Mapping and Monitoring of Agricultural Land Subtypes with Remote Sensing Technologies
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: 15 December 2025 | Viewed by 21
Special Issue Editors
Interests: remote sensing; land cover mapping; semantic segmentation
Interests: remote sensing; machine learning; deep learning; UAV; crop monitoring
Interests: crop classification; time series data analysis; machine learning
Interests: irrigation and drainage engineering; agricultural drought and water resource management; drought monitoring, mitigation, planning, and policy; risk and vulnerability management; remote sensing for drought monitoring and management; soil moisture and hydrologic/watershed modelling
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Special Issue Information
Dear Colleagues,
Agricultural land is not a homogeneous entity but a mosaic of diverse land use types, including paddy fields, rainfed croplands, agriculture facilities (e.g., plastic greenhouses, mulch films), and aquaculture ponds. The precise identification and mapping of these subtypes are critical for optimizing agricultural resource management, ensuring food security, and mitigating environmental risks such as soil degradation, water pollution, and plastic waste accumulation. Traditional broad-scale land cover classifications often fail to capture these subtle yet functionally distinct categories, limiting their utility in policy formulation and precision agriculture.
Remote sensing technologies—due to advancements in high-resolution satellite imagery, hyperspectral sensors, UAVs, and AI-driven analytics—provide unprecedented opportunities for us to achieve the fine-grained discrimination of agricultural land subtypes. For instance, distinguishing plastic-mulched fields from bare soil, mapping fragmented aquaculture ponds in coastal zones, or identifying temporary greenhouse structures requires innovative approaches to spectral analysis, temporal feature extraction, and spatial pattern recognition. This Special Issue seeks to address these challenges by spotlighting cutting-edge methodologies for the fine-scale classification and dynamic monitoring of agricultural land subtypes, with a focus on practical applications in sustainable land use planning and environmental governance.
These should cover or fit within the following themes:
- Paddy field delineation: the spectral unmixing of mixed water–vegetation signatures in rice-growing regions.
- Agricultural facility monitoring: the detection of plastic greenhouses and mulch films using thermal anomalies or polarization features (SAR).
- Aquaculture mapping: the identification of ponds and cages in coastal/inland waters via VHR imagery or Sentinel-1/2 time series.
- Dryland vs. irrigated cropland discrimination: the fusion of soil moisture data (SMAP, Sentinel-1) with optical indices.
- Temporal dynamics: tracking land use transitions (e.g., the conversion of paddy fields to aquaculture) using dense time-series analyses.
- Policy applications: high-resolution datasets for verifying agricultural subsidies, plastic film regulations, or wetland conservation.
Dr. Peng Zhang
Dr. Quanlong Feng
Dr. Pengfei Tang
Dr. Won-Ho Nam
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
- fine-scale agricultural land classification
- paddy field mapping
- agricultural facility detection
- aquaculture monitoring
- pastic mulch identification
- hyperspectral remote sensing
- multi-sensor data fusion
- time-series analysis
- machine learning
- land use policy
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