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Long-term water surface monitoring using multi-temporal Landsat satellite data at Singkarak lake
Singkarak Lake has a central role for the surrounding community. To achieve SDGs Goal 6, Singkarak Lake is decided as one of the fifteen lakes to be managed sustainably based on the Indonesian Lake National Conference 2011. Therefore, this research aims to monitor the surface water area of Singkarak...
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creator | Purnama, Yustika Fauzi, Adam Irwansyah Nurtyawan, Rian Sakti, Anjar Dimara Nuha, Muhammad Ulin Anika, Nova Putra, Raden Siregar, Diyanti Isnani Prasetyo, Budhi Agung Julzarika, Atriyon Wikantika, Ketut |
description | Singkarak Lake has a central role for the surrounding community. To achieve SDGs Goal 6, Singkarak Lake is decided as one of the fifteen lakes to be managed sustainably based on the Indonesian Lake National Conference 2011. Therefore, this research aims to monitor the surface water area of Singkarak Lake using Landsat 5, 7 and 8 surface reflectance data from 2001 to 2019. The surface water body was extracted using a water detection rule algorithm involving three remote sensing indices, i.e., NDVI, mNDWI and EVI. Furthermore, the result was compared with Joint Research Center Yearly Water Classification History data. The result of two decades monitoring shows that the surface water of Singkarak Lake fluctuated with an average of 10,683 ha. The lowest surface water area was in 2012 with 10,579 ha, while the largest surface water area was in 2019 with 10,754 ha. The comparative analysis obtained an average deviation of 122 ha or 1.13%. From the quantitative aspect, this study has proven that the area of Singkarak Lake is relatively constant. Further study can be improved by involving the water level and qualitative aspects such as chlorophyll-a content. |
doi_str_mv | 10.1063/5.0115105 |
format | conference_proceeding |
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To achieve SDGs Goal 6, Singkarak Lake is decided as one of the fifteen lakes to be managed sustainably based on the Indonesian Lake National Conference 2011. Therefore, this research aims to monitor the surface water area of Singkarak Lake using Landsat 5, 7 and 8 surface reflectance data from 2001 to 2019. The surface water body was extracted using a water detection rule algorithm involving three remote sensing indices, i.e., NDVI, mNDWI and EVI. Furthermore, the result was compared with Joint Research Center Yearly Water Classification History data. The result of two decades monitoring shows that the surface water of Singkarak Lake fluctuated with an average of 10,683 ha. The lowest surface water area was in 2012 with 10,579 ha, while the largest surface water area was in 2019 with 10,754 ha. The comparative analysis obtained an average deviation of 122 ha or 1.13%. From the quantitative aspect, this study has proven that the area of Singkarak Lake is relatively constant. 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To achieve SDGs Goal 6, Singkarak Lake is decided as one of the fifteen lakes to be managed sustainably based on the Indonesian Lake National Conference 2011. Therefore, this research aims to monitor the surface water area of Singkarak Lake using Landsat 5, 7 and 8 surface reflectance data from 2001 to 2019. The surface water body was extracted using a water detection rule algorithm involving three remote sensing indices, i.e., NDVI, mNDWI and EVI. Furthermore, the result was compared with Joint Research Center Yearly Water Classification History data. The result of two decades monitoring shows that the surface water of Singkarak Lake fluctuated with an average of 10,683 ha. The lowest surface water area was in 2012 with 10,579 ha, while the largest surface water area was in 2019 with 10,754 ha. The comparative analysis obtained an average deviation of 122 ha or 1.13%. From the quantitative aspect, this study has proven that the area of Singkarak Lake is relatively constant. Further study can be improved by involving the water level and qualitative aspects such as chlorophyll-a content.</description><subject>Algorithms</subject><subject>Chlorophyll</subject><subject>Landsat 5</subject><subject>Landsat satellites</subject><subject>Monitoring</subject><subject>Remote sensing</subject><subject>Research facilities</subject><subject>Surface water</subject><subject>Water area</subject><subject>Water levels</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kEtLxDAUhYMoOI4u_AcBd0LHPJqkXcrgCwouVHAX7zTp0Jm2qUmq-O_NMAPuXNxzLpePe-AgdEnJghLJb8SCUCooEUdoRoWgmZJUHqMZIWWesZy_n6KzEDaEsFKpYoY-Kjess2h9j78hGQ6Tb6C2uHdDG51vhzWewk77qYttIvvReehwBYMJEHEa23VttNhABJwuL4negoct7mBrz9FJA12wFwefo7f7u9flY1Y9Pzwtb6tsZISLrFhBLVcsJ5w2hJKyrgGIYUWulDFcGMpVvaK2lrI0whY0J6U0LG2csqYRJZ-jq_3f0bvPyYaoN27yQ4rUTCnJZJ5TkajrPRXqNkJs3aBH3_bgfzQletegFvrQ4H_wl_N_oB5Nw38BUcdxzQ</recordid><startdate>20230214</startdate><enddate>20230214</enddate><creator>Purnama, Yustika</creator><creator>Fauzi, Adam Irwansyah</creator><creator>Nurtyawan, Rian</creator><creator>Sakti, Anjar Dimara</creator><creator>Nuha, Muhammad Ulin</creator><creator>Anika, Nova</creator><creator>Putra, Raden</creator><creator>Siregar, Diyanti Isnani</creator><creator>Prasetyo, Budhi Agung</creator><creator>Julzarika, Atriyon</creator><creator>Wikantika, Ketut</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230214</creationdate><title>Long-term water surface monitoring using multi-temporal Landsat satellite data at Singkarak lake</title><author>Purnama, Yustika ; Fauzi, Adam Irwansyah ; Nurtyawan, Rian ; Sakti, Anjar Dimara ; Nuha, Muhammad Ulin ; Anika, Nova ; Putra, Raden ; Siregar, Diyanti Isnani ; Prasetyo, Budhi Agung ; Julzarika, Atriyon ; Wikantika, Ketut</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p2035-8bac6b24031f0109ccaa0d28477dd35d137cb1ec669d5e814096d25e8312ff593</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Chlorophyll</topic><topic>Landsat 5</topic><topic>Landsat satellites</topic><topic>Monitoring</topic><topic>Remote sensing</topic><topic>Research facilities</topic><topic>Surface water</topic><topic>Water area</topic><topic>Water levels</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Purnama, Yustika</creatorcontrib><creatorcontrib>Fauzi, Adam Irwansyah</creatorcontrib><creatorcontrib>Nurtyawan, Rian</creatorcontrib><creatorcontrib>Sakti, Anjar Dimara</creatorcontrib><creatorcontrib>Nuha, Muhammad Ulin</creatorcontrib><creatorcontrib>Anika, Nova</creatorcontrib><creatorcontrib>Putra, Raden</creatorcontrib><creatorcontrib>Siregar, Diyanti Isnani</creatorcontrib><creatorcontrib>Prasetyo, Budhi Agung</creatorcontrib><creatorcontrib>Julzarika, Atriyon</creatorcontrib><creatorcontrib>Wikantika, Ketut</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Purnama, Yustika</au><au>Fauzi, Adam Irwansyah</au><au>Nurtyawan, Rian</au><au>Sakti, Anjar Dimara</au><au>Nuha, Muhammad Ulin</au><au>Anika, Nova</au><au>Putra, Raden</au><au>Siregar, Diyanti Isnani</au><au>Prasetyo, Budhi Agung</au><au>Julzarika, Atriyon</au><au>Wikantika, Ketut</au><au>Santos, Gil Nonato C.</au><au>Putri, Ratih Fitria</au><au>Tristan, Abraham Cardenas</au><au>Omar, Rohayu Che</au><au>Widodo</au><au>Yokozeki, Tomohiro</au><au>Mustika, I Wayan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Long-term water surface monitoring using multi-temporal Landsat satellite data at Singkarak lake</atitle><btitle>AIP conference proceedings</btitle><date>2023-02-14</date><risdate>2023</risdate><volume>2654</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Singkarak Lake has a central role for the surrounding community. To achieve SDGs Goal 6, Singkarak Lake is decided as one of the fifteen lakes to be managed sustainably based on the Indonesian Lake National Conference 2011. Therefore, this research aims to monitor the surface water area of Singkarak Lake using Landsat 5, 7 and 8 surface reflectance data from 2001 to 2019. The surface water body was extracted using a water detection rule algorithm involving three remote sensing indices, i.e., NDVI, mNDWI and EVI. Furthermore, the result was compared with Joint Research Center Yearly Water Classification History data. The result of two decades monitoring shows that the surface water of Singkarak Lake fluctuated with an average of 10,683 ha. The lowest surface water area was in 2012 with 10,579 ha, while the largest surface water area was in 2019 with 10,754 ha. The comparative analysis obtained an average deviation of 122 ha or 1.13%. From the quantitative aspect, this study has proven that the area of Singkarak Lake is relatively constant. Further study can be improved by involving the water level and qualitative aspects such as chlorophyll-a content.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0115105</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Algorithms Chlorophyll Landsat 5 Landsat satellites Monitoring Remote sensing Research facilities Surface water Water area Water levels |
title | Long-term water surface monitoring using multi-temporal Landsat satellite data at Singkarak lake |
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