Optimizing the Usages of High-Spatial Resolution Remote Sensing Data: From Precision Resources Inventory to Operational Forestry
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: closed (20 January 2022) | Viewed by 38867
Special Issue Editors
Interests: remote sensing; laser scanning; precision forestry; forest management; forest health
Special Issues, Collections and Topics in MDPI journals
2. Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
Interests: ecosystem monitoring; vegetation health; time series remote sensing; LiDAR
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
High-spatial resolution remote sensing embraces a broad range of data, including airborne, mobile, and terrestrial laser scanning, aerial imagery, unmanned aerial vehicles (UAV), airborne synthetic aperture radar (SAR), and aerial/terrestrial spectroscopy, which, in turn, entail development and adoption of appropriate methodological approaches. All in all, the bundle of those data and methods, together with relevant sampling designs and field surveys for small-scale domains, form the framework for so-called “precision forestry”, with the main objective to maximize information extraction and analysis, mostly based on individual objects in forest ecosystems, for research, monitoring, and management purposes. Nevertheless, the majority of practical applications and monitoring programs entail medium- to large-scale information, mostly on levels of sample plot, parcel or other management units on regular repetition rates. In the context of remote sensing, this would mean shifting, but not necessarily downgrading, from smaller, but high-precision domain (single objects and individuals) to more generalized (pixel or segment) spatial domains while not notably compensating information accuracy. The main questions around this include those concerning:
- The spatial extrapolation methods, sampling design, and error propagation studies;
- Multidimensional, multiscale, multilevel, and multitemporal RS, especially LIDAR and UAV data analysis for forest management and monitoring purposes;
- Implementation of RS, especially LIDAR and UAV-based products in precision forestry.
In this Special Issue of Remote Sensing, we will pursue these and other related issues by hosting contributions presenting state-of-the-art data and methods with a special focus on the applications of remotely-sensed methods in precision and operational forestry. Thus, we invite all colleagues from different parts of the world to contribute to this Special Issue by submitting high-quality relevant works. We particularly welcome submissions in which uncommon methodical approaches have been developed and results were implemented in practical forest management at various scales. This call is also possibly open to communications, meta-analyses, and reviews, provided they are relevant and the detailed structure in which transfer from RS data analysis to operational precision forestry is addressed.
PD Dr. Hooman Latifi
Prof. Krzysztof Stereńczak
Guest Editors
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Keywords
- Precision forestry
- Operational forestry
- High-spatial resolution data
- Multitemporal data
- Sampling strategy
- Error prediction and propagation
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