Sabaragamuwa University of Sri Lanka

Constructing an Index to Measure the Aggregate Capacity to Climate Change in Sri Lanka

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dc.contributor.author Thathsarani, U.S
dc.contributor.author Gunaratne, L.H.P
dc.date.accessioned 2021-01-05T16:21:38Z
dc.date.available 2021-01-05T16:21:38Z
dc.date.issued 2016-12-15
dc.identifier.isbn 978-955-644-052-2
dc.identifier.uri http://repo.lib.sab.ac.lk:8080/xmlui/handle/123456789/280
dc.description.abstract Climate change is considered as the major threat to the human beings in the future. Vulnerability to the climate change refers to the potential of a system to be harmed by an external threat and it is a function of exposure, sensitivity to impacts and the ability or lack of ability to cope or adapt. Adaptive capacity represents the ability of a region or community to cope with and thrive in the face of change. Communities vary in their physical exposure to threats, and it is widely recognized that adaptation is place, culture, and issue specific. This means that strategies to facilitate and enhance adaptive capacity also must attend to context and recognize that capacities do not exist or are not developed uniformly across all communities. In this context, an attempt has been made to construct index to measure the adaptive capacity for the district level aggregate data. The data were obtained from Sri Lanka Household and Expenditure Survey results in 2009/2010, covering 25000 households. Constructing index raises several problems in the aggregation including the decision of assigning weights to the selected assets. One purpose of this research is to demonstrate a method of aggregating adaptive capacity indicators that result in a composite index. Weighted Principal Components Analysis (WPCA) is performed on assets and variables for the indicators in district level aggregation data. Constructed index shown in the analysis that the positive relationship between adaptive capacity and social assets are clearly followed by economic assets and physical assets, but human assets have been attributed a negative association. Batticaloa, Jaffna, Ampara, Moneragala, Trincomalee, Vavuniya and Puttlam districts had lower adaptive capacity, along with Colombo and Gampaha had a higher level of adaptive capacity. en_US
dc.language.iso en_US en_US
dc.publisher Sabaragamuwa University of Sri Lanka en_US
dc.subject Adaptive Capacity en_US
dc.subject Climate Change en_US
dc.subject Cumulative en_US
dc.subject Weighted Principal Component en_US
dc.title Constructing an Index to Measure the Aggregate Capacity to Climate Change in Sri Lanka en_US
dc.type Article en_US


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  • ARS 2016 [25]
    Annual Research sessions held in the year 2016

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