{"id":54748,"date":"2023-08-26T05:29:52","date_gmt":"2023-08-26T05:29:52","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/gi3020-raster-data-modelling-syllabus-for-geo-2021-regulation-professional-elective-iii\/"},"modified":"2023-08-26T05:29:52","modified_gmt":"2023-08-26T05:29:52","slug":"gi3020-raster-data-modelling-syllabus-for-geo-2021-regulation-professional-elective-iii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/gi3020-raster-data-modelling-syllabus-for-geo-2021-regulation-professional-elective-iii\/","title":{"rendered":"GI3020: Raster Data Modelling syllabus for Geo 2021 regulation (Professional Elective-III)"},"content":{"rendered":"

Raster Data Modelling detailed syllabus for Geoinformatics Engineering (Geo) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the Geo students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Geoinformatics Engineering 5th Sem scheme and its subjects, do visit Geo 5th Sem 2021 regulation scheme<\/a>. For Professional Elective-III scheme and its subjects refer to Geo Professional Elective-III syllabus scheme<\/a>. The detailed syllabus of raster data modelling is as follows. <\/p>\n

Course Objectives:<\/h4>\n

Download the iStudy App for all syllabus and other updates.<\/a>
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Unit I<\/h4>\n

POINT BASED FUNCTION\tImage – properties – reading – color contrast – histogram – zooming and display -pan operations -pyramids – enhancements – transformation.\n<\/p>\n

Unit II<\/h4>\n

NEIGHBORHOOD AND PROXIMITY ANALYSIS\t8,4 D neighborhood – texture computation – GLCM – distance measurement – buffers (point,line,area).\n<\/p>\n

Unit III<\/h4>\n

Download the iStudy App for all syllabus and other updates.<\/a>
\"Get<\/a><\/h4>\n

Unit IV<\/h4>\n

MULTILAYER MODELING\tImage ratio – indices – normalization – segmentation – similarity measures – maximum likelihood classification.\n<\/p>\n

Unit V<\/h4>\n

STATISTICAL METRICS\tMean – mode – standard deviation – correlation -regression -covariance – kappa statistics -random sample selection.\n<\/p>\n

Course Outcomes:<\/h4>\n

\u2022On completion of the course, the student is expected to<\/p>\n

    \n
  1. Acquaint with the raster data structure and its relevance in from pint based, neighbourhood based and region based geospatial .data analysis<\/li>\n
  2. Understand the various raster based data modeling applied on the earth observation data for resource management<\/li>\n
  3. Evaluate the procedures of spatial data handling using raster data model for solving resource management problems<\/li>\n
  4. Acquire knowledge on the current development, issues methods and solutions in raster data analysis using earth observation data.<\/li>\n
  5. Analyze critically and evaluate methods by applying the knowledge gained and to be a part of innovation and integration of geospatial data modeling<\/li>\n<\/ol>\n

    Text Books:<\/h4>\n

    Download the iStudy App for all syllabus and other updates.<\/a>
    \"Get<\/a><\/h4>\n

    Reference Books:<\/h4>\n
      \n
    1. Digital Image Processing, Rafael C. Gonzalez, Richard E. Woods , Pearson , Fourth edition, 2022.<\/li>\n
    2. Concepts and Techniques in Geographic Information System, C.P Lo., Second Edition, 2016.<\/li>\n
    3. Deep Learning with Python, Manning, Second Edition, 2021.<\/li>\n
    4. Geocomputation with R, Jakub Nowosad, JannesMuenchow, and Robin Lovelace, First Edition, 2020.<\/li>\n
    5. Advance Custom Raster Processing using Python, Jie Zhang, Hao. Available from:<\/li>\n

      Hu.https:\/\/www.esri.com\/content\/dam\/esrisites\/en-us\/events\/conferences\/2020\/developer-summit\/advance-raster-processing-using-python.pdf\n<\/li>\n<\/ol>\n

      For detailed syllabus of all the other subjects of Geoinformatics Engineering 5th Sem, visit Geo 5th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n

      For all Geoinformatics Engineering results, visit Anna University Geo all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"

      Raster Data Modelling detailed syllabus for Geoinformatics Engineering (Geo) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the Geo students. For course […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[80],"tags":[],"class_list":["post-54748","post","type-post","status-publish","format-standard","hentry","category-geo"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/54748","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=54748"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/54748\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=54748"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=54748"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=54748"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}