{"title":"landusemix：用于计算土地利用组合的 Python 软件包","authors":"Mehmet Ali Akyol , Sebnem Duzgun , Nazife Baykal","doi":"10.1016/j.softx.2024.101861","DOIUrl":null,"url":null,"abstract":"<div><p>Integrating different land uses within a geographic area is essential to urban planning and development. Accurate and fast land use mix (LUM) measurement is necessary for evaluating urban diversity and sustainability. In this paper, we present <span>landusemix</span>, a Python package developed to calculate LUM using two distinct indices: the Entropy Index and the Herfindahl–Hirschman Index (HHI). The <span>landusemix</span> package provides tools for GIS researchers and urban planners to measure the diversity and concentration of land use. Detailed descriptions of the methodologies employed and examples of practical usage are provided. Researchers can use this package to calculate LUM quickly and in bulk, and its results can be easily incorporated into further analysis.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"27 ","pages":"Article 101861"},"PeriodicalIF":2.4000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002310/pdfft?md5=fa23fe9a4c589220ffdf107239f08a30&pid=1-s2.0-S2352711024002310-main.pdf","citationCount":"0","resultStr":"{\"title\":\"landusemix: A Python package for calculating land use mix\",\"authors\":\"Mehmet Ali Akyol , Sebnem Duzgun , Nazife Baykal\",\"doi\":\"10.1016/j.softx.2024.101861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Integrating different land uses within a geographic area is essential to urban planning and development. Accurate and fast land use mix (LUM) measurement is necessary for evaluating urban diversity and sustainability. In this paper, we present <span>landusemix</span>, a Python package developed to calculate LUM using two distinct indices: the Entropy Index and the Herfindahl–Hirschman Index (HHI). The <span>landusemix</span> package provides tools for GIS researchers and urban planners to measure the diversity and concentration of land use. Detailed descriptions of the methodologies employed and examples of practical usage are provided. Researchers can use this package to calculate LUM quickly and in bulk, and its results can be easily incorporated into further analysis.</p></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"27 \",\"pages\":\"Article 101861\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352711024002310/pdfft?md5=fa23fe9a4c589220ffdf107239f08a30&pid=1-s2.0-S2352711024002310-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711024002310\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711024002310","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
landusemix: A Python package for calculating land use mix
Integrating different land uses within a geographic area is essential to urban planning and development. Accurate and fast land use mix (LUM) measurement is necessary for evaluating urban diversity and sustainability. In this paper, we present landusemix, a Python package developed to calculate LUM using two distinct indices: the Entropy Index and the Herfindahl–Hirschman Index (HHI). The landusemix package provides tools for GIS researchers and urban planners to measure the diversity and concentration of land use. Detailed descriptions of the methodologies employed and examples of practical usage are provided. Researchers can use this package to calculate LUM quickly and in bulk, and its results can be easily incorporated into further analysis.
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SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.
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