Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia

Detalhes bibliográficos
Autor(a) principal: Indarto, Indarto
Data de Publicação: 2022
Outros Autores: Hidayah, Entin, Lukman Hakim, Farid
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anuário do Instituto de Geociências (Online)
Texto Completo: https://revistas.ufrj.br/index.php/aigeo/article/view/46456
Resumo: This study aims to analyse land use, and land cover (LULC) changes in East Java province in Indonesia. The changes are analysed by comparing two maps (the national digital map and the map interpreted from Landsat-8). Supervised classification of Landsat image using maximum likelihood algorithm done an overall and kappa accuracy of 96.62% and 96.02 %, respectively. The classification produces nine (9) classes, i.e.: (1) the pavement or urban area, (2) heterogeneous agricultural land, (3) paddy field, (4) open water, (5) dense vegetation (forest), (6) sparse vegetation (plantation), (7) shrubland, (8) Wetlands, and (9) Sandy-clay-rock. Furthermore, three subsets areas are explored to study the LULC changes caused by the development of the transportation infrastructure; industrial sites; the agricultural sector; tourism; urbanisation and sub-urbanisation. The LULC change is more marked in the most urbanised areas (in and around the big cities), followed by LULC change in and around medium cities and rural areas.  Regional development during the last two decades has increased built-up and plantation areas. Conversely, the development has reduced paddy fields, rural areas, and water bodies. The LULC changes have significantly changed the natural to a human-dominated landscape. 
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spelling Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java IndonesiaLand use; Land cover; Change; RBI; Landsat-8; East JavaThis study aims to analyse land use, and land cover (LULC) changes in East Java province in Indonesia. The changes are analysed by comparing two maps (the national digital map and the map interpreted from Landsat-8). Supervised classification of Landsat image using maximum likelihood algorithm done an overall and kappa accuracy of 96.62% and 96.02 %, respectively. The classification produces nine (9) classes, i.e.: (1) the pavement or urban area, (2) heterogeneous agricultural land, (3) paddy field, (4) open water, (5) dense vegetation (forest), (6) sparse vegetation (plantation), (7) shrubland, (8) Wetlands, and (9) Sandy-clay-rock. Furthermore, three subsets areas are explored to study the LULC changes caused by the development of the transportation infrastructure; industrial sites; the agricultural sector; tourism; urbanisation and sub-urbanisation. The LULC change is more marked in the most urbanised areas (in and around the big cities), followed by LULC change in and around medium cities and rural areas.  Regional development during the last two decades has increased built-up and plantation areas. Conversely, the development has reduced paddy fields, rural areas, and water bodies. The LULC changes have significantly changed the natural to a human-dominated landscape. Universidade Federal do Rio de JaneiroUniversity of JemberIndarto, IndartoHidayah, EntinLukman Hakim, Farid2022-09-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/4645610.11137/1982-3908_2022_45_46456Anuário do Instituto de Geociências; Vol 45 (2022)Anuário do Instituto de Geociências; Vol 45 (2022)1982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJenghttps://revistas.ufrj.br/index.php/aigeo/article/view/46456/pdf/*ref*/Ahmed, I.M. & Alla, E.M.A. 2019, 'Landuse impact on the environment of Tuti Island, Sudan', Geography, Environment, Sustainability, vol. 12, no. 3, pp. 27–33. https://doi.org/10.24057/2071-9388-2018-13. Badan Informasi Geospatial 2018, Peta Rupa Bumi Indonesia Skala 1:25.000./*ref*/BIG - see Badan Informasi Geospatial./*ref*/BPS Jawa Timur 2017, Provinsi Jawa Timur dalam Angka. Jawa Timur Province in Figures 2017, Badan Pusat Statistik Provinsi Jawa Timur./*ref*/BSN 2014, Standar Nasional Indonesia (SNI) 7645:2014 tentang Klasifikasi Penutup Lahan, p. 28./*ref*/Congedo, L. 2016, ‘Semi-Automatic Classification Plugin Documentation’. http://dx.doi.org/10.13140/RG.2.2.29474.02242/1/*ref*/Dastgerdi, A.S., Sargolini, M., Pierantoni, I. & Stimilli, F. 2020, 'Toward an Innovative Strategic Approach for Sustainable Management of Natural Protected Areas in Italy', Geography, Environment, Sustainability, vol. 13, no. 3, pp. 68-75. https://doi.org/10.24057/2071-9388-2019-143/*ref*/Elias, E., Seifu, W., Tesfaye, B. & Girmay, W. 2019, 'Impact of land use/cover changes on lake ecosystem of Ethiopia central rift valley', M. Tejada Moral (ed.), Cogent Food & Agriculture, vol. 5, no. 1, p. 1595876. http://dx.doi.org/10.1080/23311932.2019.1595876/*ref*/Fonji, S.F. & Taff, G.N. 2014, 'Using satellite data to monitor land-use land-cover change in North-eastern Latvia', SpringerPlus, vol. 3, no. 1, pp. 1–15. http://dx.doi.org/10.1186/2193-1801-3-61/*ref*/Foody, G. 2008, 'Harshness in image classification accuracy assessment', International Journal of Remote Sensing, vol. 29, no. 11, pp. 3137–58. https://doi.org/10.1080/01431160701442120/*ref*/Foody, G.M. 2004, 'Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy', Photogrammetric Engineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing, pp. 627–33. http://dx.doi.org/10.14358/PERS.70.5.627/*ref*/Hassen, E.E. & Assen, M. 2018, 'Land use/cover dynamics and its drivers in Gelda catchment, Lake Tana watershed, Ethiopia', Environmental Systems Research, vol. 6, no. 1. https://doi.org/10.1186/s40068-017-0081-x/*ref*/Klimanova, O., Naumov, A., Greenfieldt, Y., Prado, R.B. & Tretyachenko, D. 2017, 'Recent regional trends of land use and land cover transformations in Brazil', Geography, Environment, Sustainability, vol. 10, no. 4, pp. 98–116. https://doi.org/10.24057/2071-9388-2017-10-4-98-116/*ref*/Klyuev, N.N. 2019, 'The spatial analyses of natural resources use in Russia for 1990-2017', Geography, Environment, Sustainability, vol. 12, no. 4, pp. 203–11. https://doi.org/10.24057/2071-9388-2018-65/*ref*/Landgrebe, D. 2015, MultiSpec Tutorial: Supervised Classification-Select Training Fields./*ref*/Landgrebe, D. & Biehl, L. 2018, MultiSpec (C), School of Electrical and Computer Engineering Purdue University./*ref*/Łucka, D. 2018, 'How to build a community. New Urbanism and its critics', Urban Development Issues, vol. 59, no. 1, pp. 17–26. http://dx.doi.org/10.2478/udi-2018-0025/*ref*/Mangmeechai, A. 2020, 'Effects of rubber plantation policy on water resources and land-use change in the Northeastern region of Thailand', Geography, Environment, Sustainability, vol. 13, no. 2, pp. 73–83. https://doi.org/10.24057/2071-9388-2019-145/*ref*/Mtibaa, S. & Irie, M. 2016, 'Land cover mapping in cropland dominated area using information on vegetation phenology and multi-seasonal Landsat 8 images', Euro-Mediterranean Journal for Environmental Integration, vol. 1, no. 1. http://dx.doi.org/10.1007/s41207-016-0006-5/*ref*/Nguyen, L.B. 2020, 'Land cover change detection in northwestern Vietnam using Landsat images and Google Earth Engine', Journal of Water and Land Development, no. 46, pp. 162–9. http://dx.doi.org/10.24425/jwld.2020.134209/*ref*/Ptak, M. & Ławniczak, A.E. 2012, ‘Changes in land use in the buffer zone of lake of the Mała Wełna catchment’, Limnological Review, vol. 12, no. 1, pp. 35–44. https://doi.org/https://doi.org/10.2478/v10194-011-0043-z/*ref*/QGIS Development Team 2019, QGIS Geographic Information System. Open Source Geospatial Foundation Project./*ref*/USGS - see United States Geological Survey./*ref*/United States Geological Survey 2018, EarthExplorer - Home, viewed <https://earthexplorer.usgs.gov/>./*ref*/United States Geological Survey 2019, Landsat Levels of Processing, viewed <https://www.usgs.gov/land-resources/nli/landsat/landsat-levels-processing>.Copyright (c) 2022 Anuário do Instituto de Geociênciashttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccess2022-12-28T20:46:28Zoai:www.revistas.ufrj.br:article/46456Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2022-12-28T20:46:28Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
title Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
spellingShingle Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
Indarto, Indarto
Land use; Land cover; Change; RBI; Landsat-8; East Java
title_short Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
title_full Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
title_fullStr Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
title_full_unstemmed Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
title_sort Assessment of Land Use and Land Cover Change from 2000 to 2019 in East Java Indonesia
author Indarto, Indarto
author_facet Indarto, Indarto
Hidayah, Entin
Lukman Hakim, Farid
author_role author
author2 Hidayah, Entin
Lukman Hakim, Farid
author2_role author
author
dc.contributor.none.fl_str_mv University of Jember
dc.contributor.author.fl_str_mv Indarto, Indarto
Hidayah, Entin
Lukman Hakim, Farid
dc.subject.por.fl_str_mv Land use; Land cover; Change; RBI; Landsat-8; East Java
topic Land use; Land cover; Change; RBI; Landsat-8; East Java
description This study aims to analyse land use, and land cover (LULC) changes in East Java province in Indonesia. The changes are analysed by comparing two maps (the national digital map and the map interpreted from Landsat-8). Supervised classification of Landsat image using maximum likelihood algorithm done an overall and kappa accuracy of 96.62% and 96.02 %, respectively. The classification produces nine (9) classes, i.e.: (1) the pavement or urban area, (2) heterogeneous agricultural land, (3) paddy field, (4) open water, (5) dense vegetation (forest), (6) sparse vegetation (plantation), (7) shrubland, (8) Wetlands, and (9) Sandy-clay-rock. Furthermore, three subsets areas are explored to study the LULC changes caused by the development of the transportation infrastructure; industrial sites; the agricultural sector; tourism; urbanisation and sub-urbanisation. The LULC change is more marked in the most urbanised areas (in and around the big cities), followed by LULC change in and around medium cities and rural areas.  Regional development during the last two decades has increased built-up and plantation areas. Conversely, the development has reduced paddy fields, rural areas, and water bodies. The LULC changes have significantly changed the natural to a human-dominated landscape. 
publishDate 2022
dc.date.none.fl_str_mv 2022-09-15
dc.type.none.fl_str_mv

dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/46456
10.11137/1982-3908_2022_45_46456
url https://revistas.ufrj.br/index.php/aigeo/article/view/46456
identifier_str_mv 10.11137/1982-3908_2022_45_46456
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/46456/pdf
/*ref*/Ahmed, I.M. & Alla, E.M.A. 2019, 'Landuse impact on the environment of Tuti Island, Sudan', Geography, Environment, Sustainability, vol. 12, no. 3, pp. 27–33. https://doi.org/10.24057/2071-9388-2018-13. Badan Informasi Geospatial 2018, Peta Rupa Bumi Indonesia Skala 1:25.000.
/*ref*/BIG - see Badan Informasi Geospatial.
/*ref*/BPS Jawa Timur 2017, Provinsi Jawa Timur dalam Angka. Jawa Timur Province in Figures 2017, Badan Pusat Statistik Provinsi Jawa Timur.
/*ref*/BSN 2014, Standar Nasional Indonesia (SNI) 7645:2014 tentang Klasifikasi Penutup Lahan, p. 28.
/*ref*/Congedo, L. 2016, ‘Semi-Automatic Classification Plugin Documentation’. http://dx.doi.org/10.13140/RG.2.2.29474.02242/1
/*ref*/Dastgerdi, A.S., Sargolini, M., Pierantoni, I. & Stimilli, F. 2020, 'Toward an Innovative Strategic Approach for Sustainable Management of Natural Protected Areas in Italy', Geography, Environment, Sustainability, vol. 13, no. 3, pp. 68-75. https://doi.org/10.24057/2071-9388-2019-143
/*ref*/Elias, E., Seifu, W., Tesfaye, B. & Girmay, W. 2019, 'Impact of land use/cover changes on lake ecosystem of Ethiopia central rift valley', M. Tejada Moral (ed.), Cogent Food & Agriculture, vol. 5, no. 1, p. 1595876. http://dx.doi.org/10.1080/23311932.2019.1595876
/*ref*/Fonji, S.F. & Taff, G.N. 2014, 'Using satellite data to monitor land-use land-cover change in North-eastern Latvia', SpringerPlus, vol. 3, no. 1, pp. 1–15. http://dx.doi.org/10.1186/2193-1801-3-61
/*ref*/Foody, G. 2008, 'Harshness in image classification accuracy assessment', International Journal of Remote Sensing, vol. 29, no. 11, pp. 3137–58. https://doi.org/10.1080/01431160701442120
/*ref*/Foody, G.M. 2004, 'Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy', Photogrammetric Engineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing, pp. 627–33. http://dx.doi.org/10.14358/PERS.70.5.627
/*ref*/Hassen, E.E. & Assen, M. 2018, 'Land use/cover dynamics and its drivers in Gelda catchment, Lake Tana watershed, Ethiopia', Environmental Systems Research, vol. 6, no. 1. https://doi.org/10.1186/s40068-017-0081-x
/*ref*/Klimanova, O., Naumov, A., Greenfieldt, Y., Prado, R.B. & Tretyachenko, D. 2017, 'Recent regional trends of land use and land cover transformations in Brazil', Geography, Environment, Sustainability, vol. 10, no. 4, pp. 98–116. https://doi.org/10.24057/2071-9388-2017-10-4-98-116
/*ref*/Klyuev, N.N. 2019, 'The spatial analyses of natural resources use in Russia for 1990-2017', Geography, Environment, Sustainability, vol. 12, no. 4, pp. 203–11. https://doi.org/10.24057/2071-9388-2018-65
/*ref*/Landgrebe, D. 2015, MultiSpec Tutorial: Supervised Classification-Select Training Fields.
/*ref*/Landgrebe, D. & Biehl, L. 2018, MultiSpec (C), School of Electrical and Computer Engineering Purdue University.
/*ref*/Łucka, D. 2018, 'How to build a community. New Urbanism and its critics', Urban Development Issues, vol. 59, no. 1, pp. 17–26. http://dx.doi.org/10.2478/udi-2018-0025
/*ref*/Mangmeechai, A. 2020, 'Effects of rubber plantation policy on water resources and land-use change in the Northeastern region of Thailand', Geography, Environment, Sustainability, vol. 13, no. 2, pp. 73–83. https://doi.org/10.24057/2071-9388-2019-145
/*ref*/Mtibaa, S. & Irie, M. 2016, 'Land cover mapping in cropland dominated area using information on vegetation phenology and multi-seasonal Landsat 8 images', Euro-Mediterranean Journal for Environmental Integration, vol. 1, no. 1. http://dx.doi.org/10.1007/s41207-016-0006-5
/*ref*/Nguyen, L.B. 2020, 'Land cover change detection in northwestern Vietnam using Landsat images and Google Earth Engine', Journal of Water and Land Development, no. 46, pp. 162–9. http://dx.doi.org/10.24425/jwld.2020.134209
/*ref*/Ptak, M. & Ławniczak, A.E. 2012, ‘Changes in land use in the buffer zone of lake of the Mała Wełna catchment’, Limnological Review, vol. 12, no. 1, pp. 35–44. https://doi.org/https://doi.org/10.2478/v10194-011-0043-z
/*ref*/QGIS Development Team 2019, QGIS Geographic Information System. Open Source Geospatial Foundation Project.
/*ref*/USGS - see United States Geological Survey.
/*ref*/United States Geological Survey 2018, EarthExplorer - Home, viewed <https://earthexplorer.usgs.gov/>.
/*ref*/United States Geological Survey 2019, Landsat Levels of Processing, viewed <https://www.usgs.gov/land-resources/nli/landsat/landsat-levels-processing>.
dc.rights.driver.fl_str_mv Copyright (c) 2022 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Anuário do Instituto de Geociências
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
publisher.none.fl_str_mv Universidade Federal do Rio de Janeiro
dc.source.none.fl_str_mv Anuário do Instituto de Geociências; Vol 45 (2022)
Anuário do Instituto de Geociências; Vol 45 (2022)
1982-3908
0101-9759
reponame:Anuário do Instituto de Geociências (Online)
instname:Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
instname_str Universidade Federal do Rio de Janeiro (UFRJ)
instacron_str UFRJ
institution UFRJ
reponame_str Anuário do Instituto de Geociências (Online)
collection Anuário do Instituto de Geociências (Online)
repository.name.fl_str_mv Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)
repository.mail.fl_str_mv anuario@igeo.ufrj.br||
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