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Remote Sensing for Sustainable Energy Systems

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 October 2011) | Viewed by 28079

Special Issue Editor


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Guest Editor
Department of Geoinformatics, University of Salzburg, Salzburg, Austria
Interests: terrain analysis; visualization of terrain characteristics; multi-resolution DEMs; terrain-constrained processes; surface feature extraction; DEM-DSM accuracy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The planned issue is centered around an integrated spatial / regional systems perspective of providing energy to society. One key tenet is the view that most renewables in the end are directly or indirectly driven by solar energy. Thus the Earth's surface, as the receiving boundary layer where most energy conversions occur, (co-)defines a region's potential for generating energy. Remote Sensing as the means for assessing and monitoring surface characteristics contributes valuable information towards developing sustainable energy systems.

Papers expected as contributions to this issue include, but are not limited to:

  • (Climatological) energy balance of regions, particularly in urban contexts
  • Assessment of biofuel production potentials (including a critical perspective)
  • Regional logistics of biofuel production
  • Regionalized assessment of energy demand (electrical, thermal)
  • Analysis of solar potential in built-up areas as well as for solar farms
  • Thermal assessment of buildings and built-up areas (potential for savings through isolation)
  • Siting optimization for e.g. wind farms based on land use development
  • Corridor analysis for energy transport (power lines, pipelines)
  • Hydropower potential and risk analysis (terrain modeling)
  • Green house gas emissions and energy production / usage
  • Land use patterns and energy systems
  • Managing conflicts (eg, conservation vs energy production)

Potential authors are encouraged to contact editors with abstracts outlining their proposals for paper submissions. Editors will provide early feedback aiming at making this issue an authoritative and broad source demonstrating the contribution of remote sensing to managing our world's energy needs.

Prof. Dr. Josef Strobl
Guest Editor

Keywords

  • renewable energy potentials
  • solar input on surfaces / digital surface models
  • thermal remote sensing
  • land use and biomass for biofuel production
  • land use and energy needs
  • hydropower potentials
  • corridor analysis for power supply

Published Papers (2 papers)

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1619 KiB  
Article
Inter-Sensor Comparison between THEOS and Landsat 5 TM Data in a Study of Two Crops Related to Biofuel in Thailand
by Naruemon Phongaksorn, Nitin K. Tripathi, Sivanappan Kumar and Peeyush Soni
Remote Sens. 2012, 4(2), 354-376; https://doi.org/10.3390/rs4020354 - 01 Feb 2012
Cited by 9 | Viewed by 8662
Abstract
Knowledge of the spatial distribution of biofuel crops is an important criterion to determine the sustainability of biofuel energy production. Remotely sensed image analysis is a proven and effective tool for describing the spatial distribution of crops using vegetation characteristics. Increases in the [...] Read more.
Knowledge of the spatial distribution of biofuel crops is an important criterion to determine the sustainability of biofuel energy production. Remotely sensed image analysis is a proven and effective tool for describing the spatial distribution of crops using vegetation characteristics. Increases in the number of options and availability of satellite sensors have expanded the horizon of choices of imagery sources for appropriate image acquisitions. The Thailand Earth Observation System (THEOS) satellite is one of the newest satellite sensors. The growing number of satellite sensors warrants their comparative evaluation and the standardization of data obtained from various sensors. This study conducted an inter-sensor comparison of the visible/near-infrared surface reflectance and Normalized Difference Vegetation Index (NDVI) data collected from the Landsat 5 Thematic Mapper (TM) and THEOS. The surface reflectance and the derived NDVI of the sensors were randomly obtained for two biofuel crops, namely, cassava and sugarcane. These crops had low values of visible surface reflectance, which were not significantly (p < 0.05) different. In contrast, the crops had high values of near-infrared surface reflectance that differed significantly (p > 0.05) between the crops. Strong linear relationships between the remote sensing products for the examined sensors were obtained for both cassava and sugarcane. The regression models that were developed can be used to compute the NDVI for THEOS using those determined from Landsat 5 TM and vice versa for the given biofuel crops. Full article
(This article belongs to the Special Issue Remote Sensing for Sustainable Energy Systems)
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1300 KiB  
Article
LIDAR and SODAR Measurements of Wind Speed and Direction in Upland Terrain for Wind Energy Purposes
by Steven Lang and Eamon McKeogh
Remote Sens. 2011, 3(9), 1871-1901; https://doi.org/10.3390/rs3091871 - 25 Aug 2011
Cited by 91 | Viewed by 18577
Abstract
Detailed knowledge of the wind resource is necessary in the developmental and operational stages of a wind farm site. As wind turbines continue to grow in size, masts for mounting cup anemometers—the accepted standard for resource assessment—have necessarily become much taller, and much [...] Read more.
Detailed knowledge of the wind resource is necessary in the developmental and operational stages of a wind farm site. As wind turbines continue to grow in size, masts for mounting cup anemometers—the accepted standard for resource assessment—have necessarily become much taller, and much more expensive. This limitation has driven the commercialization of two remote sensing (RS) tools for the wind energy industry: The LIDAR and the SODAR, Doppler effect instruments using light and sound, respectively. They are ground-based and can work over hundreds of meters, sufficient for the tallest turbines in, or planned for, production. This study compares wind measurements from two commercial RS instruments against an instrumented mast, in upland (semi-complex) terrain typical of where many wind farms are now being installed worldwide. With appropriate filtering, regression analyses suggest a good correlation between the RS instruments and mast instruments: The RS instruments generally recorded lower wind speeds than the cup anemometers, with the LIDAR more accurate and the SODAR more precise. Full article
(This article belongs to the Special Issue Remote Sensing for Sustainable Energy Systems)
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