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Assessment of Gap-Filling Interpolation Methods for Identifying Mangrove Trends at Segara Anakan in 2015 by using Landsat 8 OLI and Proba-V

Indonesian Journal of Geography · Vol. 52 No. 3 (2020) · hlm. 341–349

DOI
10.22146/ijg.50556
ISSN
2354-9114, 0024-9521
Terbit
2020-12-31
Penerbit
Faculty of Geography, Universitas Gadjah Mada
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-nc/4.0

Abstrak

The existence and services of mangrove ecosystems in Segara Anakan are threatened by changes in land use on land and global warming, which requires proper and intensive monitoring. The monitoring of mangrove and its trend over large areas can be done using multi-temporal remote sensing technology. However, remote sensing data is often contaminated by cloud cover, and its corresponding shadow resulted in missing data. This study aims to assess the performance of the existed gap-filling techniques, such as, linear, spline, stineman, data interpolation Empirical Orthogonal Function (dineof) and spatial downscaling strategy employing the Proba-V imagery in 100 m, when being used for estimating the missing data and depicting the trend in NDVI from Landsat 8 OLI by using Mann-Kendall test. Our result suggested that EOF-based interpolation gave better prediction results and more accurate in predicting longer missing data. Linear interpolation, on the other hand, was accurate to predict shorter missing data. Overall, all interpolation results can reconstruct 64 (spline) to 72 % (dineof) of missing data in NDVI with the RMSE of 0.10 (dineof) – 0.13 (spline). A consistent decreasing trend was also found from the four interpolation methods, which showed the consistency of the interpolated values when used for deriving trends with similar patterns of overall decreasing trend and magnitude of changes of -0.0095 to -0.0099 (NDVI unit) over the mangrove areas in 2015. The result demonstrated the potential ability of gap-filling methods for simulating the value of missing data and for deriving trends.

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  • Universitas Gadjah Mada
  • Universitas Esa Unggul
  • Ministry of Marine Affairs and Fisheries
  • Center for International Forestry Research
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Rekan penulisOrganisasiArtikel bersama
Muhammad KamalUniversitas Gadjah Mada3
Projo DanoedoroUniversitas Gadjah Mada2
Sigit HerumurtiAfiliasi tidak diketahui1
Prama Ardha AryagunaUniversitas Esa Unggul1
Yanuar Adji NugrohoUniversitas Gadjah Mada1
Prima WidayaniUniversitas Gadjah Mada1
Muhammad Sufwandika WijayaUniversitas Gadjah Mada1
Hartono HartonoUniversitas Gadjah Mada1
Pramaditya WicaksonoUniversitas Gadjah Mada1
Novi Susetyo AdiMinistry of Marine Affairs and Fisheries1
Uji Astrono PribadiCenter for International Forestry Research1
Gilang Aria SetaAfiliasi tidak diketahui1
Yusri KhoirurrizqiUniversitas Gadjah Mada1
Rohmad SasongkoUniversitas Gadjah Mada1
Nur Laila Eka UtamiUniversitas Gadjah Mada1
Amanda IrbahUniversitas Gadjah Mada1
Siti ZahrotunisaUniversitas Gadjah Mada1
Maulana Abdul HakimUniversitas Gadjah Mada1

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Sumber metadata: OAI-PMH (metadata jurnal) http://jurnal.ugm.ac.id/ijg/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Assessment of Gap-Filling Interpolation Methods for Identifying Mangrove Trends at Segara Anakan in 2015 by using Landsat 8 OLI and Proba-V</dc:title>
	<dc:creator>Arjasakusuma, Sanjiwana</dc:creator>
	<dc:creator>Pratama, Abimanyu Putra</dc:creator>
	<dc:creator>Lestari, Intan</dc:creator>
	<dc:subject xml:lang="en-US">Remote Sensing</dc:subject>
	<dc:subject xml:lang="en-US">Interpolation; Spatial-Downscaling NDVI; Mann-Kendall; Sens-slope</dc:subject>
	<dc:subject xml:lang="en-US">Vegetation; Mangrove; Trend; Interpolation</dc:subject>
	<dc:description xml:lang="en-US">The existence and services of mangrove ecosystems in Segara Anakan are threatened by changes in land use on land and global warming, which requires proper and intensive monitoring. The monitoring of mangrove and its trend over large areas can be done using multi-temporal remote sensing technology. However, remote sensing data is often contaminated by cloud cover, and its corresponding shadow resulted in missing data. This study aims to assess the performance of the existed gap-filling techniques, such as, linear, spline, stineman,  data interpolation Empirical Orthogonal Function (dineof) and spatial downscaling strategy employing the Proba-V imagery in 100 m, when being used for estimating the missing data and depicting the trend in NDVI from Landsat 8 OLI by using Mann-Kendall test. Our result suggested that EOF-based interpolation gave better prediction results and more accurate in predicting longer missing data. Linear interpolation, on the other hand, was accurate to predict shorter missing data. Overall, all interpolation results can reconstruct 64 (spline) to 72 % (dineof) of missing data in NDVI with the RMSE of 0.10 (dineof) – 0.13 (spline). A consistent decreasing trend was also found from the four interpolation methods, which showed the consistency of the interpolated values when used for deriving trends with similar patterns of overall decreasing trend and magnitude of changes of -0.0095 to -0.0099 (NDVI unit) over the mangrove areas in 2015. The result demonstrated the potential ability of gap-filling methods for simulating the value of missing data and for deriving trends.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Geography, Universitas Gadjah Mada</dc:publisher>
	<dc:contributor xml:lang="en-US">Faculty of Geography, Universitas Gadjah Mada</dc:contributor>
	<dc:date>2020-12-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijg/article/view/50556</dc:identifier>
	<dc:identifier>10.22146/ijg.50556</dc:identifier>
	<dc:source xml:lang="en-US">Indonesian Journal of Geography; Vol 52, No 3 (2020): Indonesian Journal of Geography; 341 - 349</dc:source>
	<dc:source>2354-9114</dc:source>
	<dc:source>0024-9521</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijg/article/view/50556/pdf</dc:relation>
	<dc:relation>https://journal.ugm.ac.id/ijg/article/downloadSuppFile/50556/9688</dc:relation>
	<dc:relation>https://journal.ugm.ac.id/ijg/article/downloadSuppFile/50556/9689</dc:relation>
	<dc:coverage xml:lang="en-US">Segara Anakan</dc:coverage>
	<dc:coverage xml:lang="en-US">2015</dc:coverage>
	<dc:coverage xml:lang="en-US"></dc:coverage>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 Authors</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>