A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island

Arctic plays as a key climatic region, it is highly affected by climate change. Climate change has long been considered as an effect of global warming, it is derived from complex linkages and changes in climate variables. Land surface temperature (LST) is known as one of the essential climate variab...

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Published in:Modeling Earth Systems and Environment
Main Authors: Cendana Fitrahanjani, -, Tofan Agung Eka Prasetya, -, Rachmah Indawati, -
Format: Article in Journal/Newspaper
Language:English
Published: Springer Nature logo 2021
Subjects:
Online Access:https://repository.unair.ac.id/113896/
https://repository.unair.ac.id/113896/1/15%20turnitin.pdf
https://repository.unair.ac.id/113896/2/15%20gabungan.pdf
https://repository.unair.ac.id/113896/5/1a%20statistical%20method.pdf
https://www.springer.com/journal/40808
https://doi.org/10.1007/s40808-020-00907-6
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spelling ftunivairlangga:oai:repository.unair.ac.id:113896 2023-05-15T14:51:43+02:00 A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island Cendana Fitrahanjani, - Tofan Agung Eka Prasetya, - Rachmah Indawati, - 2021 text https://repository.unair.ac.id/113896/ https://repository.unair.ac.id/113896/1/15%20turnitin.pdf https://repository.unair.ac.id/113896/2/15%20gabungan.pdf https://repository.unair.ac.id/113896/5/1a%20statistical%20method.pdf https://www.springer.com/journal/40808 https://doi.org/10.1007/s40808-020-00907-6 en eng Springer Nature logo https://repository.unair.ac.id/113896/1/15%20turnitin.pdf https://repository.unair.ac.id/113896/2/15%20gabungan.pdf https://repository.unair.ac.id/113896/5/1a%20statistical%20method.pdf Cendana Fitrahanjani, - and Tofan Agung Eka Prasetya, - and Rachmah Indawati, - (2021) A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island. Modeling Earth Systems and Environment, 7 (1). pp. 561-569. ISSN 2363-6211 QC981 Climate Article PeerReviewed 2021 ftunivairlangga https://doi.org/10.1007/s40808-020-00907-6 2022-03-15T19:56:29Z Arctic plays as a key climatic region, it is highly affected by climate change. Climate change has long been considered as an effect of global warming, it is derived from complex linkages and changes in climate variables. Land surface temperature (LST) is known as one of the essential climate variables (ECVs). Recent study founds that LST has risen in the Arctic. Due to the rising temperatures, there has been a massive decrease in basic Arctic features, which elevated the percentage of heat trapped in the surface. LST is an ECV which needs to be further investigated in key regions. This study aims to investigate LST changes over February 2000 to November 2019 in Spitsbergen. We used autoregression and multivariate regression with cubic spline used to investigate LST changes over this period in Spitsbergen. Four knots and seven knots cubic spline were applied, respectively, to detect acceleration and 7-year cycle. Research founds that LST in Spitsbergen rise by 1.039 °C per decade (CI 0.576–1.501; z: 4.403). Gustav Adolf Land, Nordaustlandet has the highest temperature rise, location of the well-known Vegafonna ice-caps. A notable increase has shown during winter days. Article in Journal/Newspaper Arctic Climate change Global warming Gustav Adolf Land Nordaustlandet Spitsbergen Airlangga University: UNAIR Repository Arctic Gustav Adolf Land ENVELOPE(21.643,21.643,79.579,79.579) Nordaustlandet ENVELOPE(22.400,22.400,79.800,79.800) Vegafonna ENVELOPE(21.201,21.201,79.454,79.454) Modeling Earth Systems and Environment 7 1 561 569
institution Open Polar
collection Airlangga University: UNAIR Repository
op_collection_id ftunivairlangga
language English
topic QC981 Climate
spellingShingle QC981 Climate
Cendana Fitrahanjani, -
Tofan Agung Eka Prasetya, -
Rachmah Indawati, -
A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
topic_facet QC981 Climate
description Arctic plays as a key climatic region, it is highly affected by climate change. Climate change has long been considered as an effect of global warming, it is derived from complex linkages and changes in climate variables. Land surface temperature (LST) is known as one of the essential climate variables (ECVs). Recent study founds that LST has risen in the Arctic. Due to the rising temperatures, there has been a massive decrease in basic Arctic features, which elevated the percentage of heat trapped in the surface. LST is an ECV which needs to be further investigated in key regions. This study aims to investigate LST changes over February 2000 to November 2019 in Spitsbergen. We used autoregression and multivariate regression with cubic spline used to investigate LST changes over this period in Spitsbergen. Four knots and seven knots cubic spline were applied, respectively, to detect acceleration and 7-year cycle. Research founds that LST in Spitsbergen rise by 1.039 °C per decade (CI 0.576–1.501; z: 4.403). Gustav Adolf Land, Nordaustlandet has the highest temperature rise, location of the well-known Vegafonna ice-caps. A notable increase has shown during winter days.
format Article in Journal/Newspaper
author Cendana Fitrahanjani, -
Tofan Agung Eka Prasetya, -
Rachmah Indawati, -
author_facet Cendana Fitrahanjani, -
Tofan Agung Eka Prasetya, -
Rachmah Indawati, -
author_sort Cendana Fitrahanjani, -
title A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
title_short A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
title_full A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
title_fullStr A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
title_full_unstemmed A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island
title_sort statistical method for analysing temperature increase from remote sensing data with application to spitsbergen island
publisher Springer Nature logo
publishDate 2021
url https://repository.unair.ac.id/113896/
https://repository.unair.ac.id/113896/1/15%20turnitin.pdf
https://repository.unair.ac.id/113896/2/15%20gabungan.pdf
https://repository.unair.ac.id/113896/5/1a%20statistical%20method.pdf
https://www.springer.com/journal/40808
https://doi.org/10.1007/s40808-020-00907-6
long_lat ENVELOPE(21.643,21.643,79.579,79.579)
ENVELOPE(22.400,22.400,79.800,79.800)
ENVELOPE(21.201,21.201,79.454,79.454)
geographic Arctic
Gustav Adolf Land
Nordaustlandet
Vegafonna
geographic_facet Arctic
Gustav Adolf Land
Nordaustlandet
Vegafonna
genre Arctic
Climate change
Global warming
Gustav Adolf Land
Nordaustlandet
Spitsbergen
genre_facet Arctic
Climate change
Global warming
Gustav Adolf Land
Nordaustlandet
Spitsbergen
op_relation https://repository.unair.ac.id/113896/1/15%20turnitin.pdf
https://repository.unair.ac.id/113896/2/15%20gabungan.pdf
https://repository.unair.ac.id/113896/5/1a%20statistical%20method.pdf
Cendana Fitrahanjani, - and Tofan Agung Eka Prasetya, - and Rachmah Indawati, - (2021) A statistical method for analysing temperature increase from remote sensing data with application to Spitsbergen Island. Modeling Earth Systems and Environment, 7 (1). pp. 561-569. ISSN 2363-6211
op_doi https://doi.org/10.1007/s40808-020-00907-6
container_title Modeling Earth Systems and Environment
container_volume 7
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