An introduction to the spatio-temporal analysis of satellite remote sensing data for geostatisticians

Militino, Ana F.; Ugarte Martínez, María Dolores; Pérez Goya, Unai

doi:10.1007/978-3-319-78999-6_13

dc.creator	Militino, Ana F.	es_ES
dc.creator	Ugarte Martínez, María Dolores	es_ES
dc.creator	Pérez Goya, Unai	es_ES
dc.date.accessioned	2019-11-12T13:50:14Z
dc.date.available	2019-11-12T13:50:14Z
dc.date.issued	2018
dc.identifier.uri	https://hdl.handle.net/2454/35352
dc.description.abstract	Satellite remote sensing data have become available in meteorology, agriculture, forestry, geology, regional planning, hydrology or natural environment sciences since several decades ago, because satellites provide routinely high quality images with different temporal and spatial resolutions. Joining, combining or smoothing these images for a better quality of information is a challenge not always properly solved. In this regard, geostatistics, as the spatiotemporal stochastic techniques of georeferenced data, is a very helpful and powerful tool not enough explored in this area yet. Here, we analyze the current use of some of the geostatistical tools in satellite image analysis, and provide an introduction to this subject for potential researchers.	en
dc.description.sponsorship	This research was supported by the Spanish Ministry of Economy, Industry and Competitiveness (Project MTM2017-82553-R), the Government of Navarra (Project PI015, 2016 and Project PI043 2017), and by the Fundación Caja Navarra-UNED Pamplona (2016 and 2017).	en
dc.format.extent	15 p.
dc.format.mimetype	application/pdf	en
dc.language.iso	eng	en
dc.publisher	Springer International Publishing	en
dc.relation.ispartof	B. S. Daya Sagar et al. (eds.), Handbook of Mathematical Geosciences: Fifty Years of IAMG. e-ISBN 978-3-319-78999-6. P. 239-253	en
dc.rights	© The Author(s) 2018. This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.	en
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject	Satellites	en
dc.subject	Image analysis	en
dc.subject	Remote sensing datas	en
dc.title	An introduction to the spatio-temporal analysis of satellite remote sensing data for geostatisticians	en
dc.type	info:eu-repo/semantics/bookPart	en
dc.type	Capítulo de libro / Liburuen kapitulua	es
dc.contributor.department	Estadística, Informática y Matemáticas	es_ES
dc.contributor.department	Estatistika, Informatika eta Matematika	eu
dc.contributor.department	Institute for Advanced Materials - INAMAT	es_ES
dc.rights.accessRights	info:eu-repo/semantics/openAccess	en
dc.rights.accessRights	Acceso abierto / Sarbide irekia	es
dc.identifier.doi	10.1007/978-3-319-78999-6_13
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-82553-R/ES/	en
dc.relation.publisherversion	https://doi.org/10.1007/978-3-319-78999-6_13
dc.type.version	info:eu-repo/semantics/publishedVersion	en
dc.type.version	Versión publicada / Argitaratu den bertsioa	es
dc.contributor.funder	Gobierno de Navarra / Nafarroako Gobernua	es

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© The Author(s) 2018. This chapter is licensed under the terms of the Creative Commons Attribution 4.0
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adaptation, distribution and reproduction in any medium or format, as long as you give appropriate
credit to the original author(s) and the source, provide a link to the Creative Commons license and
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Commons license, unless indicated otherwise in a credit line to the material. If material is not
included in the chapter’s Creative Commons license and your intended use is not permitted by
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La licencia del ítem se describe como © The Author(s) 2018. This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.