Volume 35, Issue 2, January 2022, Pages 268–281
Abdelatif Rajji1, Abdessamad Najine2, Amina WAFIK3, and Amroumoussa Benmoussa4
1 Sultan Moulay Slimane University, Department of Earth Science, Faculty of Science and Techniques, Beni Mellal, Morocco
2 Département des Ressources Naturelles, Environnement et Santé, Université Sultan Moulay Slimane, Faculté des Sciences et Techniques, Béni Mellal, Morocco
3 Départment de Géologie, Université Cadi Ayyad, Faculté des sciences semlalia, laboratoire dynamique de la lithosphère et genèse des ressources minérales et Énergétiques, Marrakech, Morocco
4 Sultan Moulay Slimane University, Department of Earth Science, Faculty of Science and Techniques, Beni Mellal, Morocco
Original language: English
Copyright © 2022 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents a new automated method for the detection and determination of building heights using their cast shadows. The approach consists in applying image processing using PCA and segmentation for the detection and recognition of buildings and their shadows. The height of the buildings is deduced by knowing the length of their shadow projected on the ground, the position (azimuth and zenith) of the sun and the sensor at the time of acquisition. These shadow analyses were carried out on a free satellite image from Google Earth. The results of the height calculations are used for the three-dimensional modelling of the buildings.The 3D models produced can be used for strategic decisions in the professional field and for urban monitoring and surveillance, as well as for various research studies on the relationship between building heights and natural and man-made phenomena: energy consumption and land subsidence. Our method, which requires a good precision of the geometric characteristics of the proposed remotely sensed data, has outperformed the majority of existing research as an automated approach to exploiting the shadows of several buildings in a single satellite image and their 3D reconstruction.
Author Keywords: Buildings, remote sensing, urban planning, shadow, Google Earth, high resolution satellite image.
Abdelatif Rajji1, Abdessamad Najine2, Amina WAFIK3, and Amroumoussa Benmoussa4
1 Sultan Moulay Slimane University, Department of Earth Science, Faculty of Science and Techniques, Beni Mellal, Morocco
2 Département des Ressources Naturelles, Environnement et Santé, Université Sultan Moulay Slimane, Faculté des Sciences et Techniques, Béni Mellal, Morocco
3 Départment de Géologie, Université Cadi Ayyad, Faculté des sciences semlalia, laboratoire dynamique de la lithosphère et genèse des ressources minérales et Énergétiques, Marrakech, Morocco
4 Sultan Moulay Slimane University, Department of Earth Science, Faculty of Science and Techniques, Beni Mellal, Morocco
Original language: English
Copyright © 2022 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents a new automated method for the detection and determination of building heights using their cast shadows. The approach consists in applying image processing using PCA and segmentation for the detection and recognition of buildings and their shadows. The height of the buildings is deduced by knowing the length of their shadow projected on the ground, the position (azimuth and zenith) of the sun and the sensor at the time of acquisition. These shadow analyses were carried out on a free satellite image from Google Earth. The results of the height calculations are used for the three-dimensional modelling of the buildings.The 3D models produced can be used for strategic decisions in the professional field and for urban monitoring and surveillance, as well as for various research studies on the relationship between building heights and natural and man-made phenomena: energy consumption and land subsidence. Our method, which requires a good precision of the geometric characteristics of the proposed remotely sensed data, has outperformed the majority of existing research as an automated approach to exploiting the shadows of several buildings in a single satellite image and their 3D reconstruction.
Author Keywords: Buildings, remote sensing, urban planning, shadow, Google Earth, high resolution satellite image.
How to Cite this Article
Abdelatif Rajji, Abdessamad Najine, Amina WAFIK, and Amroumoussa Benmoussa, “Building height estimation from high resolution satellite images,” International Journal of Innovation and Applied Studies, vol. 35, no. 2, pp. 268–281, January 2022.
