vegspec：用 Python 编写的光谱植被指数和转换汇编

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-10-09 DOI:10.1016/j.softx.2024.101928

{"title":"vegspec：用 Python 编写的光谱植被指数和转换汇编","authors":"","doi":"10.1016/j.softx.2024.101928","DOIUrl":null,"url":null,"abstract":"<div><div>The vegspec software package is a Python-based compilation of 1) more than 145 spectral vegetation indices from refereed literature over the past half century and 2) algorithms for several common spectral transformations, including first and second derivatives of reflectance, the logarithm of inverse reflectance and its derivatives, and continuum removal. The software was developed to support analyses of spectral reflectance data from field spectroradiometers and hyperspectral imagers. The outputs are useful for data mining or machine learning studies that relate plant biophysical variables (e.g., leaf chlorophyll content) with vegetative spectral properties.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"vegspec: A compilation of spectral vegetation indices and transformations in Python\",\"authors\":\"\",\"doi\":\"10.1016/j.softx.2024.101928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The vegspec software package is a Python-based compilation of 1) more than 145 spectral vegetation indices from refereed literature over the past half century and 2) algorithms for several common spectral transformations, including first and second derivatives of reflectance, the logarithm of inverse reflectance and its derivatives, and continuum removal. The software was developed to support analyses of spectral reflectance data from field spectroradiometers and hyperspectral imagers. The outputs are useful for data mining or machine learning studies that relate plant biophysical variables (e.g., leaf chlorophyll content) with vegetative spectral properties.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S235271102400298X\",\"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/S235271102400298X","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}

引用次数: 0

摘要

vegspec 软件包是一个基于 Python 的汇编，其中包括：1）过去半个世纪以来参考文献中超过 145 种光谱植被指数；2）几种常见光谱变换的算法，包括反射率的一阶和二阶导数、反向反射率的对数及其导数，以及连续体去除。开发该软件是为了支持对野外光谱辐射计和高光谱成像仪的光谱反射率数据进行分析。其输出结果可用于将植物生物物理变量（如叶片叶绿素含量）与植被光谱特性联系起来的数据挖掘或机器学习研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

vegspec: A compilation of spectral vegetation indices and transformations in Python

The vegspec software package is a Python-based compilation of 1) more than 145 spectral vegetation indices from refereed literature over the past half century and 2) algorithms for several common spectral transformations, including first and second derivatives of reflectance, the logarithm of inverse reflectance and its derivatives, and continuum removal. The software was developed to support analyses of spectral reflectance data from field spectroradiometers and hyperspectral imagers. The outputs are useful for data mining or machine learning studies that relate plant biophysical variables (e.g., leaf chlorophyll content) with vegetative spectral properties.

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

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： 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.