促进城市屋顶农业的决策支持和规划工具

Mritika Contractor, Gabriella Luna, Shreya N. Patel, Sophie Steinberg
{"title":"促进城市屋顶农业的决策支持和规划工具","authors":"Mritika Contractor, Gabriella Luna, Shreya N. Patel, Sophie Steinberg","doi":"10.1109/SIEDS49339.2020.9106586","DOIUrl":null,"url":null,"abstract":"There is an increasing trend among urban populations to recognize the importance of fresh produce in their diets and its impact on reducing the carbon footprint created by food transportation. Thus, urban farming as a produce source has grown in popularity in recent years. One farming method that is gaining attention is urban rooftop farming, which integrates farming practices into city infrastructure without requiring expensive real estate or large warehouse-type structures with interior grow lighting. Rooftops in American cities represent the largest unoccupied urban space for agricultural purposes, but they remain underutilized. Selection of feasible and safe locations, obtaining permissions, designing and constructing the farm itself, selecting appropriate crops, and projecting farm outputs are all complex issues that impede the adoption of rooftop farming. To address such complexity, this project developed a prototype Decision Support and Planning Tool that assesses rooftop feasibility, supports informed and geographically appropriate rooftop farm design and crop selection, and predicts crop yield. The team implemented requirements analysis and functional decomposition to identify structural, safety and access requirements for rooftop farming. A second phase of the requirements analysis and functional decomposition was performed to identify agricultural methods and farm design. As a result, “square foot farming” was selected as the appropriate basis for farm and tool design. Users are also guided to input their desired level of effort for maintenance, time to maturity, and crop yield to identify crops most suitable to the specific rooftop location. Analytic hierarchy process (AHP) was used to scale and calculate the weights associated with the users’ maintenance preferences. A linear programming model based on knapsack optimization was used to project maximum total yield based on available square footage and crop yield preferences. Two proof-of-concept rooftop farms, generated by the prototype Decision Support and Planning Tool, were constructed in Washington, DC and Los Angeles. Prior to the spread of COVID-19, these farms were intended to validate model results against actual yield from crops produced over a 90day growing horizon. Instead, the farms validated rooftop assessment and crop selection tool functions.","PeriodicalId":331495,"journal":{"name":"2020 Systems and Information Engineering Design Symposium (SIEDS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Decision Support and Planning Tool to Facilitate Urban Rooftop Farming\",\"authors\":\"Mritika Contractor, Gabriella Luna, Shreya N. Patel, Sophie Steinberg\",\"doi\":\"10.1109/SIEDS49339.2020.9106586\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is an increasing trend among urban populations to recognize the importance of fresh produce in their diets and its impact on reducing the carbon footprint created by food transportation. Thus, urban farming as a produce source has grown in popularity in recent years. One farming method that is gaining attention is urban rooftop farming, which integrates farming practices into city infrastructure without requiring expensive real estate or large warehouse-type structures with interior grow lighting. Rooftops in American cities represent the largest unoccupied urban space for agricultural purposes, but they remain underutilized. Selection of feasible and safe locations, obtaining permissions, designing and constructing the farm itself, selecting appropriate crops, and projecting farm outputs are all complex issues that impede the adoption of rooftop farming. To address such complexity, this project developed a prototype Decision Support and Planning Tool that assesses rooftop feasibility, supports informed and geographically appropriate rooftop farm design and crop selection, and predicts crop yield. The team implemented requirements analysis and functional decomposition to identify structural, safety and access requirements for rooftop farming. A second phase of the requirements analysis and functional decomposition was performed to identify agricultural methods and farm design. As a result, “square foot farming” was selected as the appropriate basis for farm and tool design. Users are also guided to input their desired level of effort for maintenance, time to maturity, and crop yield to identify crops most suitable to the specific rooftop location. Analytic hierarchy process (AHP) was used to scale and calculate the weights associated with the users’ maintenance preferences. A linear programming model based on knapsack optimization was used to project maximum total yield based on available square footage and crop yield preferences. Two proof-of-concept rooftop farms, generated by the prototype Decision Support and Planning Tool, were constructed in Washington, DC and Los Angeles. Prior to the spread of COVID-19, these farms were intended to validate model results against actual yield from crops produced over a 90day growing horizon. Instead, the farms validated rooftop assessment and crop selection tool functions.\",\"PeriodicalId\":331495,\"journal\":{\"name\":\"2020 Systems and Information Engineering Design Symposium (SIEDS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Systems and Information Engineering Design Symposium (SIEDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIEDS49339.2020.9106586\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Systems and Information Engineering Design Symposium (SIEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIEDS49339.2020.9106586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

越来越多的城市人口认识到新鲜农产品在他们饮食中的重要性及其对减少食品运输产生的碳足迹的影响。因此,近年来,城市农业作为一种农产品来源越来越受欢迎。一种受到关注的耕作方法是城市屋顶耕作,它将耕作实践与城市基础设施相结合,不需要昂贵的房地产或带有室内种植照明的大型仓库式结构。美国城市的屋顶是最大的未被利用的城市农业空间,但它们仍未得到充分利用。选择可行和安全的地点,获得许可,设计和建造农场本身,选择合适的作物,以及预测农场产出,这些都是阻碍屋顶农业采用的复杂问题。为了解决这种复杂性,该项目开发了一个原型决策支持和规划工具,用于评估屋顶可行性,支持知情且地理位置合适的屋顶农场设计和作物选择,并预测作物产量。该团队实施了需求分析和功能分解,以确定屋顶农场的结构、安全和访问要求。第二阶段进行需求分析和功能分解,以确定农业方法和农场设计。因此,“平方英尺农业”被选为农场和工具设计的适当基础。用户还被引导输入他们所需的维护工作水平、成熟时间和作物产量,以确定最适合特定屋顶位置的作物。采用层次分析法(AHP)对用户维护偏好的权重进行量化和计算。采用基于背包优化的线性规划模型,根据可用面积和作物产量偏好来预测最大总产量。由决策支持和规划工具原型生成的两个概念验证屋顶农场分别在华盛顿特区和洛杉矶建成。在COVID-19传播之前,这些农场旨在根据90天生长周期内生产的作物的实际产量验证模型结果。相反,农场验证了屋顶评估和作物选择工具的功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision Support and Planning Tool to Facilitate Urban Rooftop Farming
There is an increasing trend among urban populations to recognize the importance of fresh produce in their diets and its impact on reducing the carbon footprint created by food transportation. Thus, urban farming as a produce source has grown in popularity in recent years. One farming method that is gaining attention is urban rooftop farming, which integrates farming practices into city infrastructure without requiring expensive real estate or large warehouse-type structures with interior grow lighting. Rooftops in American cities represent the largest unoccupied urban space for agricultural purposes, but they remain underutilized. Selection of feasible and safe locations, obtaining permissions, designing and constructing the farm itself, selecting appropriate crops, and projecting farm outputs are all complex issues that impede the adoption of rooftop farming. To address such complexity, this project developed a prototype Decision Support and Planning Tool that assesses rooftop feasibility, supports informed and geographically appropriate rooftop farm design and crop selection, and predicts crop yield. The team implemented requirements analysis and functional decomposition to identify structural, safety and access requirements for rooftop farming. A second phase of the requirements analysis and functional decomposition was performed to identify agricultural methods and farm design. As a result, “square foot farming” was selected as the appropriate basis for farm and tool design. Users are also guided to input their desired level of effort for maintenance, time to maturity, and crop yield to identify crops most suitable to the specific rooftop location. Analytic hierarchy process (AHP) was used to scale and calculate the weights associated with the users’ maintenance preferences. A linear programming model based on knapsack optimization was used to project maximum total yield based on available square footage and crop yield preferences. Two proof-of-concept rooftop farms, generated by the prototype Decision Support and Planning Tool, were constructed in Washington, DC and Los Angeles. Prior to the spread of COVID-19, these farms were intended to validate model results against actual yield from crops produced over a 90day growing horizon. Instead, the farms validated rooftop assessment and crop selection tool functions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信