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Remote Sensing
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Remote Sensing of Desert Landscapes to Monitor Impacts of Renewable...
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Remote Sensing of Desert Landscapes to Monitor Impacts of Renewable Energy Developments

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

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 11788

Special Issue Editors

Dr. Ioannis Gitas

E-Mail Website
Guest Editor
Lab of Forest Management and Remote Sensing, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: forest fires; land-use/land-cover mapping; pre-fire planning and post-fire assessment; remote sensing; GIS; forest management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Arnon Karnieli

E-Mail Website
Guest Editor
The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker 8499000, Israel
Interests: remote sensing; geographic information systems; climate change; precision agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern energy demands have led to the recent development of large renewable energy projects in several desert regions of the world. The environmental conditions of low vegetation cover, high solar radiance, and sustained winds commonly make solar and wind energy attractive development options in these areas. However, land cover change from renewable energy development is receiving increasing attention due to potential impacts on the conservation of protected areas, endangered species, and air quality. This Special Issue will solicit papers that focus on remote sensing as a tool for change detection in desert regions that can jointly offer local, government, and industrial organizations information on key environmental conditions across arid landscapes

Prof. Ioannis Gitas
Prof. Arnon Karnieli
Guest Editors

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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

20 pages, 13144 KiB  
Article
Object-Based Image Procedures for Assessing the Solar Energy Photovoltaic Potential of Heterogeneous Rooftops Using Airborne LiDAR and Orthophoto
by Arti Tiwari, Isaac A. Meir and Arnon Karnieli
Remote Sens. 2020, 12(2), 223; https://doi.org/10.3390/rs12020223 - 9 Jan 2020
Cited by 29 | Viewed by 6014
Abstract
Available renewable energy resources play a vital role in fulfilling the energy demands of the increasing global population. To create a sustainable urban environment with the use of renewable energy in human habitats, a precise estimation of solar energy on building roofs is [...] Read more.
Available renewable energy resources play a vital role in fulfilling the energy demands of the increasing global population. To create a sustainable urban environment with the use of renewable energy in human habitats, a precise estimation of solar energy on building roofs is essential. The primary goal of this paper is to develop a procedure for measuring the rooftop solar energy photovoltaic potential over a heterogeneous urban environment that allows the estimation of solar energy yields on flat and pitched roof surfaces at different slopes and in different directions, along with multi-segment roofs on a single building. Because of the complex geometry of roofs, very high-resolution data, such as ortho-rectified aerial photography (orthophotos), and LiDAR data have been used to generate a new object-based algorithm to classify buildings. An overall accuracy index and a Kappa index of agreement (KIA) of 97.39% and 0.95, respectively, were achieved. The paper also develops a new model to create an aspect-slope map, which combines slope orientation with the gradient of the slope and uses it to demonstrate the collective results. This study allows the assessment of solar energy yields through defining solar irradiances in units of pixels over a specific time period. It might be beneficial in terms of more efficient measurements for solar panel installations and more accurate calculations of solar radiation for residents and commercial energy investors. Full article
(This article belongs to the Special Issue Remote Sensing of Desert Landscapes to Monitor Impacts of Renewable Energy Developments)
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25 pages, 5483 KiB  
Article
Forward Simulation of Multi-Frequency Microwave Brightness Temperature over Desert Soils in Kuwait and Comparison with Satellite Observations
by Hala K. AlJassar, Marouane Temimi, Dara Entekhabi, Peter Petrov, Hussain AlSarraf, Panagiotis Kokkalis and Nair Roshni
Remote Sens. 2019, 11(14), 1647; https://doi.org/10.3390/rs11141647 - 11 Jul 2019
Cited by 8 | Viewed by 3832
Abstract
In this study, we address the variations of bare soil surface microwave brightness temperatures and evaluate the performance of a dielectric mixing model over the desert of Kuwait. We use data collected in a field survey and data obtained from NASA Soil Moisture [...] Read more.
In this study, we address the variations of bare soil surface microwave brightness temperatures and evaluate the performance of a dielectric mixing model over the desert of Kuwait. We use data collected in a field survey and data obtained from NASA Soil Moisture Active Passive (SMAP), European Space Agency Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and Special Sensor Microwave/Imager (SSM/I). In situ measurements are collected during two intensive field campaigns over bare, flat, and homogeneous soil terrains in the desert of Kuwait. Despite the prevailing dry desert environment, a large range of soil moisture values was monitored, due to precedent rain events and subsequent dry down. The mean relative difference (MRD) is within the range of ±0.005 m3·m−3 during the two sampling days. This reflects consistency of soil moisture in space and time. As predicted by the model, the higher frequency channels (18 to 19 GHz) demonstrate reduced sensitivity to surface soil moisture even in the absence of vegetation, topography and heterogeneity. In the 6.9 to 10.7 GHz range, only the horizontal polarization is sensitive to surface soil moisture. Instead, at the frequency of 1.4 GHz, both polarizations are sensitive to soil moisture and span a large dynamic range as predicted by the model. The error statistics of the difference between observed satellite brightness temperature (Tb) (excluding SMOS data due to radio frequency interference, RFI) and simulated brightness temperatures (Tbs) show values of Root Mean Square Deviation (RMSD) of 5.05 K at vertical polarization and 4.88 K at horizontal polarization. Such error could be due to the performance of the dielectric mixing model, soil moisture sampling depth and the impact of parametrization of effective temperature and roughness. Full article
(This article belongs to the Special Issue Remote Sensing of Desert Landscapes to Monitor Impacts of Renewable Energy Developments)
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