Malaysia environment data

# EOS-RS Flood Proxy Map: Malaysia, Floods, Dec 2021, v0.4 The Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS) created this preliminary Flood Proxy Map (FPM) depicting areas that are likely flooded in north and central Peninsular Malaysia due to heavy rains. This map was derived from synthetic aperture radar (SAR) images acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (9 Dec 2021) and during (21 Dec 2021) the event. The image covers an area indicated by the large white polygon. Each light blue pixel measures about 30 meters across. This flood proxy map should be used as a guide to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. Sentinel-1 data were accessed through the Copernicus Open Hub and AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). The product contains modified Copernicus Sentinel data (2021), processed by ESA and analyzed by the Earth Observatory of Singapore - Remote Sensing Lab (EOS-RS), using the Advanced Rapid Imaging and Analysis (ARIA) system originally developed at NASA's Jet Propulsion Laboratory, California Institute of Technology, and modified at EOS-RS. **More map details and files:** **More map details and files:**

# ARIA-SG Flood Proxy Map: Malaysia, Floods, 7 Jan 2021, v0.7 Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) from 1 Jan 2020 to 7 Jan 2021. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS) in collaboration with NASA-JPL and Caltech. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds). **More map details and files:** **More map details and files:**

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.