{"title":"CataEx: A multi-task export tool for the Google Earth Engine data catalog","authors":"Gisela Domej , Kacper Pluta , Marek Ewertowski","doi":"10.1016/j.envsoft.2024.106227","DOIUrl":null,"url":null,"abstract":"<div><div>Satellite imagery is provided by different missions such as ASTER, MODIS, Sentinel, Landsat, IKONOS, GeoEye, SPOT, WorldView, Pléaides, or RapidEye. One of the major encumbrances is the digital volume that satellite imagery claims during download, storage, and processing. This inconvenience has been overcome since 2010 by the Google Earth Engine, a cloud-based platform for global geospatial analysis dedicated to users who are not necessarily remote sensing specialists.</div><div>However, compatibility with traditional desktop or web-based GIS software remains tricky as bringing satellite imagery from the Google Earth Engine to another software requires a coded export via JavaScript or Python.</div><div>We present the multi-functional code tool CataEx in JavaScript to exemplify several essential types of computations (i.e., filtering of image collections, cloud masking, index and histogram generation, and layer creation) before exporting images as GeoTIFFs. CataEx is kept deliberately simple without much \"sophisticated\" code language to allow JavaScript beginners to get familiar with basic coding concepts and develop their own scripts.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"183 ","pages":"Article 106227"},"PeriodicalIF":4.8000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815224002883","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Satellite imagery is provided by different missions such as ASTER, MODIS, Sentinel, Landsat, IKONOS, GeoEye, SPOT, WorldView, Pléaides, or RapidEye. One of the major encumbrances is the digital volume that satellite imagery claims during download, storage, and processing. This inconvenience has been overcome since 2010 by the Google Earth Engine, a cloud-based platform for global geospatial analysis dedicated to users who are not necessarily remote sensing specialists.
However, compatibility with traditional desktop or web-based GIS software remains tricky as bringing satellite imagery from the Google Earth Engine to another software requires a coded export via JavaScript or Python.
We present the multi-functional code tool CataEx in JavaScript to exemplify several essential types of computations (i.e., filtering of image collections, cloud masking, index and histogram generation, and layer creation) before exporting images as GeoTIFFs. CataEx is kept deliberately simple without much "sophisticated" code language to allow JavaScript beginners to get familiar with basic coding concepts and develop their own scripts.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.