Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells
Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities’ fundamental characteristics and processes, and of the impact o...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2014-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/9/6/064015 |
| _version_ | 1797747907126886400 |
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| author | Hasi Bagan Yoshiki Yamagata |
| author_facet | Hasi Bagan Yoshiki Yamagata |
| author_sort | Hasi Bagan |
| collection | DOAJ |
| description | Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities’ fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-temporal Landsat data from around 1985–2010 to monitor the spatio-temporal land-cover dynamics of 50 global cities. The maximum-likelihood classification method is applied to Landsat data to define the cities’ urbanized areas at different points in time. Subsequently, 1 km ^2 grid squares with unique cell IDs are designed to link among land-cover maps for spatio-temporal land-cover change analysis. Then, we calculate land-cover category proportions for each map in 1 km ^2 grid cells. Statistical comparison of the land-cover changes in grid square cells shows that urban area expansion in 50 global cities was strongly negatively correlated with forest, cropland and grassland changes. The generated land-cover proportions in 1 km ^2 grid cells and the spatial relationships between the changes of land-cover classes are critical for understanding past patterns and the consequences of urban development so as to inform future urban planning, risk management and conservation strategies. |
| first_indexed | 2024-03-12T15:57:20Z |
| format | Article |
| id | doaj.art-0e9c4b157b73446285aafc636944d9a7 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:57:20Z |
| publishDate | 2014-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-0e9c4b157b73446285aafc636944d9a72023-08-09T14:46:22ZengIOP PublishingEnvironmental Research Letters1748-93262014-01-019606401510.1088/1748-9326/9/6/064015Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cellsHasi Bagan0Yoshiki Yamagata1Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, JapanCenter for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, JapanGlobal urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities’ fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-temporal Landsat data from around 1985–2010 to monitor the spatio-temporal land-cover dynamics of 50 global cities. The maximum-likelihood classification method is applied to Landsat data to define the cities’ urbanized areas at different points in time. Subsequently, 1 km ^2 grid squares with unique cell IDs are designed to link among land-cover maps for spatio-temporal land-cover change analysis. Then, we calculate land-cover category proportions for each map in 1 km ^2 grid cells. Statistical comparison of the land-cover changes in grid square cells shows that urban area expansion in 50 global cities was strongly negatively correlated with forest, cropland and grassland changes. The generated land-cover proportions in 1 km ^2 grid cells and the spatial relationships between the changes of land-cover classes are critical for understanding past patterns and the consequences of urban development so as to inform future urban planning, risk management and conservation strategies.https://doi.org/10.1088/1748-9326/9/6/064015urban growthLandsatland coverchange analysisgrid cells |
| spellingShingle | Hasi Bagan Yoshiki Yamagata Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells Environmental Research Letters urban growth Landsat land cover change analysis grid cells |
| title | Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells |
| title_full | Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells |
| title_fullStr | Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells |
| title_full_unstemmed | Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells |
| title_short | Land-cover change analysis in 50 global cities by using a combination of Landsat data and analysis of grid cells |
| title_sort | land cover change analysis in 50 global cities by using a combination of landsat data and analysis of grid cells |
| topic | urban growth Landsat land cover change analysis grid cells |
| url | https://doi.org/10.1088/1748-9326/9/6/064015 |
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