Landsat image time series (1988-2020) of the Modified Soil Adjusted Vegetation Index (MSAVI) for change detection in the eastern Hindu Kush
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| Natura: | Dataset Open Access |
| Lingua: | en |
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PANGAEA
2021
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| _version_ | 1867171029839773696 |
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| author | Khan, Saeed Akhtar Vanselow, Kim A Sass, Oliver Samimi, Cyrus |
| author_facet | Khan, Saeed Akhtar Vanselow, Kim A Sass, Oliver Samimi, Cyrus |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Based on Landsat satellite imagery we set up a 32-year raster image time series. Due to the arid environment soil noise is an issue therefore we calculated the MSAVI. We carried out the following steps: 1. Data was pre-processed for clouds removal using quality assessment bands, 2. Valleys were extracted using buffers along the river network while non-vegetated areas such as glaciers and mountain slopes were masked out, 3. Breaks for Additive Season and Trend (BFAST) was applied to detect timing, magnitude, and number of breakpoints in the trend component of the time series. The dataset is suitable to analyze land cover change and detect the impacts of disasters in the eastern Hindu Kush region. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_937677 |
| institution | PANGAEA |
| language | en |
| publishDate | 2021 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Landsat image time series (1988-2020) of the Modified Soil Adjusted Vegetation Index (MSAVI) for change detection in the eastern Hindu Kush Khan, Saeed Akhtar Vanselow, Kim A Sass, Oliver Samimi, Cyrus BFAST; breakpoint; Land cover change; Pakistan; remote sensing Based on Landsat satellite imagery we set up a 32-year raster image time series. Due to the arid environment soil noise is an issue therefore we calculated the MSAVI. We carried out the following steps: 1. Data was pre-processed for clouds removal using quality assessment bands, 2. Valleys were extracted using buffers along the river network while non-vegetated areas such as glaciers and mountain slopes were masked out, 3. Breaks for Additive Season and Trend (BFAST) was applied to detect timing, magnitude, and number of breakpoints in the trend component of the time series. The dataset is suitable to analyze land cover change and detect the impacts of disasters in the eastern Hindu Kush region. |
| title | Landsat image time series (1988-2020) of the Modified Soil Adjusted Vegetation Index (MSAVI) for change detection in the eastern Hindu Kush |
| topic | BFAST; breakpoint; Land cover change; Pakistan; remote sensing |
| url | https://doi.org/10.1594/PANGAEA.937677 |