Over het archief
Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
Dit archief wordt uitgebouwd en beheerd volgens de principes van de Open Access Movement, en het daaruit ontstane Open Archives Initiative.
Basisinformatie over ‘Open Access to scholarly information'.
| one publication added to basket [383013] |
Monitoring trends of mangrove disturbance at the tin mining area of Bangka Island using Landsat time series and Landtrendr
Sari, S.P.; Feyen, J.; Koedam, N.; Van Coillie, F. (2022). Monitoring trends of mangrove disturbance at the tin mining area of Bangka Island using Landsat time series and Landtrendr, in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. IEEE International Symposium on Geoscience and Remote Sensing IGARSS, : pp. 457-460. https://dx.doi.org/10.1109/IGARSS46834.2022.9883322
In: (2022). IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. IEEE International Symposium on Geoscience and Remote Sensing IGARSS. IEEE: USA. ISBN 978-1-6654-2793-7; e-ISBN 978-1-6654-2792-0. https://dx.doi.org/10.1109/IGARSS46834.2022, meer
In: IEEE International Symposium on Geoscience and Remote Sensing IGARSS. IEEE: New York. ISSN 2153-6996, meer
|  |
| Beschikbaar in | Auteurs |
|
Documenttype: Congresbijdrage
|
| Author keywords |
Change detection; Forest disturbance; Google Earth Engine; LandTrendr; Mangroves; Tin mining |
| Abstract |
Open-pit tin mining systems in Bangka Island have an outrageous impact due to massive changes in the landscape. The land clearing process in the coastal area before the mining activity and its tailings might cause the mangrove disruption. However, to date, spatially-distributed information on mangrove disturbance due to mining is limited. This research hence aims to fill this gap using remote sensing technology. Trends/dynamics in mangrove disturbance and recovery are studied for the period 1988 to 2021 using the LandTrendr-algorithm implemented on the Google Earth Engine platform. NBR (Normalized Burn Ratio), NDMI (Normalized Difference Moisture Index), NDVI (Normalized Difference Vegetation Index), and Enhanced Vegetation Index (EVI) were used as vegetation indicators to detect the disturbance in mangroves areas. The results show that a significant disturbance occurred, shown by the decrease in NBR, NDMI, NDVI, and EVI values. Some observation areas are still experiencing ongoing disturbance by the end of observing time (2021). |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
