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Applied Remote Sensing in Irrigated Agriculture
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Applied Remote Sensing in Irrigated Agriculture

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water, Agriculture and Aquaculture".

Deadline for manuscript submissions: closed (20 July 2025) | Viewed by 1449

Special Issue Editors

Prof. Dr. Christopher M. U. Neale

E-Mail Website
Guest Editor
Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE 68588, USA
Interests: remote sensing of agriculture and natural resources; irrigation water management
Special Issues, Collections and Topics in MDPI journals
Dr. Ivo Zution Gonçalves

E-Mail Website
Guest Editor
Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE 68588, USA
Interests: irrigation water management; climate impacts in agriculture; remote sensing for irrigation water management; crop yield estimation

Special Issue Information

Dear Colleagues,

The goal of this Special Issue is to present the latest remote sensing technologies and approaches being used to monitor irrigated agriculture, estimate consumptive use by crops, and conduct irrigation scheduling. The remote sensing platforms presently used in agriculture include satellites, aircraft, and drones. The development of low-cost, high-resolution digital sensors have led to commercial constellations of satellites that provide high-resolution multispectral imagery at global scales, while aircraft and drones provide imagery at regional and field scales. Several energy balance modeling approaches that depend on multispectral and thermal infrared wavelengths have been improved and are operational. We encourage submitting papers describing the latest applications and models that use remote sensing inputs for conducting irrigation water demand estimates and irrigation scheduling.

We are pleased to invite you to submit a manuscript to this Special Issue titled “Applied Remote Sensing in Irrigated Agriculture.” This Special Issue aims to present the latest remote sensing-based models and approaches for monitoring water use and conducting irrigation water management in agriculture.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  • Remote sensing-based land surface energy balance for water resources management and irrigation;
  • Remote sensing-based soil–water balance for sustainable irrigation practices;
  • Development and application of innovative sensors for monitoring crop water demand and stress;
  • Advances in hydrology and water resource modeling for efficient irrigation strategies;
  • Atmospheric science and meteorological modeling for improved irrigation scheduling and climate adaptation;
  • Remote sensing applications in evapotranspiration mapping for irrigated cropping systems;
  • Leveraging UAV and satellite platforms for real-time irrigation decision support;
  • Spatial and temporal variability of soil water content using remote sensing for irrigation optimization;
  • Integration of remote sensing with machine learning for predicting crop yield and irrigation water demand.

We look forward to receiving your contributions.

Prof. Dr. Christopher M. U. Neale
Dr. Ivo Zution Gonçalves
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • satellite and airborne remote sensing
  • energy balance
  • evapotranspiration
  • crop health and yield monitoring

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

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14 pages, 1977 KB  
Article
Assessing Riparian Evapotranspiration Dynamics in a Water Conflict Region in Nebraska, USA
by Ivo Z. Gonçalves, Burdette Barker, Christopher M. U. Neale, Derrel L. Martin and Sammy Z. Akasheh
Water 2025, 17(20), 2949; https://doi.org/10.3390/w17202949 - 13 Oct 2025
Viewed by 279
Abstract
The escalating pressure on water resources in agricultural regions has become a catalyst for water conflicts. The adoption of innovative approaches to estimate actual evapotranspiration (ETa) offers potential solutions to mitigate conflicts related to water usage. This research presents the application of a [...] Read more.
The escalating pressure on water resources in agricultural regions has become a catalyst for water conflicts. The adoption of innovative approaches to estimate actual evapotranspiration (ETa) offers potential solutions to mitigate conflicts related to water usage. This research presents the application of a remote sensing-based methodology for estimating actual evapotranspiration (ETa) based on a two-source energy balance model (TSEB) for riparian vegetation in Nebraska, US using the Spatial EvapoTranspiration Modeling Interface (SETMI). Estimated results through SETMI and field data using the eddy covariance system (EC) considering the period 2008–2013 were used to validate the energy balance components and ETa. Modeled energy balance components showed a strong correlation to the ground data from EC, with ET presenting R2 equal to 0.96 and RMSE of 0.73 mm.d−1. In 2012, the lowest adjusted crop coefficient (Kcadj) values were observed across all land covers, with a mean value of 0.49. The years 2013 and 2012, due to the dry conditions, recorded the highest accumulated ETa values (706 mm and 664 mm, respectively). Soybeans and corn exhibited the highest ETa values, recording 699 mm and 773 mm, respectively. Corn and soybeans, together accounting for a substantial portion of the land cover at 15% and 3%, respectively, play a significant role. Given that most fields cultivating these crops are irrigated, both pumped groundwater and surface water directly impact the water source of the Republican River. The SETMI model has generated appropriate estimated daily ETa values, thereby affirming the model’s utility as a tool for assisting water management and decision-makers in riparian zones. Full article
(This article belongs to the Special Issue Applied Remote Sensing in Irrigated Agriculture)
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Review

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26 pages, 2055 KB  
Review
Evapotranspiration Estimation in the Arab Region: Methodological Advances and Multi-Sensor Integration Framework
by Shamseddin M. Ahmed, Khalid G. Biro Turk, Adam E. Ahmed, Azharia A. Elbushra, Anwar A. Aldhafeeri and Hossam M. Darrag
Water 2025, 17(18), 2702; https://doi.org/10.3390/w17182702 - 12 Sep 2025
Viewed by 795
Abstract
Evapotranspiration (ET) estimation is crucial for sustainable water resource management in arid and semi-arid regions, particularly in the Arab world, where water scarcity remains a significant challenge. The objectives of this study were to map dominant ET estimation techniques and their geographic distribution, [...] Read more.
Evapotranspiration (ET) estimation is crucial for sustainable water resource management in arid and semi-arid regions, particularly in the Arab world, where water scarcity remains a significant challenge. The objectives of this study were to map dominant ET estimation techniques and their geographic distribution, demonstrate fusion-based ET estimation under data-scarce conditions, and examine their alignment with climate change and food security priorities. The study reviewed 1279 ET-related articles indexed in the Web of Science, highlighting methodological trends, regional disparities, and the emergence of data-driven techniques. The results showed that traditional methods—primarily the Penman-Monteith model—dominate nearly 70% of the literature. In contrast, machine learning (ML), remote sensing (RS), and artificial intelligence (AI) collectively account for approximately 30%, with hybrid fusion frameworks appearing in only 2% of studies. ML applications are concentrated in Morocco, Egypt, and Iraq, while 50% of Arab countries lack any ML or AI-based research on energy transition (ET). Complementing the bibliometric analysis, this study demonstrates the practical potential of ML-based ET fusion using Landsat and the FAO Water Productivity (WaPOR) data within Saudi Arabia. A random forest model outperformed traditional averaging, reducing the mean absolute error (MAE) to 215.08 mm/year and the root mean square error (RMSE) to 531.34 mm/year, with a Pearson correlation coefficient of 0.86. The findings advocate for greater support and regional collaboration to advance ET monitoring and integrate ML-based modelling into climate resilience frameworks. Full article
(This article belongs to the Special Issue Applied Remote Sensing in Irrigated Agriculture)
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