scholarly journals Greenhouse Detection from Color Infrared Aerial Image and Digital Surface Model

2019 ◽  
Author(s):  
Dilek Koc-San ◽  
Salih Celik
Keyword(s):  
Aerial Image ◽  
Surface Model ◽  
Digital Surface Model

scholarly journals AUTOMATIC RECONSTRUCTION OF ROOF MODELS FROM BUILDING OUTLINES AND AERIAL IMAGE DATA

2019 ◽  
Vol 59 (5) ◽  
pp. 448-457
Author(s):  
Vojtěch Hron ◽  
Lena Halounová
Keyword(s):  
Image Data ◽  
Aerial Survey ◽  
Aerial Image ◽  
Surface Model ◽  
Digital Surface Model ◽  
Multiple Datasets ◽  
Building Models ◽  
The Creation ◽  
Near Future ◽  
Different Levels

The knowledge of roof shapes is essential for the creation of 3D building models. Many experts and researchers use 3D building models for specialized tasks, such as creating noise maps, estimating the solar potential of roof structures, and planning new wireless infrastructures. Our aim is to introduce a technique for automating the creation of topologically correct roof building models using outlines and aerial image data. In this study, we used building footprints and vertical aerial survey photographs. Aerial survey photographs enabled us to produce an orthophoto and a digital surface model of the analysed area. The developed technique made it possible to detect roof edges from the orthophoto and to categorize the edges using spatial relationships and height information derived from the digital surface model. This method allows buildings with complicated shapes to be decomposed into simple parts that can be processed separately. In our study, a roof type and model were determined for each building part and tested with multiple datasets with different levels of quality. Excellent results were achieved for simple and medium complex roofs. Results for very complex roofs were unsatisfactory. For such structures, we propose using multitemporal images because these can lead to significant improvements and a better roof edge detection. The method used in this study was shared with the Czech national mapping agency and could be used for the creation of new 3D modelling products in the near future.

scholarly journals Digital surface model based on aerial image stereo pairs for 3D building

2014 ◽  
Vol 3 (1) ◽  
pp. 119-126 ◽  
Author(s):  
Abdelkader El Garouani ◽  
Abdalla Alobeid ◽  
Said El Garouani
Keyword(s):  
Aerial Image ◽  
Surface Model ◽  
Digital Surface Model ◽  
Model Based

EVALUASI KETELITIAN HORIZONTAL DARI CITRA TEGAK SATELIT RESOLUSI SANGAT TINGGI MENGGUNAKAN SRTM DAN TERRASAR-X UNTUK PEMETAAN SKALA BESAR

2018 ◽  
Vol 2 ◽  
pp. 535
Author(s):  
Maundri Prihanggo
Keyword(s):  
Control Point ◽  
Ground Control ◽  
Surface Model ◽  
Digital Surface Model ◽  
Check Point ◽  
Ground Control Point

<p>Saat ini, citra satelit resolusi sangat tinggi digunakan dalam berbagai macam aplikasi, terutama pemetaan skala besar. Sebelum dapat digunakan, citra satelit tersebut harus diorthorektifikasi terlebih dahulu. Data <em>Digital Surface Model </em>(DSM) dan <em>Ground Control Point</em> (GCP) adalah dua data utama yang diperlukan saat melakukan orthorektifikasi. Perbedaan data DSM yang digunakan akan menghasilkan perbedaan nilai ketelitian horizontal pada kedua citra tegak hasil orthorektifikasi. Pada penelitian ini digunakan dua jenis DSM yaitu SRTM dan Terrasar-X. Ketelitian vertikal dari SRTM adalah 90 m sedangkan ketelitian vertikal dari Terrasar-X adalah 12,5 m. Penelitian ini berlokasi di Wilayah Buli, Kabupaten Halmahera Timur, Provinsi Maluku. Terdapat tiga sensor citra satelit yang digunakan yaitu Pleiades, Quickbird dan Worldview-2 yang digunakan pada lokasi penelitian. Total GCP yang digunakan adalah 33 titik, tiap titiknya diukur dengan melakukan pengamatan geodetik dan memiliki ketelitian horizontal ≤15 cm dan ketelitian vertikal ≤30 cm. Ketelitian horizontal dari citra tegak satelit resolusi sangat tinggi diperoleh dengan melakukan uji terhadap Independent Check Point (ICP). Total ICP yang digunakan adalah 12 titik, tiap titik ICP diukur dengan metode dan standar yang sama dengan titik GCP. Ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data SRTM adalah 18,856 m sedangkan ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data Terrasar-X adalah 2.168 m . Hasil dari penelitian ini membuktikan bahwa ketelitian vertikal data DSM yang digunakan memberikan pengaruh pada citra tegak satelit hasil orthorektifikasi tersebut. Mengacu pada Peraturan Kepala BIG nomor 15 tahun 2014, citra tegak satelit hasil orthorektifikasi menggunakan data Terrasar-X sebagai DSM memenuhi ketelitian horizontal peta dasar kelas 3 skala 1:5.000 sedangkan citra tegak satelit hasil orthorektifikasi menggunakan data SRTM sebagai DSM tidak dapat memenuhi ketelitian horizontal peta dasar skala besar.</p><p><strong>Kata kunci:</strong> orthorektifikasi, DSM, ketelitian horizontal</p>

Measuring historical flooding and erosion in Goodnews Bay using datasets commonly available to Alaska communities

Shore & Beach ◽  
2020 ◽  
pp. 3-13
Author(s):  
Richard Buzard ◽  
Christopher Maio ◽  
David Verbyla ◽  
Nicole Kinsman ◽  
Jacquelyn Overbeck
Keyword(s):  
Rural Communities ◽  
Coastal Communities ◽  
Aerial Imagery ◽  
Coastal Hazards ◽  
Surface Model ◽  
Digital Surface Model ◽  
Wave Impact ◽  
Information Gap ◽  
Quantitative Analyses ◽  
Gnss Measurements

Coastal hazards are of increasing concern to many of Alaska’s rural communities, yet quantitative assessments remain absent over much of the coast. To demonstrate how to fill this critical information gap, an erosion and flood analysis was conducted for Goodnews Bay using an assortment of datasets that are commonly available to Alaska coastal communities. Measurements made from orthorectified aerial imagery from 1957 to 2016 show the shoreline eroded 0 to 15.6 m at a rate that posed no immediate risk to current infrastructure. Storm surge flood risk was assessed using a combination of written accounts, photographs of storm impacts, GNSS measurements, hindcast weather models, and a digital surface model. Eight past storms caused minor to major flooding. Wave impact hour calculations showed that the record storm in 2011 doubled the typical annual wave impact hours. Areas at risk of erosion and flooding in Goodnews Bay were identified using publicly available datasets common to Alaska coastal communities; this work demonstrates that the data and tools exist to perform quantitative analyses of coastal hazards across Alaska.

scholarly journals Automated Generation of Digital Terrain Model using Point Clouds of Digital Surface Model in Forest Area

2011 ◽  
Vol 3 (5) ◽  
pp. 845-858 ◽  
Author(s):  
Kande R.M.U. Bandara ◽  
Lal Samarakoon ◽  
Rajendra P. Shrestha ◽  
Yoshikazu Kamiya
Keyword(s):  
Digital Terrain Model ◽  
Point Clouds ◽  
Forest Area ◽  
Surface Model ◽  
Digital Surface Model ◽  
Automated Generation ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals UNDERWATER PHOTOGRAMMETRY DIGITAL SURFACE MODEL (DSM) OF THE SUBMERGED SITE OF THE ANCIENT LIGHTHOUSE NEAR QAITBAY FORT IN ALEXANDRIA, EGYPT

2019 ◽  
Vol XLII-2/W10 ◽  
pp. 1-8 ◽  
Author(s):  
M. Abdelaziz ◽  
M. Elsayed
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Data Gathering ◽  
Archaeological Site ◽  
3D Models ◽  
Surface Model ◽  
Digital Surface Model ◽  
Architectural Elements ◽  
3D Photogrammetry ◽  
First Time

<p><strong>Abstract.</strong> Underwater photogrammetry in archaeology in Egypt is a completely new experience applied for the first time on the submerged archaeological site of the lighthouse of Alexandria situated on the eastern extremity of the ancient island of Pharos at the foot of Qaitbay Fort at a depth of 2 to 9 metres. In 2009/2010, the CEAlex launched a 3D photogrammetry data-gathering programme for the virtual reassembly of broken artefacts. In 2013 and the beginning of 2014, with the support of the Honor Frost Foundation, methods were developed and refined to acquire manual photographic data of the entire underwater site of Qaitbay using a DSLR camera, simple and low cost materials to obtain a digital surface model (DSM) of the submerged site of the lighthouse, and also to create 3D models of the objects themselves, such as statues, bases of statues and architectural elements. In this paper we present the methodology used for underwater data acquisition, data processing and modelling in order to generate a DSM of the submerged site of Alexandria’s ancient lighthouse. Until 2016, only about 7200&amp;thinsp;m<sup>2</sup> of the submerged site, which exceeds more than 13000&amp;thinsp;m<sup>2</sup>, was covered. One of our main objectives in this project is to georeference the site since this would allow for a very precise 3D model and for correcting the orientation of the site as regards the real-world space.</p>

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