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Agronomy
Special Issues
Geoinformatics Application in Agriculture—Volume II
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Geoinformatics Application in Agriculture—Volume II

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 3772

Special Issue Editors

Dr. Jitka Kumhálová

E-Mail Website
Guest Editor
Faculty of Engineering, Department Machinery Utilization, Czech University of Life Sciences Prague, Prague, Czech Republic
Interests: GIS; optical remote sensing; UAV; satellite images; photogrammetry; precision agriculture
Special Issues, Collections and Topics in MDPI journals
Dr. Jose A. Domínguez Gómez

E-Mail Website
Guest Editor
Department of Topographic and Cartographic Engineering, Universidad Politécnica de Madrid, Madrid, Spain
Interests: GIS; optical and radar remote sensing; UAV; satellite images; photogrammetry; precision agriculture
Prof. Dr. Iñigo Molina

E-Mail Website
Guest Editor
Department of Topographic and Cartographic Engineering, Universidad Politécnica de Madrid, Madrid, Spain
Interests: soil moisture content (SMC); global navigation satellite systems reflectometry (GNSS-R); active-passive sensors; earth-science applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Following the success of the first Special Issue “Geoinformatics Application in Agriculture” in Agronomy, the Editorial Office is pleased to launch a second series of the issue.

With the development of geoinformatics (GIS and remote sensing), the interest of users in these advanced tools is also increasing. In recent years, there has been an enhanced focus on robotics and automation technologies, which fulfill the concept of smart agriculture. This mainly involves the implementation of geoinformatics tools, where modern methods such as machine learning or advanced approaches of photogrammetry are employed. The development in this area also follows the current technological development (development of a modern UAV concept, precise sensors, etc.). The present Special Issue will focus on recent advancements in the application of geoinformatics in agriculture. Research papers, communications, and review articles are welcome. In particular, we encourage contributions covering the implementation of geoinformatics methods into agricultural practice. These methods include the use and application of GIS, especially their advanced tools and solutions. Particular attention will also be given to research involving the implementation of remote sensing methods, such as optical and microwave remote sensing and its application in agriculture. Attention will also be given to studies that focus unmanned aerial vehicle development in the agricultural context and the development of new solutions based on photogrammetry methods for crop growth monitoring, special crops included.

Dr. Jitka Kumhálová
Dr. Jose A. Domínguez Gómez
Prof. Dr. Iñigo Molina
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. Agronomy is an international peer-reviewed open access monthly 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

  • geoinformatics
  • smart farming
  • GIS application
  • optical and microwave remote sensing
  • UAV
  • photogrammetry

Published Papers (3 papers)

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Research

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16 pages, 4510 KiB  
Article
Refined Evaluation of Climate Suitability of Maize at Various Growth Stages in Major Maize-Producing Areas in the North of China
by Xiaowei Wang, Xiaoyu Li, Yunsheng Lou, Songcai You and Haigen Zhao
Agronomy 2024, 14(2), 344; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy14020344 - 08 Feb 2024
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Abstract
The Northeast region of China and Huang Huai Hai (3H) region are vital maize production bases in northern China that are crucial for national food security. The absence of phenological data hinders a detailed assessment of the alignment between maize development stages and [...] Read more.
The Northeast region of China and Huang Huai Hai (3H) region are vital maize production bases in northern China that are crucial for national food security. The absence of phenological data hinders a detailed assessment of the alignment between maize development stages and climatic resources. This study combines the authors’ maize phenology data with climate suitability modeling to evaluate maize’s climate suitability at different developmental stages in both regions. This study shows that during the maize growth cycle, the average temperature, precipitation, sunshine, and comprehensive climate suitability were 0.77, 0.49, 0.87, and 0.65, respectively, in the Northeast. In contrast, the average temperature, precipitation, sunshine, and comprehensive climate suitability in the 3H region were 0.98, 0.53, 0.73, and 0.70, respectively. Precipitation is a major factor influencing maize growth, with temperature and sunshine impacting growth differently across regions. Temperature significantly affects maize in the Northeast, while sunshine plays a greater role in the 3H region. The Northeast is suitable for drought-resistant maize varieties, and implementing a late harvest policy in Liaoning could enhance maize yield. The 3H region generally has favorable climatic conditions. Apart from certain parts of Henan needing drought-resistant varieties, areas with ample growing seasons can adopt long-duration varieties to maximize thermal resource utilization. Our results have important implications for optimizing maize planting strategies and enhancing regional resilience, aiming to assess meteorological factors’ impact on maize growth in key production areas. Full article
(This article belongs to the Special Issue Geoinformatics Application in Agriculture—Volume II)
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16 pages, 2268 KiB  
Article
Unmanned-Aerial-Vehicle Data as an Effective Tool for the Evaluation of Ancient Khorasan and Modern Kabot Spring Wheat Varieties under Different Tillage Systems
by Kristýna Balážová, Jitka Kumhálová and Jan Chyba
Agronomy 2024, 14(1), 147; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy14010147 - 08 Jan 2024
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Abstract
With the changing climate, there is an increasing emphasis on drought-resistant varieties, including the ability to maintain quality production. As there is also interest in ancient wheat varieties, the aim of this study was to evaluate the growth parameters of the ancient Khorasan [...] Read more.
With the changing climate, there is an increasing emphasis on drought-resistant varieties, including the ability to maintain quality production. As there is also interest in ancient wheat varieties, the aim of this study was to evaluate the growth parameters of the ancient Khorasan (Kamut®) and modern Kabot spring wheat varieties using remote sensing data. Images from unmanned aerial vehicles during four growing seasons were processed. Based on vegetation indices, the growth of these varieties and their response to meteorological conditions were evaluated, as well as the ability to resist drought and higher temperatures with respect to specific soil conditions under conventional (CT), minimum (MTC), and minimization (MTD) tillage systems. It was found that Khorasan had the lowest values of the vegetation indices on the CT variant in the dry years 2022 and 2023. On the contrary, in the previous wet years, 2020 and 2021, both varieties showed similar results. Regarding water stress, the CT variant was also the least suitable for ancient Khorasan (average Crop Water Stress Index = CWSI = 0.38). On the contrary, this variant seems to be suitable for the modern Kabot variety (CWSI = 0.29), while no significant difference between tillage variants was found for this variety. In general, water stress was easily detectable from the observed parameters in the growth phase of stem elongation (R2 up to 0.88). Regarding the individual methods of tillage and water stress, the ancient variety Khorasan performed the worst with the CT variant. MTD appeared to be the best tillage method for Khorasan cultivation in terms of water management. Full article
(This article belongs to the Special Issue Geoinformatics Application in Agriculture—Volume II)
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Review

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23 pages, 38159 KiB  
Review
Web Mapping for Farm Management Information Systems: A Review and Australian Orchard Case Study
by Hari Krishna Dhonju, Kerry Brian Walsh and Thakur Bhattarai
Agronomy 2023, 13(10), 2563; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy13102563 - 05 Oct 2023
Cited by 1 | Viewed by 2086
Abstract
A web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on [...] Read more.
A web mapping XYZ Tile Layer Service, such as Google Earth (GE), provides an amazing resource for the visualization of spatial data against aerial and satellite imagery with global coverage, typically at a resolution finer than 5 m. However, the increasing requirement on spatial accuracy in farm information requires a greater appreciation of the issues involved in the use of such services. Position errors can be created in the georeferencing and orthorectification of images, transformation between reference frames (datums) in map projection, e.g., using a spheroid as compared to an ellipsoid earth model, and tectonic shifts. A review is provided of these issues, and a case study is provided of the horizontal positional accuracy of web map imagery for Australian mango orchards. Positional accuracies varied from 1.804 to 6.131 m across four farms using GE 2021 imagery, between 1.556 and 3.365 m in one farm for the most recent imagery available from each of four web map providers, and from 0.806 m (in 2016) to 10.634 m (in 2003) in one farm for the period of 2003 and 2021 using the historical GE imagery resource. A procedure involving the estimation of four transformation parameters was demonstrated for the alignment of GNSS data with GE imagery. However, as the scale factor was unity and the rotational value was near zero, the use of a simple horizontal mean shift vector was recommended. Further recommendations are provided on (i) the use of web mapping services, with a comparison of the use of UAV survey imagery, and (ii) the need for metadata, particularly the date of collection, on collected position data, in the context of use in farm management information systems. Full article
(This article belongs to the Special Issue Geoinformatics Application in Agriculture—Volume II)
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