<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-22T00:11:14Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/111512" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/111512</identifier><datestamp>2026-06-06T00:55:18Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Dennis McLaughlin.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Kaneshiro, Jonathan Takao</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Civil and Environmental Engineering</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="accessioned">2017-09-15T15:37:27Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2017-09-15T15:37:27Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/111512</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1003324217</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2017.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 105-110).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">For over 50 years in The State of Hawai'i, the issues of food self sufficiency and environmental resource protection have been called for, but not necessarily addressed in a quantitative manner. These concerns have been key priorities in The State of Hawai'i Constitution, Hawai'i 2050 Sustainability Plan, Hawai'i County Development Plan and various Community Development Plans. As Hawaiian agriculture transitions from industrial mono-cropping plantation landscapes to small stakeholder farms, it is more important than ever to challenge these issues in the most efficient and sustainable way that is conscious of both environmental resources and resident values. This thesis aims to quantitatively allocate land and environmental resources using a representative entropy-based optimization model, which is formulated to maintain biodiversity while maximizing food self-sufficiency. Rigorous methods to quantify biophysical, water and land resources are implemented to ensure a robust output of optimal cropping areas on a pixel basis. Tradeoff curves are generated comparing fractions of land needed for agricultural expansion, self-sufficient population in fruits and vegetables and total entropy of Hawai'i Island. Results show that Hawai'i Island could sustain up to 6M people in fruits and vegetables, while maintaining the highest spatial heterogeneity and biodiversity. The high populations, however, should be assessed with regard to the cropping land expansions and changes in landscape, as these tradeoffs may outweigh the benefits.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Jonathan Takao Kaneshiro.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">M.Eng.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">110 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Civil and Environmental Engineering.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Optimal land allocation for Hawaiian agriculture using an entropy-based approach</dim:field>
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   	&lt;Title>Optimal land allocation for Hawaiian agriculture using an entropy-based approach&lt;/Title>
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   	&lt;PublicationDate>2017&lt;/PublicationDate>
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        	&lt;DisplayName>Kaneshiro, Jonathan Takao&lt;/DisplayName>
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    &lt;Keyword>Civil and Environmental Engineering.&lt;/Keyword&gt;
   	&lt;Abstract>For over 50 years in The State of Hawai&amp;apos;i, the issues of food self sufficiency and environmental resource protection have been called for, but not necessarily addressed in a quantitative manner. These concerns have been key priorities in The State of Hawai&amp;apos;i Constitution, Hawai&amp;apos;i 2050 Sustainability Plan, Hawai&amp;apos;i County Development Plan and various Community Development Plans. As Hawaiian agriculture transitions from industrial mono-cropping plantation landscapes to small stakeholder farms, it is more important than ever to challenge these issues in the most efficient and sustainable way that is conscious of both environmental resources and resident values. This thesis aims to quantitatively allocate land and environmental resources using a representative entropy-based optimization model, which is formulated to maintain biodiversity while maximizing food self-sufficiency. Rigorous methods to quantify biophysical, water and land resources are implemented to ensure a robust output of optimal cropping areas on a pixel basis. Tradeoff curves are generated comparing fractions of land needed for agricultural expansion, self-sufficient population in fruits and vegetables and total entropy of Hawai&amp;apos;i Island. Results show that Hawai&amp;apos;i Island could sustain up to 6M people in fruits and vegetables, while maintaining the highest spatial heterogeneity and biodiversity. The high populations, however, should be assessed with regard to the cropping land expansions and changes in landscape, as these tradeoffs may outweigh the benefits.&lt;/Abstract>
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