Quantitative Remote Sensing and Its Applications in Agriculture and Vegetation
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: 26 February 2025 | Viewed by 240
Special Issue Editors
Interests: three-dimensional radiative transfer modelling; remote sensing scene modelling; temperature and emissivity separation; vegetation index; crop mapping
Interests: bidirectional reflectance distribution function; precision agriculture; geological remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: radiative transfer modelling; LiDAR; forestry; voxelization; ray tracing; biophysical information retrieval
Special Issues, Collections and Topics in MDPI journals
Interests: three-dimensional radiative transfer modelling; vegetation; hyperspectral; LiDAR; fluorescence; radiative budget
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Quantitative remote sensing has revolutionized the way we monitor and manage agricultural landscapes and vegetation. With advancements in sensor technology, data processing, and modelling techniques, remote sensing offers unprecedented opportunities to gather detailed and accurate information about crops and vegetation. These developments are crucial for enhancing our understanding of agricultural systems and vegetation dynamics, enabling better decision-making, and improving sustainability.
This Special Issue aims to explore the latest advancements in quantitative remote sensing and its wide range of applications in agriculture and vegetation studies. We invite submissions that delve into innovative methodologies, sensor technologies, and modelling approaches that contribute to the quantitative assessment and monitoring of agricultural and vegetative systems. Articles may address, but are not limited, to the following topics:
- Sensor Calibration and Design
- Radiation Directionality Observing and Modelling
- Kernel-driven Models
- Geometric Optics Models
- Three-dimensional Remote Sensing Scene Modelling
- Radiative Transfer
- Radiation Budget and Balance
- Authenticity Validation and Spatial Scale Conversion
- Photosynthetically Active Radiation (PAR)
- Leaf Area Index (LAI) and Clumping Index
- Chlorophyll Content and Fluorescence
- Vegetation Index
- Artificial Intelligence in Remote Sensing
- Disaster Monitoring and Crop Yield Estimation
Dr. Zhijun Zhen
Prof. Dr. Shengbo Chen
Dr. Tiangang Yin
Prof. Dr. Jean-Philippe Gastellu-Etchegorry
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
- quantitative remote sensing
- radiation directionality observing and modelling
- radiative transfer and radiation budget
- bidirectional reflectance distribution function (BRDF)
- directional anisotropy
- angular anisotropy
- retrieval of plant biochemical parameters
- precision agriculture
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