[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125747-en":3,"doc-seo-125747-105":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},125747,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Wetland mapping using LiDAR and Random Forest machine learning","This thesis presents a wetland mapping approach that integrates LiDAR-derived data with Random Forest machine learning for reliable wetland identification. The work outlines the overall workflow, including data handling, creation and use of indices, and the development of a Random Forest model. It further describes implementation support through an ArcGIS Pro toolbox and evaluates performance through results and discussion, followed by conclusions summarizing findings and practical implications for mapping wetland features.","Wetland mapping using LiDAR and Random Forest machine learning  \nby  \nJade Gerlitz  \nA thesis submitted to the graduate faculty  \nin partial fulfillment of the requirements for the degree of  \nMASTER OF SCIENCE  \nMajor: Agricultural and Biosystems Engineering  \nProgram of Study Committee:  \nAmy Kaleita, Co-major Professor  \nBrian Gelder, Co-major Professor  \nBradley Miller  \nThe student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this thesis. The Graduate College will ensure this thesis is globally accessible and will not permit alterations after a degree is conferred.  \nIowa State University  \nAmes, Iowa  \n2023  \nCopyright © Jade Gerlitz, 2023. All rights reserved.  \nTABLE OF CONTENTS  \nPage  \nACKNOWLEDGMENTS ............................................................................................................. iii  \nABSTRACT................................................................................................................................... iv  \nCHAPTER 1. GENERAL INTRODUCTION ................................................................................1  \nReference ................................................................................................................................... 4  \nCHAPTER 2. WETLAND IDENTIFICATION USING LIDAR AND RANDOM FOREST MACHINE LEARNING .................................................................................................................6  \nIntroduction ............................................................................................................................... 6  \nMethods ..................................................................................................................................... 8  \nData ...................................................................................................................................... 8  \nIndices ................................................................................................................................ 11  \nRandom Forest ................................................................................................................... 19  \nArcGIS Pro Toolbox Creation............................................................................................ 21  \nEvaluation of Approach...................................................................................................... 24  \nResults and Discussion ............................................................................................................ 25  \nResults ................................................................................................................................ 25  \nDiscussion .......................................................................................................................... 28  \nConclusion ............................................................................................................................... 29  \nReference ................................................................................................................................. 30  \nAppendix A. Toolbox Manual ................................................................................................. 31  \nImplementation of Extract Indices Toolbox....................................................................... 31  \nPre-installation instructions ................................................................................................ 32  \nGeoprocessing Instructions ................................................................................................ 36  \nAppendix B. Code ................................................................................................................... 39  \nAppendix C. Research Code.................................................................................................... 48  \nRandom Fo","cbCaipDqyC4deRwP","https://ap.wps.com/l/cbCaipDqyC4deRwP","pdf",1962369,1,64,"English","en",105,"# Acknowledgments\n# Abstract\n# Chapter 1. General Introduction\n## Reference\n# Chapter 2. Wetland Identification Using LiDAR and Random Forest Machine Learning\n## Introduction\n## Methods\n## Data\n## Indices\n## Random Forest\n## ArcGIS Pro Toolbox Creation\n## Evaluation of Approach\n## Results and Discussion\n## Results\n## Discussion\n## Conclusion\n## Reference\n# Appendix A. Toolbox Manual\n## Implementation of Extract Indices Toolbox\n## Pre-installation instructions\n## Geoprocessing Instructions\n# Appendix B. Code\n# Appendix C. Research Code\n## Random Forest Research Code\n## Random Forest Creation Code\n# Chapter 3. General Conclusion","[{\"question\":\"What data source does the thesis use for wetland identification?\",\"answer\":\"The thesis uses LiDAR-derived data as the primary input for identifying wetlands with machine learning.\"},{\"question\":\"How is the Random Forest method applied in the wetland mapping workflow?\",\"answer\":\"A Random Forest model is trained and evaluated as part of the identification process, using engineered indices and the prepared dataset.\"},{\"question\":\"What tools are provided to support implementation of the approach?\",\"answer\":\"The thesis includes an ArcGIS Pro Toolbox and a toolbox manual, along with code and research code in the appendices to support implementation.\"}]","Wetland mapping using LiDAR and Random Forest machine learning | PDF",1785901000,161,{"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},"wetland-mapping-using-lidar-and-random-forest-machine-learning","",{"@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/wetland-mapping-using-lidar-and-random-forest-machine-learning/125747/",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","2026-08-05",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},"What data source does the thesis use for wetland identification?","Question",{"text":75,"@type":76},"The thesis uses LiDAR-derived data as the primary input for identifying wetlands with machine learning.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the Random Forest method applied in the wetland mapping workflow?",{"text":80,"@type":76},"A Random Forest model is trained and evaluated as part of the identification process, using engineered indices and the prepared dataset.",{"name":82,"@type":73,"acceptedAnswer":83},"What tools are provided to support implementation of the approach?",{"text":84,"@type":76},"The thesis includes an ArcGIS Pro Toolbox and a toolbox manual, along with code and research code in the appendices to support implementation.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]