This document represents an aggregation of the best available disaster damages caused by the 2017 Hurricane Maria in Puerto Rico and is an initial assessment of the cost to rebuild a stronger, more resilient Puerto Rico
The project “Making Aceh Safer Through Disaster Risk Reduction In Development (DRR-A)” is designed to make DRR a normal part of the development process established in core functions of Aceh’s local government and their public and private partners.
This assessment was carried out with a view to providing a measured basis for the development of informed recovery and rehabilitation strategies for the province of Nanngroe Aceh Darussalam focusing on two central themes: settlement and livelihood.
This document contains the ten most important management lessons learned over a period of four years by BRR, the coordinating agency responsible for the reconstruction of Aceh and Nias following the 2004 Indian Ocean tsunami.
This report provides a summary of damage of the 2004 Indian Ocean Earthquake and Tsunami in Indonesia at the Kabupaten (district) and Kecamatan (subdistrict) levels. The damage assessment activity focused only on survey/data collection and reporting.
Indonesia - government
International Organization for Migration
This document presents the experience and lessons learned from the implementation of the Earthquake and Tsunami Emergency Support Project (ETESP) housing program carried out by the Asian Development Bank in Indonesia.
This document presents the major challenges in Aceh’s transition and governmental priorities, benchmarks and outcomes in virtually every sector of peace building, recovery and development activity in the aftermath of the 2004 earthquake and tsunami.
Indonesia - government
United Nations - Headquarters
United Nations Children's Fund (Global Headquarters, New York)
Asian Development Bank
United Nations Development Programme - Headquarters
World Bank, the
United Nations Human Settlements Programme - Headquarters
This study analyzed the content of Twitter data collected during Hurricane Harvey to identify the data of the highest relevance for assessing the impacts on infrastructure through automatically grouping the tweets by topics of discussion.