Advanced Remote Sensing for Next-Generation Smart Agriculture: Innovations, Integration, and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: 23 January 2026 | Viewed by 17
Special Issue Editors
Interests: RTM; crop model; UAV; crop mapping; crop model
Special Issues, Collections and Topics in MDPI journals
2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Interests: orchard monitoring; crop phenotyping; LiDAR; UAV
Special Issues, Collections and Topics in MDPI journals
Interests: crop modelling; plant phenotyping; machine learning; climate adaptation
Interests: precision agriculture; agricultural machinery and equipment; intelligent agriculture; intelligent agricultural equipment; crop growth monitoring; plant protection drone equipment; drone remote sensing
Special Issue Information
Dear Colleagues,
The escalating global challenges of population growth, climate change, and resource scarcity demand a paradigm shift in agricultural production towards more efficient, sustainable, and resilient systems. Smart agriculture, also known as Agriculture 4.0, has emerged as a data-driven solution with remote sensing technology at its core. Recent advancements in sensor technologies, such as hyperspectral, LiDAR, and thermal imaging, coupled with new platforms like high-resolution satellite constellations and unmanned aerial vehicles (UAVs), are generating unprecedented data streams. Simultaneously, the evolution of powerful analytical methods, including Artificial Intelligence and deep learning, is unlocking the full potential of this data to monitor and manage agricultural landscapes with remarkable precision and scale. This synergy is revolutionizing applications from field-level phenotyping to regional-scale yield forecasting.
This Special Issue aims to curate a collection of cutting-edge research that highlights the latest innovations and applications of remote sensing in smart agriculture. The goal is to bridge the gap between technological potential and practical on-farm implementation, creating actionable intelligence for farmers, agronomists, and policymakers.
We invite submissions of original research articles and comprehensive reviews covering, but not limited to, the following topics:
- Deep learning and machine learning algorithms for crop classification, segmentation, and status monitoring.
- Fusion of multi-modal remote sensing data (e.g., optical, LiDAR, SAR, thermal).
- High-throughput phenotyping using remote and proximal sensing.
- Estimation and forecasting of crop yield and biomass.
- Monitoring of soil properties, including moisture, nutrients, and organic carbon.
- Detection and management of biotic and abiotic stresses (e.g., pests, diseases, water scarcity, nutrient deficiencies).
- Remote sensing for precision irrigation, fertilization, and spraying.
- Development of remote sensing-driven Decision Support Systems (DSS) for agriculture.
Prof. Dr. Fenghua Yu
Dr. Hao Yang
Dr. Qiaomin Chen
Dr. Xiaobo Sun
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. 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
- smart agriculture
- remote sensing
- Unmanned Aerial Vehicles (UAVs)
- satellite imagery
- Hyperspectral & Multispectral Imaging
- LiDAR
- Artificial Intelligence (AI)
- crop monitoring
- yield prediction
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