Electrochemical determination of diethylstilbestrol by using a magnetic nanoparticle/graphene composite film electrode

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Author listPoo-Arporn Y., Pakapongpan S., Poo-Arporn R.P.

PublisherTaylor and Francis Group

Publication year2019

Journal acronymIJRS

Volume number625

Issue number1

ISSN0143-1161

eISSN1366-5901

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062697122&doi=10.1080%2f01431161.2019.1583394&partnerID=40&md5=2bccff71ac71888a662c4b53942fb82b

LanguagesEnglish-Great Britain (EN-GB)


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Abstract

Change detection (CD) from remote sensing data is a very challenging research problem, especially when we analyse an urban scene. Urban scenes are composed of many different types of objects, both natural and man-made. The building class is one of the important and most complex classes to analyse, important because it is useful for so many applications and complex because it exhibits many changes due to human activity and natural catastrophes. For these reasons, we focus our study on building change detection (BCD). In this paper we propose a classification scheme for BCD research according to several important dimensions including objective, input data, temporal resolution, analysis unit, target output unit, building features, processing technique, change categories, and assessment of results. This classification scheme can guide practitioners in choosing appropriate change detection methods to achieve their goals as well as informing new research efforts. Based on this multidimensional characterisation of BCD, we offer a number of suggestions for further work to be done in this field. ฉ 2019, ฉ 2019 Informa UK Limited, trading as Taylor & Francis Group.


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Last updated on 2023-17-10 at 07:36