Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method
Ulaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-10-01
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| Series: | Land |
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| Online Access: | http://www.mdpi.com/2073-445X/2/4/534 |
| _version_ | 1819145093548867584 |
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| author | Reiichiro Ishii Izuru Saizen Masayuki Matsuoka Narumasa Tsutsumida |
| author_facet | Reiichiro Ishii Izuru Saizen Masayuki Matsuoka Narumasa Tsutsumida |
| author_sort | Reiichiro Ishii |
| collection | DOAJ |
| description | Ulaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the central part of Ulaanbaatar, which has been affected by anthropogenic disturbances. The breaks for additive seasonal and trend (BFAST) method is a powerful tool for implementing this study because it is able to robustly and automatically derive the timing and locations of land cover changes from spatio-temporal datasets. We applied the BFAST method for the first time to urban expansion analysis, with NDVI time series calculated from MODIS (MOD09A1 product) during the period 2000–2010. The results show that land cover has changed across 22.51% of the study area, and that the change occurs at a later time with increasing distance from the city center. Bi-temporal high-resolution satellite images of a sample area in 2000 and 2008 confirmed that the detection of land cover changes by BFAST corresponds to areas in which residential development is dominant. This study demonstrates that BFAST is an effective method for monitoring urban expansion. In addition, it increases the applicability of NDVI time series. |
| first_indexed | 2024-12-22T12:52:33Z |
| format | Article |
| id | doaj.art-feaeab44428347ca8448a575b83586ea |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-12-22T12:52:33Z |
| publishDate | 2013-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-feaeab44428347ca8448a575b83586ea2022-12-21T18:25:12ZengMDPI AGLand2073-445X2013-10-012453454910.3390/land2040534Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend MethodReiichiro IshiiIzuru SaizenMasayuki MatsuokaNarumasa TsutsumidaUlaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the central part of Ulaanbaatar, which has been affected by anthropogenic disturbances. The breaks for additive seasonal and trend (BFAST) method is a powerful tool for implementing this study because it is able to robustly and automatically derive the timing and locations of land cover changes from spatio-temporal datasets. We applied the BFAST method for the first time to urban expansion analysis, with NDVI time series calculated from MODIS (MOD09A1 product) during the period 2000–2010. The results show that land cover has changed across 22.51% of the study area, and that the change occurs at a later time with increasing distance from the city center. Bi-temporal high-resolution satellite images of a sample area in 2000 and 2008 confirmed that the detection of land cover changes by BFAST corresponds to areas in which residential development is dominant. This study demonstrates that BFAST is an effective method for monitoring urban expansion. In addition, it increases the applicability of NDVI time series.http://www.mdpi.com/2073-445X/2/4/534urban expansionland cover change detectionNDVI time seriesMODISUlaanbaatar |
| spellingShingle | Reiichiro Ishii Izuru Saizen Masayuki Matsuoka Narumasa Tsutsumida Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method Land urban expansion land cover change detection NDVI time series MODIS Ulaanbaatar |
| title | Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method |
| title_full | Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method |
| title_fullStr | Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method |
| title_full_unstemmed | Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method |
| title_short | Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method |
| title_sort | land cover change detection in ulaanbaatar using the breaks for additive seasonal and trend method |
| topic | urban expansion land cover change detection NDVI time series MODIS Ulaanbaatar |
| url | http://www.mdpi.com/2073-445X/2/4/534 |
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