[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120337-en":3,"doc-seo-120337-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120337,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Ecosystem classification using machine learning - Master’s thesis","Ecosystems sustain essential resources and influence human health, motivating the need to assess ecosystem condition in the face of global change. The planetary boundaries framework links stability and resilience to nine key processes, noting that six boundaries had been crossed by 2023. With Europe’s nature restoration law setting restoration targets, ecosystem health evaluation becomes a prerequisite for restoration. Remote sensing enables detection of ecosystems and their temporal change using satellite light measurements. This thesis applies Random Forest and SVM models on Sentinel-2 data processed in Google Earth Engine, with Random Forest achieving the best validation accuracy (90.8%) and strong training performance (89.6%).","Master’s thesis  \nNT NU  \nNorwegian Un ivers ity of Science and Technology Faculty of Information Technology and Electrical Engineering  \nSeyedramin Mortazavi  \nEcosystem classification using machine learning  \nMaster’s thesis in Simulation and Visualization Supervisor: Agus Hasan  \nCo-supervisor: Arron Wilde Tippett January 2022  \nSeyedramin Mortazavi  \nEcosystem classification using machine learning  \nMaster’s thesis in Simulation and Visualization Supervisor: Agus Hasan  \nCo-supervisor: Arron Wilde Tippett January 2022  \nNorwegian University of Science and Technology  \nFaculty of Information Technology and Electrical Engineering  \nABSTRACT  \nEcosystems are a crucial part of Earth and they provide essential resources and also affect human health in various ways. The planetary boundaries framework proposed by a team of scientists at at Stockholm Resilience Centre; it rooted in Earth system science, identifies nine pivotal processes crucial for maintaining the stability and resilience of the planet. According to the boundaries 6 boundaries have crossed by 2023 . Europe has introduced a nature restoration law which sets targets for restoring ecosystems. In order to restore an ecosystem first we have to assess its health. Remote sensing can be used for the detection of ecosystems and their changes during time in order to assess the change in its health. Satellites can be used to get the data by measuring the amount of light reflected from the surface of the earth in various frequencies. Machine learning methods have been a popular tool in remote sensing helping with the detection of different ecosystems and studying them. In this project machine learning methods of Random Forests and SVM were used to classify land types in Norway. This algorithms were implemented on the data from sentinel-2 satellite, and Google earth engine platform was used for processing the data, training the models and visualization. The random forests model yielded the best result, with 90.8% accuracy for validation data and 89.6% for training.  \nSAMMENDRAG  \nØkosystemer er en avgjørende del av jorden, og de gir essensielle ressurser samtidig som de påvirker menneskers helse på ulike måter. rammeverket for planetariske grenser, foreslått av et team av forskere ved Stockholm Resilience Centre, forankret i jordens systemvitenskap, identifiserer ni avgjørende prosesser som eravgjørende for å opprettholde planetens stabilitet og motstandskraft. Ifølge rammeverket har 6 grenser blitt krysset innen 2023 . Europa har innført en lov om naturgjenoppretting som fastsetter mål for å gjenopprette økosystemer. For å gjenopprette et økosystem må vi først vurdere helsen. Fjernmåling kan brukes til å oppdage økosystemer og deres endringer over tid for å vurdere endringen ihelsen deres. Satellitter kan brukes til å skaffe data ved å måle mengden lys som reflekteres fra jordoverflaten i ulike frekvenser. Maskinlæringsmetoder har vært et populært verktøy innen fjernmåling for å hjelpe med å oppdage ulike økosystemer og studere dem. I dette prosjektet ble maskinlæringsmetodene Random Forests og SVM brukt til å klassifisere landtyper i Norge. Disse algoritmene ble implementertpå data fra Sentinel-2-satellitten, og Google Earth Engine-plattformen ble brukt til å behandle data, trene modellene og visualisere resultatene. Random Forestsmodellen ga det beste resultatet, med en nøyaktighet på 90,8% for valideringsdata og 89,6% for treningsdata.  \nPREFACE  \nI want to thank everyone who helped me finish my master’s thesis. This project involved a lot of research, thinking, and looking back on things, and I couldn’t have completed it without the support and guidance of many people. Firstly, a big thankyou to my supervisors. They were always there for me, sharing their knowledge and encouraging me. Their advice helped shape my thesis into its final version. And, of course, a shoutout to the teachers and professors at NTNU for creating a great academic environment and providing resource","cbCaihJpBgfcr9aa","https://ap.wps.com/l/cbCaihJpBgfcr9aa","pdf",20215966,1,56,"English","en",105,"# Contents\n## Abstract and Sammendrag\n## Preface and Contents\n## List of Figures\n## 1 Introduction\n## 2 Theory","[{\"question\":\"Why is ecosystem health assessment important in the thesis?\",\"answer\":\"Ecosystems provide essential resources and affect human health, and restoration efforts require evaluating ecosystem health first.\"},{\"question\":\"How does the project use remote sensing and satellite data?\",\"answer\":\"It uses Sentinel-2 satellite measurements of reflected light across different frequencies to detect ecosystems and track changes over time.\"},{\"question\":\"Which machine learning models are used, and how did Random Forest perform?\",\"answer\":\"Random Forest and SVM are used to classify land types in Norway. Random Forest produced the best results with 90.8% validation accuracy and 89.6% training accuracy.\"}]","Ecosystem classification using machine learning - Master’s thesis | PDF",1785729554,141,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"ecosystem-classification-using-machine-learning-masters-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/ecosystem-classification-using-machine-learning-masters-thesis/120337/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is ecosystem health assessment important in the thesis?","Question",{"text":75,"@type":76},"Ecosystems provide essential resources and affect human health, and restoration efforts require evaluating ecosystem health first.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the project use remote sensing and satellite data?",{"text":80,"@type":76},"It uses Sentinel-2 satellite measurements of reflected light across different frequencies to detect ecosystems and track changes over time.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning models are used, and how did Random Forest perform?",{"text":84,"@type":76},"Random Forest and SVM are used to classify land types in Norway. 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