Small Reservoirs Automated Classification using SAR
PLEASE NOTE: Object oriented classification was used to automatically classify water bodies. For this classification the minimal mapping unit of 0.5 ha was not used, because of the possibility of encountering smaller ones, due to the fact that reservoirs become smaller in the dry season. For this demonstration a subset was taken with 55 reservoirs that could be manually digitised that are validated against the base map. 51 reservoirs were automatically extracted with the developed classification method. This has detection rate of 93%.
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| Field | Value |
|---|---|
| Last updated | unknown |
| Created | unknown |
| Format | ZIP |
| License | Creative Commons Attribution 4.0 |
| Created | 1 week ago |
| distribution size | 90.3 MB |
| format | ZIP |
| harvest source | https://development-data-hub-s3-public.s3.amazonaws.com/ddhfiles/143195/geospatial/ESA/ESA-LakeMalawi/1_SMALL_RESERVOIRS/d_automated.zip |
| harvest system reference | https://development-data-hub-s3-public.s3.amazonaws.com/ddhfiles/143195/geospatial/ESA/ESA-LakeMalawi/1_SMALL_RESERVOIRS/d_automated.zip |
| id | d4636c11-edd5-4f29-9b23-eb45b3831c8c |
| metadata modified | 1 week ago |
| package id | 19a5eb5e-58fc-4a12-a9d7-220a13b89ecb |
| position | 3 |
| resource id | 18567c43-f0cc-eb11-bacc-000d3a596ff0 |
| resource type | Download |
| resource unique id | DR0052231 |
| state | active |