Dear Colleagues,

We are pleased to invite you for the Special Issue “Irrigation Mapping Using Satellite Remote Sensing II” – continuation of the earlier successful effort.

At the time of writing this summary (April 2023), vast lands across the world encounter severe drought, with some regions in Spain and the USA entering a critical water shortage stage following multi-annual drought events, prompting regional governments to reduce water allocations to 10–20% and completely restrict irrigation. If we assume a fairly constant but unevenly distributed amount of water at a global scale amid increasing water use by population and cultivation, irrigation becomes pivotal in all resource nexuses. Remote sensing at field and unmanned aerial systems (UASs) scales provide prospects for local/regional solutions to assist irrigation models, and evaluate and account for spatiotemporal biases and hence save water (e.g., deficit irrigation). However, satellite data ultimately have large/global outreach, often with open access, and can be fully automated. Remote sensing data and numerical crop modeling are also suggested to be used conjunctively to assess crop water status and groundwater return flows more efficiently and support regional water and irrigation systems management. Machine learning algorithms—neural networks, change detection, random forest—synergistically used with high-resolution remote sensing data also offer new approaches to estimate irrigation variables more accurately.

This Special Issue aims to contribute to studies using terrestrial remote sensing data and advanced methods as complementary tools to evaluate the hydrological cycle and improve or innovate irrigation and optimize water use. Our aim is to tackle, among others, the integration of multi-sensor and multi-scale data, especially satellite imagery, for irrigation variables, irrigation-relevant data noise assessment and reduction (mixed pixels, edge effects), detection of evaporative losses in agriculture at a satellite scale, advantages and risks of machine-learning-based decision support systems, ensembled quantification of irrigation demands, calculating regional and global water use efficiency, and especially constraints other than socioeconomic: coarser resolutions of satellite data, potential of deep-penetrating radar to assist satellite studies, diurnal crop water dynamics masking actual irrigation needs, etc. Novel research using very-high-resolution and -accuracy instruments, for instance nuclear magnetic resonance, to support the satellite-scale mapping of crop water and/or soil moisture are also welcomed in this Special Issue.

We therefore welcome original research articles and reviews from scientific and industry experts, including PhD students, for an excellent opportunity to publish original and novel findings on the topic. Research areas may include, but are not limited to, the following:

• Mapping of irrigated areas and evapotranspiration using optical, radar and other sensors at multiple spatiotemporal and spectral scales;
• Assimilation of satellite data and novel sensor data flows in irrigation/hydrologic models to monitor crop water consumption and use;
• Remote-sensing-assisted irrigation engineering and hydraulic management at local and regional scales;
• Computation methods and algorithms, including machine learning, to estimate crop drought/heat stress and irrigation need, and beta-version decision support systems in irrigation management;
• Drought perceptions and irrigation water allocation from a sociopolitical perspective based on existing and planned satellite monitoring programs.

We look forward to receiving your contributions.

Dr. Kiril Manevski
Prof. Mathias N. Andersen
Dr. Junxiang Peng
Prof. Dr. Juan Antonio Rodríguez Díaz
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. Remote Sensing 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 2700 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.

• irrigation scheduling
• deficit irrigation
• scale issue
• biophysical modeling
• artificial intelligence approach
• drought and heat stress
• transpiration
• evaporative loss in agriculture
• water allocation for irrigation

• Irrigation Mapping Using Satellite Remote Sensing in Remote Sensing (9 articles)