Nicolas Cattaneo, Rasmus Astrup, Clara Antón-Fernández
{"title":"PixSim: Enhancing high-resolution large-scale forest simulations","authors":"Nicolas Cattaneo, Rasmus Astrup, Clara Antón-Fernández","doi":"10.1016/j.simpa.2024.100695","DOIUrl":null,"url":null,"abstract":"<div><p>PixSim is a flexible, open-source forest growth simulator designed to operate at the pixel level of high-resolution, wall-to-wall forest resource maps generated through remote sensing approaches. PixSim addresses the need to adapt forest growth simulators to the data produced by modern remote sensing-based forest inventories, rather than relying on stand-level averages from traditional field-based inventories. By operating at the pixel level, PixSim captures intra-stand variability in high-resolution forest resource maps, which is often overlooked by stand-level simulators. This capability aligns with the current focus on precision forestry, aimed at improving management decisions with localized data and small-scale management. Implemented in the R programming language, PixSim features minimal package dependencies, provides flexibility and scalability, and has been optimized for high-resolution, large-scale simulations, ensuring efficient computation. The simulator’s flexibility and open-source nature support the incorporation of management modules and the inclusion of climate change scenarios in simulations.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":"21 ","pages":"Article 100695"},"PeriodicalIF":1.3000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000836/pdfft?md5=607affcb7b08c73e36361ba980a6ef08&pid=1-s2.0-S2665963824000836-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963824000836","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
PixSim is a flexible, open-source forest growth simulator designed to operate at the pixel level of high-resolution, wall-to-wall forest resource maps generated through remote sensing approaches. PixSim addresses the need to adapt forest growth simulators to the data produced by modern remote sensing-based forest inventories, rather than relying on stand-level averages from traditional field-based inventories. By operating at the pixel level, PixSim captures intra-stand variability in high-resolution forest resource maps, which is often overlooked by stand-level simulators. This capability aligns with the current focus on precision forestry, aimed at improving management decisions with localized data and small-scale management. Implemented in the R programming language, PixSim features minimal package dependencies, provides flexibility and scalability, and has been optimized for high-resolution, large-scale simulations, ensuring efficient computation. The simulator’s flexibility and open-source nature support the incorporation of management modules and the inclusion of climate change scenarios in simulations.