Special Issue "New Advancements in the Field of Remote Sensing in Land Surface Processes"
Deadline for manuscript submissions: 20 February 2024 | Viewed by 4840
2. Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 Delft, The Netherlands
Interests: land surface processes; terrestrial water cycle; water management; optical remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue in Infrastructures: Applications of Infrared Thermography to Infrastructure Inspection
Special Issue in Sensors: Understanding Land Surface Processes and Ecosystem Changes with Optical and Laser Remote Sensing
Special Issue in Remote Sensing: Remotely Sensed Land Surface Processes
Special Issue in Remote Sensing: Remote Sensing of Desertification
Special Issue in Remote Sensing: Renewable Energy Mapping
Special Issue in Sensors: Advances in Remote Sensors for Earth Observation
Special Issue in Sustainability: Spotlight on Nature-Based Solutions against Natural Hazard
Special Issue in Remote Sensing: Land-Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions
Special Issue in Remote Sensing: Land-Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions II
Special Issue in Remote Sensing: Advances in Remote Sensing for Regional Soil Moisture Monitoring
Special Issue in Remote Sensing: Land-Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions III
Topics: Digital Environment Technology for Supporting Regional Sustainable Development
Decades of remote sensing technology have transformed our understanding of the universe. We are now better able to observe, map, and model earth processes in order to understand not only the dynamics of these processes, but also to understand the earth–atmosphere interactions which they relate to. Natural resources mapping, simulation of water, energy and carbon fluxes, groundwater dynamics, soil moisture and precipitation prediction, natural hazards modelling, and many other areas of application have emerged because of the advancements in remote sensing. We can now acquire images that have much better spatiotemporal resolution, which can be interpreted faster and more efficiently.
This Special Issue aims at providing a snapshot of new horizons in earth observations, which have been opened by simultaneous advances in new physical measurements and by the rapid miniaturization of established sensor systems. Efforts by the science and engineering community have paved the way for fundamentally new measurements, such as Doppler lidars and fluorescence radiometry, and for far-reaching miniaturization of complex instruments, e.g., hyperspectral imagers. In addition, the feasibility of on-board data processing has been demonstrated even on nano-satellites. Such developments are observable in earth observation from space- and airborne platforms and a host of mobile systems. Both earth system science and sustainable use of natural resources are benefiting from such advances.
Land surface processes are complex processes that occur at the interface between the land and the atmosphere, which determine global and local climates at different scales. For example, urban surface energy balance determines the urban climate, while glaciers surface energy balance determines changes in glacier mass and the water balance at a regional scale. The applications of remote sensing in land surface processes have grown rapidly in different research fields dealing with, e.g., the cryosphere, forests, agriculture, and urban areas. However, no systematic exploration has been attempted of the specific advantages and synergies of the latest generation of earth observation systems to study land surface processes.
This Special Issue invites contributions describing applications of new remote sensing technologies to observe and model land surface processes. In particular, but not exclusively, manuscripts are encouraged addressing the following topics:
- Land surface temperature retrieval and surface flux parameterization based on remote sensing of complex heterogeneous surfaces, e.g., urban areas and 3D vegetation canopies;
- LiDAR to map land surface properties, such as aerodynamic roughness;
- Remote sensing of the terrestrial carbon cycle in different biomes;
- Remote sensing of glaciers and high-elevation water cycles;
- Assimilation of remote sensing data in numerical models of land surface process.
Prof. Dr. Massimo Menenti
Dr. Jiyue Zhu
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.
- multispectral, hyperspectral, and LiDAR sensors
- active and passive microwave sensors
- space-borne, airborne, and UAV platforms
- proximal sensing
- robotic manned and unmanned systems
- data processing techniques
- big data
- decision support system
- machine learning
- downscaling and upscaling techniques