@Article{pakinsight,
AUTHOR = {},
TITLE = {Post Disaster Recovery Process of Landslides in Developing Countries: A Case Study of Aranayake Landslide - Sri Lanka},
JOURNAL = {Review of Environment and Earth Sciences},
VOLUME = {6},
YEAR = {2019},
NUMBER = {1},
PAGES = {14-23},
URL = {http://www.pakinsight.com/archive/80/03-2019/1},
ISSN = {2313-8440},
ABSTRACT = {The basic principle for the recovery of residential area from a landslide disaster is restoring the damaged area to its condition before the disaster. This study focuses on evaluates the recovery process and reinstallation of pre-disaster economic functions after the landslide occurred in the year 2016 at Aranayake, Sri Lanka. Estimated values of the collapsed infrastructure is 7,806 USD, and the affected region generates 200 000 USD for the annual country GDP. In contrast, 887 families directly or indirectly affected by the landslide. The primary data were obtained from comprehensive questioner survey of affected household (n=120), semi-structured focused group discussions, and key informant discussions. Recovery was assumed as a function of emergency recovery (ER), infrastructure resettlement (IR) and long-term recovery (LtR). Correlation analysis and multiple regression analysis were used to model the association between dependent variable Recovery and independent variables ER, IR and LtR. The findings revealed that, there is no systematic procedure used to monitor the progress of recovery programme. LtR has a profoundly positive effect on recovery with compared to IR and ER. Results suggest that ER and IR are individually insignificant but they effect on recovery jointly. Multiple regression model can be expressed as Recovery = 0.205+ 0.640ER + 0.124IR + 0.249LtR. The finding of this study is recommended to establish an institutional framework to monitor, evaluate and rectify the disaster recovery process with standardized indicators, procedures, and guidelines. Further, it is recommended to adopt a community based long-term recovery approach for sustainable landslide disaster recovery. },
DOI = {10.18488/journal.80.2019.61.14.23}
}