Hyperspectral Sensors for Soil Parameters and Crop Parameters Retrieval
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 20 July 2024 | Viewed by 1577
Special Issue Editors
Interests: the synthetic aperture radar image processing; the application of unmanned aerial vehicle; quantitative estimation of land surface variables from satellite remote sensing and on integration of multiple data sources with numerical models
Special Issues, Collections and Topics in MDPI journals
Interests: algorithms for automatic linear and other man-made feature detection from images; methods for GIS feature extraction and lane use/cover change detection in urban environment using multispectral and hyperspectral data; methods for object oriented information extraction from high resolution remotely sensed imagery; applications of radar/optical remote sensing and GIS for environmental change analysis near large rivers/mountains and in marsh and mangrove wetlands
Special Issues, Collections and Topics in MDPI journals
Interests: quantitative remote sensing; vegetation remote sensing; data fusion; data assimilation; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The utilization of hyperspectral sensors in remote sensing has opened up avenues for the extraction of soil properties and the analysis of crop health. This technology, using a wide range of electromagnetic spectrum, provides continuous spectral data that can improve our understanding of soil properties, crop growth conditions, and changes. Further, it can help in accurate retrieval of biophysical and biochemical parameters of soil and crops, thereby significantly contributing to precision agriculture and sustainable farming practices. Therefore, the burgeoning use of hyperspectral sensors in remote sensing provides unprecedented possibilities for comprehensive monitoring of soil and crop parameters. In light of these advancements, we are inviting researchers to contribute their latest findings and research work.
The aim of this special issue is to convene and showcase the most recent developments, innovations, and applications of hyperspectral sensors in retrieving soil and crop parameters. This includes, but is not limited to, the use of hyperspectral sensors mounted on various platforms such as stationary setups, mobile units, Unmanned Aerial Vehicles (UAVs), aircraft, and satellites at different spatial and temporal scales.
This special Issue, “Hyperspectral Sensors for Soil Parameters and Crop Parameters Retrieval”, encourages submissions that discuss novel techniques or approaches leveraging hyperspectral sensors to retrieve soil parameters such as soil moisture, organic matter, mineral content, and other soil physicochemical properties. Similarly, contributions are welcomed on the estimation or inversion of crop parameters, including growth conditions, nutritional status, disease detection, and productivity. These could span different spatial and temporal scales, covering small farm-level studies to global agricultural landscapes.
Dr. Minfeng Xing
Prof. Dr. Jinfei Wang
Dr. Qisheng He
Guest Editors
Manuscript Submission Information
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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
- hyperspectral imaging
- soil parameter retrieval
- crop parameter retrieval
- remote sensing technologies
- precision agriculture
- sustainable farming
- soil physicochemical properties
- crop health monitoring
- unmanned aerial vehicles (UAVs)
- biophysical and biochemical parameter estimation
