Three-Dimensional Polygonal Building Model Estimation From Single Satellite Images

2012 ◽  
Vol 50 (6) ◽  
pp. 2254-2272 ◽  
Author(s):  
Mohammad Izadi ◽  
Parvaneh Saeedi
Keyword(s):  
Satellite Images ◽  
Three Dimensional ◽  
Model Estimation ◽  
Building Model

scholarly journals Simulating rainfall, water evaporation and groundwater flow in three-dimensional satellite images with cellular automata

2016 ◽  
Vol 67 ◽  
pp. 89-99 ◽  
Author(s):  
Moisés Espínola ◽  
José A. Piedra-Fernández ◽  
Rosa Ayala ◽  
Luis Iribarne ◽  
Saturnino Leguizamón ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Groundwater Flow ◽  
Satellite Images ◽  
Three Dimensional ◽  
Water Evaporation

GIS three-dimensional Modelling with geo-informatics techniques

2017 ◽  
Author(s):  
Katarzyna Bobkowska ◽  
Jakub Szulwic ◽  
Paweł Tysiac ◽  
Patryk Ziółkowski
Keyword(s):  
Data Model ◽  
Point Cloud ◽  
Satellite Images ◽  
Three Dimensional ◽  
Great Promise ◽  
Gis Model ◽  
High Resolution Satellite Images ◽  
Potential Applications ◽  
The Subject ◽  
Three Dimensional Models

The integration issue of virtual models and geo-referenced database have a very broad spectrum of potential applications. Before the integration issue was on the cusp, it was quite problematic to combine three-dimensional models with the geo-referenced database. An integrated database contains a variety of data including such as object orientated data model and raster data. Within this paper, authors present an integration process aiming to make real virtual GIS database which includes the creation of structures, such as bridges, buildings, roads and terrain formations. To create a three-dimensional GIS model high-resolution satellite images/point cloud has been used. For 3D modelling and reconstruction purposes, The Blender program has been used since the software provides with quick workflow and userfriendly interface. As a result of this study authors concede that integrated techniques for three-dimensional GIS databases allow conducting easy as well as sophisticated operation in an efficient and non-time consuming way. The subject holds great promise for a future, current challenges focusing on new approaches for conjectures of spatial objects that will be used to boost the capabilities for automatic visualization.

scholarly journals Bathymetry Time Series Using High Spatial Resolution Satellite Images

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 531 ◽  
Author(s):  
Manuel Erena ◽  
José A. Domínguez ◽  
Joaquín F. Atenza ◽  
Sandra García-Galiano ◽  
Juan Soria ◽  
...  
Keyword(s):  
High Precision ◽  
Spatial Resolution ◽  
Satellite Images ◽  
Environmental Variability ◽  
High Spatial Resolution ◽  
Numerical Models ◽  
Three Dimensional ◽  
Satellite System ◽  
Precision Data ◽  
Mar Menor

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and water ecosystem complexity.

scholarly journals Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images

2021 ◽  
Vol 13 (17) ◽  
pp. 3535
Author(s):  
Zhongli Fan ◽  
Li Zhang ◽  
Yuxuan Liu ◽  
Qingdong Wang ◽  
Sisi Zlatanova
Keyword(s):  
Satellite Imagery ◽  
Image Matching ◽  
Satellite Images ◽  
Three Dimensional ◽  
Phase Correlation ◽  
Feature Descriptor ◽  
Matching Method ◽  
Reference Images ◽  
Sar Data ◽  
Optical Satellite Images

Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.

scholarly journals Pemetaan Bangunan Tiga Dimensi Untuk Pemodelan Jalur Evakuasi Darurat

2017 ◽  
Author(s):  
debby nurliza ulhaq ◽  
Budhy Soeksmantono ◽  
Ketut Wikantika
Keyword(s):  
Shortest Paths ◽  
Three Dimensional ◽  
Emergency Evacuation ◽  
Dijkstra’S Algorithm ◽  
Related Data ◽  
Building Model ◽  
Dijkstra's Algorithm ◽  
3D Building Model ◽  
Road Data ◽  
Evacuation Route

AbstrakMitigasi bencana merupakan salah satu hal penting yang harus dipertimbangkan terutama dalam konstruksi bangunan karena hal tersebut cukup rumit terlebih apabila dikaitkan dengan fakta tidak adanya informasi yang dapat digunakan untuk orang-orang menyelamatkan diri mereka sendiri. Maka dari itu, makalah ilmiah ini memperkenalkan mengenai network analysist untuk rute evakuasi darurat yang bertujuan untuk mencari rute terbaik menuju tempat aman seperti titik berkumpul tergantung pada situasi terkini. Pembuatan keputusan berdasarkan rute yang tepat akan dipilih berdasarkan kategori usia korban dan kondisi saat bencana terjadi, sehingga dapat mengurangi dampak buruk yang akan muncul. Algoritma Dijkstra menunjukan suatu algoritma perncarian rute terpendek antara gedung dan titik berkumpul dengan menghubungkan keduanya melalui data jalan. Model rute evakuasi ini dibentuk dengan menggunakan kombinasi antara model bangunan tiga dimensi yang dibangun dari data LiDAR, orthophoto, dan data lainnya yang berkaitan dengan pemodelan. Bangunan tiga dimensi dapat digunakan dalam manajemen bencana dan respon darurat karena dapat menyediakan informasi penting seperti lokasi bangunan. Evaluasi dari model yang diajukan meningkatkan kemampuan penyelamatan diri sendiri yang mengarah pada berkurangnya dampak buruk yang akan terjadi.Kata kunci: Evakuasi Darurat, Algoritma Dijkstra, LiDAR, pemodelan bangunan 3D AbstractMitigation is an important thing to be considered especially in building construction because it is quite complicated due to the fact that much of the information is unavailable for people to rescue themselves. Hence, this paper introduces about network analysis for evacuation emergency route which aims at finding the best route to the secured place such as the closest assembly point depends on the situation. Thus, decision making regarding the proper route to be chosen depends of the victim age category and current condition to minimize impact that can be generated. Dijkstra’s Algorithm is presented an algorithm for finding the shortest paths between building and assembly point by linking them through road data. This emergency evacuation route model is constructed by combining with three dimensional building model which constructed by using LiDAR data, orthophoto, and the other related data. Three dimensional geo data can be used in disaster management and emergency response because they may provide valuable information such as location of the building. The evaluation of the proposed model for a case study building improve self-sustaining which lead to chances of less adverse effects can appear.Keywords: Emergency Evacuation, Dijkstra’s Algorithm, LiDAR, 3D building model

scholarly journals How to circumvent the limitations of open source software and orthorectify how (or better) than with commercial software

2020 ◽  
Author(s):  
Valerio Baiocchi ◽  
Roberta Onori ◽  
Felicia Monti ◽  
Francesca Giannone
Keyword(s):  
Open Source ◽  
Satellite Images ◽  
Research Work ◽  
Three Dimensional ◽  
Commercial Software ◽  
Whole Process ◽  
High Resolution Satellite Images ◽  
Open Source Gis ◽  
Gis Software ◽  
Better Than

<p>High and very high resolution satellite images are now an irreplaceable resource for earth observation in general and for the extraction of hydrogeological information in particular. In order to use them correctly and compare them with previous surveys and maps, they must be treated geometrically to remove the distortions introduced by the acquisition process. Orthorectification is not a simple georeferencing because the process must take into account the three-dimensional acquisition geometry of the sensor. For this reason orthorectification must be performed within specific commercial software with additional costs compared to image acquisition which, in some cases, is currently free of charge.<br>Some orthorectification algorithms, mainly based on the RPC approach, are available in open source GIS software such as QGIS. OTB (Orpheus toolbox) for QGIS contains some of these algorithms but its interfaces are not clear and there are some incomprehensible limitations such as the impossibility to input three-dimensional ground control points (GCPs). This severely limits the final achievable accuracy because it does not allow to correctly estimate the influence of different ground morphologies on the acquisition geometry. To get around these limitations you can make a "pseudo DEM" and other expedients to complete the whole process obtaining absolute results comparable if not better than those of commercial software.<br>The proposed procedure may not be the fastest but it can be a valid alternative for those who use satellite images as a tool in their research work.</p><p> </p>

scholarly journals 3D SURFACE RECONSTRUCTION FROM MULTI-DATE SATELLITE IMAGES

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 313-320
Author(s):  
S. Bullinger ◽  
C. Bodensteiner ◽  
M. Arens
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Stereo Matching ◽  
State Of The Art ◽  
Satellite Image ◽  
Three Dimensional ◽  
Point Clouds ◽  
Reconstruction Algorithms ◽  
Depth Maps ◽  
Median Error

Abstract. The reconstruction of accurate three-dimensional environment models is one of the most fundamental goals in the field of photogrammetry. Since satellite images provide suitable properties for obtaining large-scale environment reconstructions, there exist a variety of Stereo Matching based methods to reconstruct point clouds for satellite image pairs. Recently, a Structure from Motion (SfM) based approach has been proposed, which allows to reconstruct point clouds from multiple satellite images. In this work, we propose an extension of this SfM based pipeline that allows us to reconstruct not only point clouds but watertight meshes including texture information. We provide a detailed description of several steps that are mandatory to exploit state-of-the-art mesh reconstruction algorithms in the context of satellite imagery. This includes a decomposition of finite projective camera calibration matrices, a skew correction of corresponding depth maps and input images as well as the recovery of real-world depth maps from reparameterized depth values. The paper presents an extensive quantitative evaluation on multi-date satellite images demonstrating that the proposed pipeline combined with current meshing algorithms outperforms state-of-the-art point cloud reconstruction algorithms in terms of completeness and median error. We make the source code of our pipeline publicly available.

Use of topographic LiDAR point clouds for building reconstruction

2021 ◽  
Author(s):  
Yipeng Yuan
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Point Clouds ◽  
Building Roof ◽  
Building Model ◽  
Building Models ◽  
Urban Models ◽  
Elevation Data ◽  
3D Building Model ◽  
Building Reconstruction

Demand for three-dimensional (3D) urban models keeps growing in various civil and military applications. Topographic LiDAR systems are capable of acquiring elevation data directly over terrain features. However, the task of creating a large-scale virtual environment still remains a time-consuming and manual work. In this thesis a method for 3D building reconstruction, consisting of building roof detection, roof outline extraction and regularization, and 3D building model generation, directly from LiDAR point clouds is developed. In the proposed approach, a new algorithm called Gaussian Markov Random Field (GMRF) and Markov Chain Monte Carlo (MCMC) is used to segment point clouds for building roof detection. The modified convex hull (MCH) algorithm is used for the extraction of roof outlines followed by the regularization of the extracted outlines using the modified hierarchical regularization algorithm. Finally, 3D building models are generated in an ArcGIS environment. The results obtained demonstrate the effectiveness and satisfactory accuracy of the developed method.

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