Estimation and Mapping of Soil Properties Based on Multi-Source Data Fusion
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: closed (30 September 2020) | Viewed by 71814
Special Issue Editors
Interests: proximal soil sensing; soil and water management; soil dynamics; tillage; traction; compaction; mechanical weeding; soil remediation and management and precision agriculture
Special Issues, Collections and Topics in MDPI journals
Interests: soil sensing; data fusion; soil spectroscopy; digital soil mapping; optical remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in remote and proximal sensing technologies are valuable for enriching our geo-datasets of soil properties, which are necessary for soil management and the precision application of farming input resources. This is because of the advantages of these modern technologies that provide a high sampling density enabling the exploration of the spatial variability of soil characteristics with high resolution and are fast and cost-effective compared to the traditional laboratory analysis methods. However, soils are complex, and measurements of key soil properties or processes in soils might not be achievable by the use of a single sensor. This necessitates new approaches that present innovative solutions beyond the single-sensor approach and can be implemented in situ in either stationary or on-line measurement modes. In the last few years, several studies on multi-sensor and data fusion approaches have been reported in the literature, although this research area is still at its early stages of development. The integration of different data—multi-source data fusion—has greatly benefited many applications that require more extensive temporal and spatial information than that contained in any individual dataset provided by a single sensor. At the same time, the major progresses that have been made in different aspects of digital soil mapping (DSM) make DSM increasingly mature and operable than ever before. The integration of multi-sensor source data fusion with the DSM technique will provide a better understanding of soil processes and enable a more accurate estimation of soil properties at various spatial and temporal scales. It will also provide new insights into processes occurring in soils and sources of variabilities linked to soil dynamics in different scenarios of land management practices, environmental pollution, and climate change.
In this Special Issue, we are seeking original scientific contributions on new methods for the estimation and mapping of biological, physical, and chemical soil properties based on multi-source spatio-temporal data fusion techniques. The Special Issue is open to all scientists working in related fields, and submissions relevant to the topics listed below are welcome:
- Proximal soil sensing for the measurement and spatial modelling of soil properties (e.g., fertility, physical, chemical, contaminants)
- Remote sensing for the measurement and spatial modelling of soil properties (e.g., fertility, physical, chemical, contaminants)
- Modelling approaches for deriving new indices to estimate soil properties and/or soil processes
- The potential of multi-sensor techniques for deriving information on soils including decision-support tools
- Data-fusion approaches applied to proximal and remote sensing of soils
- Estimating and mapping soil-related yield limiting factors, including yield prediction
- The use of proximal and remote sensing in precision agriculture
- Measurement and mapping of soil contaminations including heavy metals and hydrocarbon contaminations.
Prof. Dr. Abdul M. Mouazen
Prof. Dr. Zhou Shi
Guest Editors
Manuscript Submission Information
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Keywords
- Proximal soil sensing
- Remote sensing
- Soil property
- Sensor fusion
- Data fusion
- Digital soil mapping
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