Investigating adoption patterns of residential low impact development (LID) using classification trees

Domenico C. Amodeo () and Royce A. Francis ()
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Domenico C. Amodeo: The George Washington University
Royce A. Francis: The George Washington University

Environment Systems and Decisions, 2019, vol. 39, issue 3, 295-306

Abstract: Abstract Local governments are under pressure to improve storm water management and often times must comply with consent decrees with the Federal Government. Decentralizing a portion of the storm water management by integrating private landowners into localized retention and infiltration efforts, that is, low impact development (LID) or green infrastructure projects, is becoming increasingly popular. Some wastewater systems have considered incentivizing private land owners to make improvements aimed at retaining storm water or slowing the conveyance to grey infrastructure. This study examines potential opportunities for incentivizing private residential land owners in Washington DC to install LID projects. This study maps LID configurations to a set of adoption strategies and categories. The C4.5 algorithm is then applied to identify a high performance decision tree for classifying parcels by adoption strategy or adoption categories based on property-level attributes.

Keywords: Low impact development; Storm water retention; Environmental policy; Landscaping; Decision trees; Machine learning; Best management practices; Green roofs; Combined sewage overflow; Urban planning; Water quality; Storm water management; Impervious; Permeable; LID; Rain barrels; Infiltration; Run-off; CSO; Adopters; green city; C4.5 algorithm (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10669-019-09725-3

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