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place <br /> County of Hawaii General Plan Comprehensive Review <br /> Trend Scenario and Land Use Allocation Technical Report <br /> Date: April 18, 2016 <br /> Authors: Amy DeBay, Ian Varley, Doug Walker <br /> Introduction <br /> Task S2 (Land Use Allocation)sets up a framework for estimating future development patterns <br /> (amounts and location) based on a set of rules. Task E (Trend Scenario) uses an initial, calibrated run of <br /> the allocation model to estimate future development patterns based on historical trends. These tasks <br /> go hand-in-hand and are combined in this technical report. <br /> Allocation Concepts and Approach <br /> Future development patterns(amounts and location)are estimated using an algorithm-driven process <br /> called allocation. Allocation models the interplay between market demand for development in certain <br /> locations("desirability")and amount of development allowed according to current regulations or by <br /> future land use patterns suggested by alternate scenarios("capacity"). Given a pre-determined amount <br /> of growth expected in the given time frame (here, new growth between 2015 and 2040),the allocation <br /> process estimates where each incremental unit of new development will go,following the basic <br /> presumption that the most desirable areas will be developed first, capacity allowing. Thus highly <br /> desirable areas are assigned growth first, and then slightly less desirable areas get developed next, etc., <br /> until all the estimated growth amount has been accommodated. Numerous refinements to the basic <br /> principle are used to produce the final estimates. For example, parcels aren't always filled all the way to <br /> capacity, a certain amount of controlled"randomness"is often applied to the growth pattern, etc. For <br /> mixed use areas, both residential and non-residential growth can be assigned. <br /> In this study, a CommunityViz tool called Allocatorg is used. The methods combined with the <br /> algorithms in Allocator 5 provide a well-reasoned analysis that will be helpful for this and myriad other <br /> planning studies, but it is recognized that the results have limitations in terms of modelling precision <br /> and confidence. The CommunityViz allocation method is sometimes described as"light-weight"to <br /> "medium-weight,"differentiating it from the"heavy-weight"algorithms such as UrbanSim or PECAS <br /> that are considerably more sophisticated but are more difficult and expensive to implement. In <br /> contrast, the Allocator 5 method is easier to use and lends itself well to"what-if"type scenario <br /> planning. <br /> At the highest level,the allocation algorithm takes 3 inputs—growth amount, capacity, and <br /> desirability—and generates i output—a pattern of future development. Our methods for each of these <br /> are described next. <br /> Growth Amount <br /> As a 201.5 baseline for housing unit data, Placeways used data from the County's Real Property Tax <br /> (RPT)office to identify the number of housing units and non-residential square feet. The procedure <br /> began with a database file from RPT that, unfortunately, lacked metadata, so the fields were <br /> interpreted manually. For each TMK, buildings were converted to housing units where appropriate <br /> Trend Scenario and Land Use Allocation Technical Report 1 <br />