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Title:GPU-based solar irradiance estimation over digital surface models using structurally lossless viewshed compression
Authors:ID Lukač, Niko (Author)
ID Žalik, Borut (Author)
Files:URL https://www.mdpi.com/2072-4292/18/17/3044
 
.pdf remotesensing-18-03044.pdf (14,44 MB)
MD5: DCE933B4251F4D43226203826F0F2EEE
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:High-resolution solar irradiance modelling over large 3D geospatial data is computationally demanding, and accounting for surface inter-reflection makes it even so. For computational efficiency it requires storing for every part of the surface, explicit knowledge of the other surfaces visible from it (its viewshed). The storage of each surface’s viewshed grows with both the dataset size and the angular resolution, and quickly becomes the dominant mem ory bottleneck. This paper presents a novel Graphics Processing Unit (GPU)-accelerated method for estimating solar potential over Digital Surface Models (DSMs) that model direct, diffuse and reflective irradiances. It keeps the viewshed information compact through a novel structurally lossless compression, i.e., a domain-specific encoding of remote sensing derived visibility data that preserves exactly the visibility structure consumed by the radiative model, rather than a general-purpose integer coder. An ablation analysis over eight synthetic DSMs showed that the best compression scheme reached a compression ratio (CR) of up to ≈3.3, exceeding the general-purpose GPU baselines Binary Packing 32 and Elias-Fano on every dataset. On the largest DSM, whose 29.6GB uncompressed viewshed exceeds the 24GB device memory, compression kept the data resident and re duced the runtime from 6.7h to 0.5h. Finally, the proposed method was applied to LiDAR (Light Detection and Ranging)-derived DSMs for four distinct locations, with the results demonstrating its high applicability.
Keywords:solar irradiance, GPGPU, viewshed, RLE, structurally lossless compression
Publication status:Published
Publication version:Version of Record
Submitted for review:18.07.2026
Article acceptance date:03.09.2026
Publication date:06.09.2026
Publisher:MDPI
Year of publishing:2026
Number of pages:24 str.
Numbering:vol. 18, no. 17, [article no.] 3044
PID:20.500.12556/DKUM-100385 New window
UDC:004.9
ISSN on article:2072-4292
COBISS.SI-ID:290297859 New window
DOI:10.3390/rs18173044 New window
Copyright:© 2026 by the authors
Publication date in DKUM:16.09.2026
Views:92
Downloads:12
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Remote sensing
Shortened title:Remote sens.
Publisher:MDPI
ISSN:2072-4292
COBISS.SI-ID:32345133 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J7-50095-2023
Name:Prostorsko-časovni algoritmi za ocenitev mikroklimatskih parametrov

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0041-2020
Name:Računalniški sistemi, metodologije in inteligentne storitve

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:sončno obsevanje, vidno polje, strukturna kompresija brez izgub


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