Design and development of land surface temperature calculation plugin of QGIS

Muhammad Rahmahalim, F. Ramdani, A. Rusydi
{"title":"Design and development of land surface temperature calculation plugin of QGIS","authors":"Muhammad Rahmahalim, F. Ramdani, A. Rusydi","doi":"10.1145/3427423.3427432","DOIUrl":null,"url":null,"abstract":"Land Surface Temperature (LST) is the temperature found in the outermost layer of the soil surface. Information about LST is very important because LST is a factor that can influence global climate change. There are several ways that can be used to obtain LST data, one of which is to use data obtained from satellites using the help of a satellite image data processing application such as raster calculator within QGIS. There are various plugins provided by QGIS to help its users. Plugins are additional tools designed to deal with various problems encountered. However, there is currently no plugin that automatically calculates the LST algorithm. LST algorithm calculations performed on the QGIS application still use manual methods so to get LST data requires a complex step to produce LST data. To facilitate the process of getting LST data, a plugin is needed that helps users to automatically calculate LST. In this case, the plugin QGIS to calculate the surface temperature is built using the Python (PyQT for designing the UI and PyQGIS the API for QGIS) with the hope that it can simplify and speed up the process of calculating LST data","PeriodicalId":120194,"journal":{"name":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3427423.3427432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Land Surface Temperature (LST) is the temperature found in the outermost layer of the soil surface. Information about LST is very important because LST is a factor that can influence global climate change. There are several ways that can be used to obtain LST data, one of which is to use data obtained from satellites using the help of a satellite image data processing application such as raster calculator within QGIS. There are various plugins provided by QGIS to help its users. Plugins are additional tools designed to deal with various problems encountered. However, there is currently no plugin that automatically calculates the LST algorithm. LST algorithm calculations performed on the QGIS application still use manual methods so to get LST data requires a complex step to produce LST data. To facilitate the process of getting LST data, a plugin is needed that helps users to automatically calculate LST. In this case, the plugin QGIS to calculate the surface temperature is built using the Python (PyQT for designing the UI and PyQGIS the API for QGIS) with the hope that it can simplify and speed up the process of calculating LST data
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
QGIS中地表温度计算插件的设计与开发
地表温度(Land Surface Temperature, LST)是土壤表面最外层的温度。关于地表温度的信息非常重要,因为地表温度是影响全球气候变化的一个因素。有几种方法可用于获取地表温度数据,其中一种方法是使用卫星图像数据处理应用程序(如QGIS中的光栅计算器)从卫星获得的数据。QGIS提供了各种插件来帮助用户。插件是用来处理遇到的各种问题的附加工具。但是,目前还没有自动计算LST算法的插件。在QGIS应用程序上执行的LST算法计算仍然使用手动方法,因此获得LST数据需要一个复杂的步骤来生成LST数据。为了方便获取LST数据的过程,需要一个插件来帮助用户自动计算LST。在本例中,使用Python (PyQT设计UI, PyQGIS为QGIS提供API)构建了计算地表温度的插件QGIS,希望它能简化和加快地表温度数据的计算过程
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Rank consistency of TOPSIS in mobile based recommendation system Detection of online review spam: a literature review A comparative analysis of usability evaluation methods of academic mobile application: are four methods better? Evaluation of multivariate transductive neuro-fuzzy inference system for multivariate time-series analysis and modelling Comparison of image thresholding and clustering segmentation methods for understanding nutritional content of food images
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1