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Multi-Source Remote Sensing Data for Water Resource Management in Agriculture

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 1694

Special Issue Editors


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Guest Editor
Council for Agricultural Research and Economics (CREA) Research Centre for Agricultural Policies and Bioeconomy, Borgo XX Giugno 74, 06121 Perugia, Italy
Interests: environmental impact assessment; remote sensing applications; water resources management; vegetation mapping agricultural statistics

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Guest Editor
French National Institute for Agriculture, Food, and Environment (INRAE), Maison de la Télédétection—UMR TETIS, 500 rue JF Breton, CEDEX 05, 34093 Montpellier, France
Interests: environmental science; irrigation and water management; soil science; microwave remote sensing; lidar
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Institute of Soil Science and Plant Cultivation (IUNG).ul. Czartoryskich 8, 24-100 Pulawy, Poland
Interests: evapotranspiration; water stress; drought; agricultural policy; environmental impact assessment

Special Issue Information

Dear Colleagues,

Water plays a fundamental role for agricultural production and plays an important role in food security. Irrigated agriculture represents 20% of the total cultivated land and contributes of 40% percent of the total food produced worldwide. Irrigated agriculture is, on average, at least twice as productive per unit of land as rainfed agriculture, thereby allowing for more production intensification and crop diversification. Due to population growth, urbanization, and climate change, competition for water resources is expected to increase, with a particular impact on agriculture. Irrigation monitoring is of great importance in agricultural water management to guarantee better water use efficiency, especially under changing climatic conditions and water scarcity. In that context the evolution of remote sensing techniques and availability of data from different platform (Ground-Based, UAV-Based, Satellite-Based) in recent years, has opened new perspectives for supporting sustainable water resources management. A great contribution of Remote Sensing on irrigation monitoring is to provide detailed spatial/temporal information of the dynamics of the irrigated areas and the key elements of wich irrigation depend like crop Evapotranspiration (ET) and Soil Moisture (SM). This information would be helpful for supporting policy makers in the formulation of strategic agricultural plans to increase the efficiency of water use in agriculture.

The purpose of this Special Issue is to identify current research trends and key issues relate to water resource management in agriculture. We welcome novel research, reviews covering all irrigation related topics. We are especially interested in recent integrated water resources research using data fusion techniques, combining different sources (e.g., multi/hyperspectral sensor, optical/microwave, UAV with ground measurements), for retrieve ET constituents' parameters (such as land surface temperature, LAI, crop height, and albedo), and SM component (e.g., vegetation index, soil backscattering model, roughness and vegetation effects of radar signal).

The topic “Multi-Source Remote Sensing Data for Water Resource Management in Agriculture” invites high-quality papers focused on the design and development of methods, algorithm, strategies, and new technologies for water resource management and development impact assessment using multi-source remote sensing technologies under land use and climate changes. Potential topics include, but are not limited to:

  • Mapping irrigated areas;
  • Evapotranspiration mapping;
  • Soil Moisture mapping;
  • Synergy between radar and other sensors for SM and ET retrieval;
  • Role of remote sensing in supporting water policy;
  • Application of remote sensing techniques to estimate water stored volume in artificial reservoir

Dr. Pasquale Nino
Dr. Nicolas Baghdadi
Guest Editors

Artur Łopatka
Guest Editor Assistant

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. 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.

Keywords

  • irrigation
  • optical and microwave remote sensing
  • evapotranspiration
  • soil moisture
  • unmanned aerial vehicles (UAV)
  • ground sensor

Published Papers (1 paper)

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Research

19 pages, 7992 KiB  
Article
Improving the STARFM Fusion Method for Downscaling the SSEBOP Evapotranspiration Product from 1 km to 30 m in an Arid Area in China
by Jingjing Sun, Wen Wang, Xiaogang Wang and Luca Brocca
Remote Sens. 2023, 15(22), 5411; https://doi.org/10.3390/rs15225411 - 18 Nov 2023
Viewed by 1088
Abstract
Continuous evapotranspiration (ET) data with high spatial resolution are crucial for water resources management in irrigated agricultural areas in arid regions. Many global ET products are available now but with a coarse spatial resolution. Spatial-temporal fusion methods, such as the spatial and temporal [...] Read more.
Continuous evapotranspiration (ET) data with high spatial resolution are crucial for water resources management in irrigated agricultural areas in arid regions. Many global ET products are available now but with a coarse spatial resolution. Spatial-temporal fusion methods, such as the spatial and temporal adaptive reflectance fusion model (STARFM), can help to downscale coarse spatial resolution ET products. In this paper, the STARFM model is improved by incorporating the temperature vegetation dryness index (TVDI) into the data fusion process, and we propose a spatial and temporal adaptive evapotranspiration downscaling method (STAEDM). The modified method STAEDM was applied to the 1 km SSEBOP ET product to derive a downscaled 30 m ET for irrigated agricultural fields of Northwest China. The STAEDM exhibits a significant improvement compared to the original STARFM method for downscaling SSEBOP ET on Landsat-unavailable dates, with an increase in the squared correlation coefficients (r2) from 0.68 to 0.77 and a decrease in the root mean square error (RMSE) from 10.28 mm/10 d to 8.48 mm/10 d. The ET based on the STAEDM additionally preserves more spatial details than STARFM for heterogeneous agricultural fields and can better capture the ET seasonal dynamics. The STAEDM ET can better capture the temporal variation of 10-day ET during the whole crop growing season than SSEBOP. Full article
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