategies. The three-temperature (3T) model has potential for rapid estimation of transpiration rates, but its application to low-altitude remote sensing has not yet been further investigated. To evaluate the performance of 3T model based on land surface temperature (LST) and canopy temperature (TC) in estimating transpiration rate, this study utilized an unmanned aerial vehicle (UAV) equipped with a thermal infrared (TIR) camera to capture TIR images of summer maize during the nodulation-irrigation stage under four different moisture treatments, from which LST was extracted. The Gaussian Hidden Markov Random Field (GHMRF) model was applied to segment the TIR images, facilitating the extraction of TC. Finally, an improved 3T model incorporating fractional vegetation coverage (FVC) was proposed. The findings of the study demonstrate that: (1) The GHMRF model offers an effective approach for TIR image segmentation. The mechanism of thermal TIR segmentation implemented by the GHMRF model is explored. The results indicate that when the potential energy function parameter β value is 0.1, the optimal performance is provided. (2) The feasibility of utilizing UAV-based TIR remote sensing in conjunction with the 3T model for estimating Tr has been demonstrated, showing a significant correlation between the measured and the estimated transpiration rate (Tr-3TC), derived from TC data obtained through the segmentation and processing of TIR imagery. The correlation coefficients (r) were 0.946 in 2022 and 0.872 in 2023. (3) The improved 3T model has demonstrated its ability to enhance the estimation accuracy of crop Tr rapidly and effectively, exhibiting a robust correlation with Tr-3TC. The correlation coefficients for the two observed years are 0.991 and 0.989, respectively, while the model maintains low RMSE of 0.756 mmol H2O m−2 s−1 and 0.555 mmol H2O m−2 s−1 for the respective years, indicating strong interannual stability. Full article
(This article belongs to the Special Issue Remote Sensing Application in Augmenting Water and Fertilizer Utilization for Sustainable Agriculture)
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