An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach
Urbanization is leading us to a more chaotic state where healthy living becomes a prime concern. The high-rise buildings influence the urban setting with a high shadow rate on surroundings that can have no positive impact on the general neighborhood. Nevertheless, shadows are the main factor of defe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/9/583 |
| _version_ | 1797518964169900032 |
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| author | Sukriti Bhattacharya Christian Braun Ulrich Leopold |
| author_facet | Sukriti Bhattacharya Christian Braun Ulrich Leopold |
| author_sort | Sukriti Bhattacharya |
| collection | DOAJ |
| description | Urbanization is leading us to a more chaotic state where healthy living becomes a prime concern. The high-rise buildings influence the urban setting with a high shadow rate on surroundings that can have no positive impact on the general neighborhood. Nevertheless, shadows are the main factor of defeatist virtual settings, they are expensive to render in real-time. This paper investigates how the amount of sunlight varies by season and how seasons can indicate the time of year to understand how shadows vary in length at different times of the day and how they change over the seasons. We propose a novel efficient (fast and scalable) algorithm to calculate a 2.5D cast-shadow map from a given LiDAR-derived Digital Surface Model (DSM). We present a proof-of-concept demonstration to examine the technical practicability of the introduced algorithm. Tensor-based techniques such as singular value decomposition, tensor unfolding are examined and deployed to represent the multidimensional data. The proposed method exploits horizon mapping ideas and extends the method to a modern graphics algorithm (Bresenham’s line drawing algorithm) to account for the DSM’s underlying surface geometry. A proof-of-concept is developed utilizing Python’s TensorFlow library, exploring data flow graphs and the tensor data structure. The heavy computer graphics algorithm used in this paper is parallelized using PySpark. Results explicate significant enhancements in overall performance while preserving accuracy at negligible variations. |
| first_indexed | 2024-03-10T07:36:42Z |
| format | Article |
| id | doaj.art-5ddf7c411f6b4101a9ea6a71e775ffe5 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T07:36:42Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-5ddf7c411f6b4101a9ea6a71e775ffe52023-11-22T13:24:42ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-08-0110958310.3390/ijgi10090583An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based ApproachSukriti Bhattacharya0Christian Braun1Ulrich Leopold2Department for IT for Innovative Services, Luxembourg Institute of Science and Technology (LIST), L-4362 Esch-sur-Alzette, LuxembourgDepartment for Environmental Research and Innovation, Luxembourg Institute of Science and Technology (LIST), L-4362 Esch-sur-Alzette, LuxembourgDepartment for Environmental Research and Innovation, Luxembourg Institute of Science and Technology (LIST), L-4362 Esch-sur-Alzette, LuxembourgUrbanization is leading us to a more chaotic state where healthy living becomes a prime concern. The high-rise buildings influence the urban setting with a high shadow rate on surroundings that can have no positive impact on the general neighborhood. Nevertheless, shadows are the main factor of defeatist virtual settings, they are expensive to render in real-time. This paper investigates how the amount of sunlight varies by season and how seasons can indicate the time of year to understand how shadows vary in length at different times of the day and how they change over the seasons. We propose a novel efficient (fast and scalable) algorithm to calculate a 2.5D cast-shadow map from a given LiDAR-derived Digital Surface Model (DSM). We present a proof-of-concept demonstration to examine the technical practicability of the introduced algorithm. Tensor-based techniques such as singular value decomposition, tensor unfolding are examined and deployed to represent the multidimensional data. The proposed method exploits horizon mapping ideas and extends the method to a modern graphics algorithm (Bresenham’s line drawing algorithm) to account for the DSM’s underlying surface geometry. A proof-of-concept is developed utilizing Python’s TensorFlow library, exploring data flow graphs and the tensor data structure. The heavy computer graphics algorithm used in this paper is parallelized using PySpark. Results explicate significant enhancements in overall performance while preserving accuracy at negligible variations.https://www.mdpi.com/2220-9964/10/9/583tensorTensorFlowDigital Surface ModelBresenham’s Algorithmcast shadow |
| spellingShingle | Sukriti Bhattacharya Christian Braun Ulrich Leopold An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach ISPRS International Journal of Geo-Information tensor TensorFlow Digital Surface Model Bresenham’s Algorithm cast shadow |
| title | An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach |
| title_full | An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach |
| title_fullStr | An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach |
| title_full_unstemmed | An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach |
| title_short | An Efficient 2.5D Shadow Detection Algorithm for Urban Planning and Design Using a Tensor Based Approach |
| title_sort | efficient 2 5d shadow detection algorithm for urban planning and design using a tensor based approach |
| topic | tensor TensorFlow Digital Surface Model Bresenham’s Algorithm cast shadow |
| url | https://www.mdpi.com/2220-9964/10/9/583 |
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