title: Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale

authors: Schicker, Renee Deborah

subjects: landslide susceptibility

abstract: Landslide susceptibility assessment was undertaken for the Waikato Region, New Zealand. Landslide inventory data were extracted from a pre-existing database that included few landslides in the region (1.4% of area), and is limited in terms of completeness of record and location uncertainty. This database is in contrast to those normally used for research, which are derived for the research project and are complete and accurate, but is representative of those that may exist within government bodies. This paper applies statistical methods to derive a meaningful predictive map for planning purposes from such a relatively poorly defined database. Susceptibility maps for both logistic regression and weights of evidence were derived and evaluated using success, prediction, and ROC curves. Both statistical methods gave models with fair predictive capacity for validation samples from the original database with areas under ROC curves (AUC) of 0.71 to 0.75. An independent set of landslide data compiled from observations made in Google Earth showed lower overall prediction quality, with the logistic regression method giving the best prediction (AUC = 0.71). For this regional assessment, categorical data proved a major constraint on the application of logistic regression as the area considered has complex geology and geomorphology. As a result, the large number of categories required led to a complex and unwieldy statistical model, whereas division into fewer categories meant that real variability in the area could not be adequately represented. This limited the result to a model with two continuous variables, slope and mean monthly rainfall. The incomplete record in the database proved of little concern for the logistic regression method as the model was able to generalise landslide locations from the known sites well, giving a similar AUC value for the original and independent data; the same was not true for the weights of evidence method which was not successful at predicting landslides outside those in the original data.

text: Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale Landslide susceptibility assessment was undertaken for the Waikato Region, New Zealand. Landslide inventory data were extracted from a pre-existing database that included few landslides in the region (1.4% of area), and is limited in terms of completeness of record and location uncertainty. This database is in contrast to those normally used for research, which are derived for the research project and are complete and accurate, but is representative of those that may exist within government bodies. This paper applies statistical methods to derive a meaningful predictive map for planning purposes from such a relatively poorly defined database. Susceptibility maps for both logistic regression and weights of evidence were derived and evaluated using success, prediction, and ROC curves. Both statistical methods gave models with fair predictive capacity for validation samples from the original database with areas under ROC curves (AUC) of 0.71 to 0.75. An independent set of landslide data compiled from observations made in Google Earth showed lower overall prediction quality, with the logistic regression method giving the best prediction (AUC = 0.71). For this regional assessment, categorical data proved a major constraint on the application of logistic regression as the area considered has complex geology and geomorphology. As a result, the large number of categories required led to a complex and unwieldy statistical model, whereas division into fewer categories meant that real variability in the area could not be adequately represented. This limited the result to a model with two continuous variables, slope and mean monthly rainfall. The incomplete record in the database proved of little concern for the logistic regression method as the model was able to generalise landslide locations from the known sites well, giving a similar AUC value for the original and independent data; the same was not true for the weights of evidence method which was not successful at predicting landslides outside those in the original data.

year: 2012

title: Energy cultures: Implication for policymakers

authors: Barton, Barry

abstract: The Energy Cultures research project (2009-2012) was planned to help inform policy making related to residential energy use and energy efficiency in New Zealand. It sought, in part, to help address the difficulties faced by government agencies in achieving the economically viable potential for residential electricity savings. In particular, the project set out to examine household energy behaviour in relation to space heating and hot water heating, which together account for around 60% of household energy use. The programme was designed as a number of discrete research projects, linked together by the Energy Cultures conceptual framework. This report presents the policy implications of the multiple findings of that research.

text: Energy cultures: Implication for policymakers The Energy Cultures research project (2009-2012) was planned to help inform policy making related to residential energy use and energy efficiency in New Zealand. It sought, in part, to help address the difficulties faced by government agencies in achieving the economically viable potential for residential electricity savings. In particular, the project set out to examine household energy behaviour in relation to space heating and hot water heating, which together account for around 60% of household energy use. The programme was designed as a number of discrete research projects, linked together by the Energy Cultures conceptual framework. This report presents the policy implications of the multiple findings of that research.

year: 2013

title: Hōmai te Waiora ki Ahau: te ara whakamua - towards the establishment of construct validity

authors: Palmer, Stephanie

abstract: Hōmai te Waiora ki Ahau: te ara
whakamua, is about the development of a
tool to measure psychological wellbeing
among Māori. Why is it relevant? Because
a quick look at the June 2002 edition of
New Zealand’s Journal of Psychology will
show you that the wellbeing measures
being used in this country are not responsive to the needs of
Māori, are not based on Māori concepts or
Constructs, do not facilitate Māori participation in
te ao Māori and do not provide pathways through
which Māori can develop a positive Māori
identity.
It is highly unlikely that the tools
which psychologists use to measure
wellbeing among Māori will help Māori to
experience whānau ora and that, as we all
know, is the paramount health objective for
Māori (Ministry of Health, 2002). In this
regard, it would seem that the powers that
be in psychology are failing to meet their
Treaty obligations to Māori. Therefore,
Hōmai te Waiora ki Ahau simply aims to assist change. This presentation will briefly
describe the context of the development of
this measure, the methodologies used to
develop this tool, the outcomes of a small
pilot-study, and current challenges and
future directions for Hōmai te Waiora ki
Ahau.

text: Hōmai te Waiora ki Ahau: te ara whakamua - towards the establishment of construct validity Hōmai te Waiora ki Ahau: te ara
whakamua, is about the development of a
tool to measure psychological wellbeing
among Māori. Why is it relevant? Because
a quick look at the June 2002 edition of
New Zealand’s Journal of Psychology will
show you that the wellbeing measures
being used in this country are not responsive to the needs of
Māori, are not based on Māori concepts or
Constructs, do not facilitate Māori participation in
te ao Māori and do not provide pathways through
which Māori can develop a positive Māori
identity.
It is highly unlikely that the tools
which psychologists use to measure
wellbeing among Māori will help Māori to
experience whānau ora and that, as we all
know, is the paramount health objective for
Māori (Ministry of Health, 2002). In this
regard, it would seem that the powers that
be in psychology are failing to meet their
Treaty obligations to Māori. Therefore,
Hōmai te Waiora ki Ahau simply aims to assist change. This presentation will briefly
describe the context of the development of
this measure, the methodologies used to
develop this tool, the outcomes of a small
pilot-study, and current challenges and
future directions for Hōmai te Waiora ki
Ahau.

year: 2003