{"id":54942,"date":"2019-04-19T10:51:39","date_gmt":"2019-04-19T17:51:39","guid":{"rendered":"https:\/\/www.esri.com\/about\/newsroom\/?post_type=arcuser&p=54942"},"modified":"2024-05-07T10:13:58","modified_gmt":"2024-05-07T17:13:58","slug":"imagery-and-gis-best-practices-for-extracting-information-from-imagery","status":"publish","type":"arcuser","link":"https:\/\/www.esri.com\/about\/newsroom\/arcuser\/imagery-and-gis-best-practices-for-extracting-information-from-imagery","title":{"rendered":"Imagery and GIS: Best Practices for Extracting Information from Imagery"},"author":1432,"featured_media":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"sync_status":"","episode_type":"","audio_file":"","podmotor_file_id":"","podmotor_episode_id":"","castos_file_data":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","_links_to":"","_links_to_target":""},"categories":[10892,551],"tags":[178472,178462,241,10332],"arcuser_issues":[23202],"class_list":["post-54942","arcuser","type-arcuser","status-publish","format-standard","hentry","category-esri-press","category-imagery","tag-best-practices","tag-book","tag-gis","tag-imagery","arcuser_issues-winter-2018"],"acf":{"short_description":"Imagery and GIS have a symbiotic relationship: Imagery is the foundation of most GIS datasets, and GIS can be used to more effectively manage\u2026","pdf":{"host_remotely":false,"file":"","file_url":""},"flexible_content":[{"acf_fc_layout":"content","content":"Imagery and GIS have a symbiotic relationship: Imagery is the foundation of most GIS datasets, and GIS can be used to more effectively manage and derive information from imagery."},{"acf_fc_layout":"image","image":54952,"image_position":"right","orientation":"vertical","hyperlink":""},{"acf_fc_layout":"content","content":"Imagery and GIS: Best Practices for Extracting Information from Imagery<\/a><\/em>\u00a0provides GIS users with the knowledge to make informed decisions about working and processing imagery; extracting information from it; and assessing, publishing, and serving imagery datasets.\r\n\r\nThis book is especially valuable given the recent significant improvements in the availability, cost, and spectral and spatial resolution of remotely sensed data<\/a> and the proliferation of remote-sensing devices. For civilian uses, the availability of remotely sensed data has exploded owing to the evolution of sensors, the development of smaller and more agile platforms such as drones, the improved positional accuracy of GPS, and decreases in the cost of storage on disk and in the cloud.\r\n\r\nImagery and GIS together support an increasing number of vital applications for environmental management, humanitarian aid, public safety, climate monitoring, transportation, agriculture, and many other industries. These applications will only expand in scope and importance in the future.\r\n\r\nThe book\u2019s first section introduces the fundamental concepts of imagery. It covers how remotely sensed data is collected and the characteristics of that data. With this foundation, the final chapter of the section explains how to select the most appropriate imagery for an application.\r\n\r\nThe other three sections address in very practical terms how to use imagery, extract information from it, and manage image and GIS data. The topics covered include digital elevation models, image classification, change analysis, and accuracy assessment.\r\n\r\nNumerous screen captures, diagrams, charts, and graphs illustrate the concepts discussed, and a glossary of terms and lists of acronyms and references enhance comprehension.\r\n\r\nImagery and GIS Web App, an Esri Story Map app developed to provide current information on the use of and availability of high to moderate resolution data from remote sensing satellites in service can be accessed at esriurl.com\/IGT42.\r\n\r\nThe authors have decades of experience working with imagery and GIS in research, real-world applications, and teaching.\r\n\r\nKass Green\u2019s career in remote sensing and GIS spans more than 30 years. She has worked for nongovernmental organizations (NGOs), public agencies, and private companies throughout the world. This work has included innovative research, multiscale and multisensor mapping projects; strategic planning; policy analysis; and decision support tools development.\r\n\r\nDr. Russell G. Congalton, a professor of remote sensing and GIS at the University of New Hampshire, has more than 35 years of experience teaching and researching geospatial technologies and working for private industry, federal and state agencies, and academia.\r\n\r\nMark Tukman, the owner of Tukman Geospatial in Santa Rosa, California, has more than 20 years\u2019 experience using imagery and other datasets to help public and private organizations map land cover, make decisions using spatial data, and support land conservation efforts.\u00a0Esri Press, 2017, 435 pp., ISBN: 9781589484894<\/a>."},{"acf_fc_layout":"pdf","file":55022}],"references":null},"yoast_head":"\nImagery and GIS: Best Practices for Extracting Information from Imagery | Winter 2018 | ArcUser<\/title>\n<meta name=\"description\" content=\"Imagery and GIS have a symbiotic relationship: Imagery is the foundation of most GIS datasets, and GIS can be used to more effectively manage and derive information from imagery.\" \/>\n<meta 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