Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Automatic Water Canal Detection in Multispectral Satellite Images
Date
2013-04-26
Author
Gedik, Ekin
Kahraman, Ersin
Çinar, Umut
Çetin, Yasemin
Halıcı, Uğur
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
158
views
0
downloads
Cite This
In this paper, a method for automatically detecting water regions and classifying water canals containing water in high resolution multispectral satellite images in a rule based manner is proposed. As water canals may be of different lengths and widths, indices employed in the literature and image gradients are used adaptively to classify water regions. The well known spatial properties of water canals are used to determine the water canals among the extracted water regions. The proposed algorithm is tested on high resolution multispectral satellite images covering large areas and satisfactory results are obtained.
Subject Keywords
Water canal extraction
,
High resolution satellite images
,
Spectral index
,
Structural analysis
URI
https://hdl.handle.net/11511/55105
Collections
Graduate School of Informatics, Conference / Seminar
Suggestions
OpenMETU
Core
Detection of reservoir water levels using landsat remote sensing data over Ermenek and Altınkaya dams
Şenocak, Ali Ulvi Galip; Yılmaz, M. Tuğrul.; Department of Civil Engineering (2019)
Detection of water border using remote sensing observations at the visible bands and incorporating them with the digital elevation map is a useful approach for detecting water volume of dams and the water bodies with existing DEM images. In this study, NDWI, NDPI, WI2015 and AWEI indices retrieved using Landsat 8 images and ASTER/SRTM DEM maps are utilized to infer about the water levels of Ermenek and Altınkaya dams’ reservoir water levels. To reduce the water level retrieval errors during the cloudy and t...
A new robust method for bridge detection from high resolution electro optic satellite images
Gedik, Ekın; Cınar, Umut; Karaman, Ersin; Çetin, Yasemin; Halıcı, Uğur (null; 2012-05-09)
In this paper, an automatic approach for identifying bridges over water in satellite images is proposed. The proposed algorithm has three main steps. It starts with extracting the water regions in the satellite image by thresholding the NIR and clustering the NDWI images. Next possible river and water canals in the extracted water mask are identified by certain geometric constraints. Finally possible bridge regions are extracted by morphological operations applied to the water and river-canal mask....
Automated Detection of Arbitrarily Shaped Buildings in Complex Environments From Monocular VHR Optical Satellite Imagery
Ok, Ali Ozgun; Senaras, Caglar; Yuksel, Baris (2013-03-01)
This paper introduces a new approach for the automated detection of buildings from monocular very high resolution (VHR) optical satellite images. First, we investigate the shadow evidence to focus on building regions. To do that, we propose a new fuzzy landscape generation approach to model the directional spatial relationship between buildings and their shadows. Once all landscapes are collected, a pruning process is developed to eliminate the landscapes that may occur due to non-building objects. The fina...
Multiple-criteria calibration of a distributed watershed model using spatial regularization and response signatures
Pokhrel, Prafulla; Yılmaz, Koray Kamil; Gupta, Hoshin V. (Elsevier BV, 2012-02-08)
This paper explores the use of a semi-automated multiple-criteria calibration approach for estimating the parameters of the spatially distributed HL-DHM model to the Blue River basin, Oklahoma. The study was performed in the context of Phase 2 of the DMIP project organized by the Hydrology Lab of the NWS. To deal with the problem of ill conditioning, we employ a regularization approach that constrains the search space using information contained in a priori estimates of the spatially distributed parameter f...
A Learning-Based Resegmentation Method for Extraction of Buildings in Satellite Images
Dikmen, Mehmet; Halıcı, Uğur (2014-12-01)
This letter introduces a new method for building extraction in satellite images. The algorithm first identifies the shadow segments on an oversegmented image, and then neighboring shadow segments, which are assumed to be cast by a single building, are merged. Next, candidate regions where buildings most likely occur are detected by using these shadow regions. Along with this information, closeness to shadows in illumination direction and spectral properties of segments are used to classify them as belonging...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Gedik, E. Kahraman, U. Çinar, Y. Çetin, and U. Halıcı, “Automatic Water Canal Detection in Multispectral Satellite Images,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55105.