Satellite imagery and change detection for land cover

Satellite imagery is widely used for studying the surface of earth. The optical images which contain multi-spectral bands provide a great amount of information which cannot be observed by human eyes directly. As large amount of satellite images is produced, processing the images to gather useful...

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Main Author: Liu, Lu
Other Authors: Lu Yilong
Format: Final Year Project
Language:English
Published: 2017
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Online Access:http://hdl.handle.net/10356/71753
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-717532023-07-07T15:52:01Z Satellite imagery and change detection for land cover Liu, Lu Lu Yilong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Satellite imagery is widely used for studying the surface of earth. The optical images which contain multi-spectral bands provide a great amount of information which cannot be observed by human eyes directly. As large amount of satellite images is produced, processing the images to gather useful data becomes critical. Change detection is one of the common topic in satellite image processing. The applications of change detection include agriculture, urban planning, ocean study, etc. Proposed by Twenty First Century Aerospace Technology (Asia) Pte Ltd (21AT), this project conducts a research on potential change detection algorithms to find out the efficient and accurate method of change detection which is suitable for their cases. During this project, a MATLAB image change detection toolbox is built containing five change detection methods, including Image Differencing, Normalized Difference Vegetation Index, Principal Component Analysis, K-means Clustering and Maximum Likelihood Classification. In this report, five change detection methods will be compared through three case studies in Singapore, India and China respectively. All methods show their advantages and disadvantages. Among them, Image Differencing and Principal Component Analysis are recommended for similar cases. Bachelor of Engineering 2017-05-19T02:54:52Z 2017-05-19T02:54:52Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71753 en Nanyang Technological University 68 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Liu, Lu
Satellite imagery and change detection for land cover
description Satellite imagery is widely used for studying the surface of earth. The optical images which contain multi-spectral bands provide a great amount of information which cannot be observed by human eyes directly. As large amount of satellite images is produced, processing the images to gather useful data becomes critical. Change detection is one of the common topic in satellite image processing. The applications of change detection include agriculture, urban planning, ocean study, etc. Proposed by Twenty First Century Aerospace Technology (Asia) Pte Ltd (21AT), this project conducts a research on potential change detection algorithms to find out the efficient and accurate method of change detection which is suitable for their cases. During this project, a MATLAB image change detection toolbox is built containing five change detection methods, including Image Differencing, Normalized Difference Vegetation Index, Principal Component Analysis, K-means Clustering and Maximum Likelihood Classification. In this report, five change detection methods will be compared through three case studies in Singapore, India and China respectively. All methods show their advantages and disadvantages. Among them, Image Differencing and Principal Component Analysis are recommended for similar cases.
author2 Lu Yilong
author_facet Lu Yilong
Liu, Lu
format Final Year Project
author Liu, Lu
author_sort Liu, Lu
title Satellite imagery and change detection for land cover
title_short Satellite imagery and change detection for land cover
title_full Satellite imagery and change detection for land cover
title_fullStr Satellite imagery and change detection for land cover
title_full_unstemmed Satellite imagery and change detection for land cover
title_sort satellite imagery and change detection for land cover
publishDate 2017
url http://hdl.handle.net/10356/71753
_version_ 1772826070615064576