Please note that there are still documents that are required to be submitted via e-mail after filling up both forms above.
Digital terrain model in flood monitoring registration#
The LiDAR Data Request form is for everyone who is requesting existing LiDAR Data and has filled up the LiDAR Data Requester Registration Form.
Existing data requesters who have requested via e-mail prior to Jmust fill up this form for new data requests. Every data requester is required to fill up this form in order to request data using the Data Request Form. The LiDAR Data Requester Form is for everyone who is requesting existing LiDAR Data as seen in the coverage map above. Since the LiPAD Portal is under maintenance, may we request all data requests be coursed through the following Google Forms: LiDAR Data Requester Registration Form Please see the RESOURCE MAPS menu above if you are interested on obtaining resource maps. Resource Maps are available on their respective portals produced by the components of the PHIL-LiDAR 2 Program. Please proceed to the FMC sub-website if you are interested on downloading Flood Hazard Maps. We finish by summarizing some current efforts by national and international organizations to estimate flood hazard as well as to monitor and forecast floods in real-time, and discussing perspectives on how current and future satellite missions, in combination with models, could help to mitigate flood related disasters in Brazil.How to request LiDAR Data Flood Hazard Mapsįlood Hazard Maps are still available at the LiPAD FMC website, without registration. Cross-scale comparisons between global, regional, and local flood models in Brazilian rivers also provide valuable insights on the capabilities of current models, showing, for example, that more distributed information of cross-sections are needed to achieve better predictions. Innovative methods include estimation of river cross-section parameters with data assimilation and genetic calibration algorithms, and floodplain topography estimation based on detailed in situ survey as well as on a combination of water mask and water level time series. Then, some examples of recent advances on the use of RS data for improving models are presented. Models have been validated with remotely sensed water levels and flood extent mainly for large natural wetlands in the Amazon. A systematic literature review of current flood model applications in the country using RS showed that flood extent and satellite altimetry data have been underused, in particular at local scales. Here we present some recent lessons from Brazil regarding the use of RS in improving flood models across scales. In the last decades, RS has provided new opportunities for improving flood models from local to global scales, especially in regions with large and sparsely gauged river systems. However, less research attention has been given to the floods with socioeconomic impacts.
In Brazil, a substantial understanding of flooding regimes in large natural wetlands, as in the Amazon and Pantanal regions, has been promoted through remote sensing (RS) and river flood modeling.
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