Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/4737
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dc.contributor.authorPatidar, Nitesh-
dc.contributor.authorKeshari, A. K.-
dc.date.accessioned2020-09-07T21:37:18Z-
dc.date.available2020-09-07T21:37:18Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Remote Sensing 2020, VOL. 41, NO. 10, 3970–3992en_US
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/4737-
dc.description.abstractThe spatial distribution and the temporal dynamics of impervious surface (IS) are important for understanding urbanization and its impact on surface energy balance, ecohydrological processes, and urban heat island. Despite the development of various methods, quantification of IS on multi-temporal scale is still challenging in complex urban areas due to the mixed pixel problem and the spectral ambiguity between classes. This study aimed at developing an algorithm, named Rule-Based Spectral Unmixing Algorithm (RBSUA), to derive sub-pixel IS fraction at annual scale using a time series of satellite images. A rule-based composite scheme is developed to integrate temporal contextual information into the popular Multiple Endmember Spectral Mixture Analysis (MESMA) to improve the classification of spectrally ambiguous classes. The developed algorithm also encompasses a temporal filtering to derive consistent IS fractions. Evaluation of the algorithm in a complex urban area – the National Capital Region (NCR), India – shows an improved performance in separating spectrally ambiguous classes, particularly IS and soil, and obtaining consistent series of IS fraction. The developed algorithm yielded the accuracy of annual IS fraction between 88% and 91% which is considerably higher than those from the original MESMA (48% to 83%). The application of the RBSUA in the NCR, India, shows that the IS has increased in the study area from the initial value of 377 ± 78 km2 in 1992 to 708 ± 64 km2 in 2017. The results suggested that the developed algorithm was effective in deriving IS at the sub-pixel level and detecting changes at the annual frequency.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectIimpervious surfaceen_US
dc.subjectMultiple Endmember Spectral Mixture Analysisen_US
dc.subjectSub-pixel impervious surface fractionen_US
dc.titleA rule-based spectral unmixing algorithm for extracting annual time series of sub-pixel impervious surface fractionen_US
dc.typeArticleen_US
Appears in Collections:Research papers in International Journals

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