{"id":792,"date":"2018-09-02T20:32:51","date_gmt":"2018-09-02T19:32:51","guid":{"rendered":"http:\/\/jenacopterlabs.de\/?page_id=792"},"modified":"2018-09-02T20:47:55","modified_gmt":"2018-09-02T19:47:55","slug":"imprs-summerschool-2018","status":"publish","type":"page","link":"https:\/\/jenacopterlabs.de\/?page_id=792","title":{"rendered":"IMPRS Summerschool 2018"},"content":{"rendered":"

IMPRS 2018 MPI BGC Jena, 3.9.2018<\/strong><\/p>\n

PD Dr. S. Hese (Friedrich-Schiller-University Jena, Department for Earth Observation, soeren.hese@uni-jena.de)<\/strong><\/p>\n

Introduction to image processing for Earth observation data analysis:\u00a0<\/strong>– Landcover Classification and Multispectral Data Analysis using the ENVI\/IDL Image Processing Environment <\/strong><\/p>\n

Data: Landsat TM5 subset (LS-TM5-02071993-SUBSET-UTM32.envi.hdr), 30 m spatial resolution, UTM 32, Datum:WGS84, BSQ file structure.<\/p>\n

 <\/p>\n

ENVI 5.4 Hands-On Exercises: <\/u><\/p>\n

    \n
  1. Software Environment Setup:\n
      \n
    1. ENVI working directory setup<\/li>\n
    2. ENVI .hdr & external format import ()<\/li>\n
    3. Linking displays within ENVI<\/li>\n
    4. Window Management in ENVI Classic<\/li>\n<\/ol>\n<\/li>\n
    5. Subsetting\n
        \n
      1. Data spectral sub-setting (deleting channel 6)<\/li>\n
      2. Spatial sub-setting using ROI Tools<\/li>\n<\/ol>\n<\/li>\n
      3. Header Data Analysis\n
          \n
        1. spectral properties,<\/li>\n
        2. geocoding information,<\/li>\n
        3. header information,<\/li>\n
        4. band statistics & histograms,<\/li>\n
        5. band scatterplots<\/li>\n
        6. BSQ \/BIL Setup<\/li>\n<\/ol>\n<\/li>\n
        7. Data Preprocessing\n
            \n
          1. Orthocorrection & ATCOR (demo in PCI EASI\/PACE)<\/li>\n
          2. Contrast stretching \/ histogram modifications on display and with LUT<\/li>\n
          3. Filtering with spatial filters, low pass, high pass, custom filter functions)<\/li>\n<\/ol>\n<\/li>\n
          4. Texture filtering with Co-Occurrence masks<\/li>\n
          5. \u201cBand Math\u201d tool syntax (IDL) and NDVI calculation into a new floating point image file<\/li>\n
          6. Landcover classification\n
              \n
            1. Preparation and design of ROIs for supervised classification,<\/li>\n<\/ol>\n<\/li>\n
            2. ROI management<\/li>\n
            3. Signature separabilit<\/li>\n
            4. Scatterplot visualisation<\/li>\n
            5. n-dimensional visualization<\/li>\n<\/ol>\n
                \n
                  \n
                1. Maximum likelihood classification with ROIs<\/li>\n
                2. Calculation of area statistics from thematic classification results<\/li>\n<\/ol>\n<\/ol>\n

                  Post-classification analysis \u2013 confusion matrix using ROI ground truth<\/p>\n

                  IMPRS2018-ENVI54.zip<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

                  IMPRS 2018 MPI BGC Jena, 3.9.2018 PD Dr. S. Hese (Friedrich-Schiller-University Jena, Department for Earth Observation, soeren.hese@uni-jena.de) Introduction to image processing for Earth observation data analysis:\u00a0– Landcover Classification and Multispectral Data Analysis using the ENVI\/IDL Image Processing Environment Data: Landsat TM5 subset (LS-TM5-02071993-SUBSET-UTM32.envi.hdr), 30 m spatial resolution, UTM 32, Datum:WGS84, BSQ file structure.   ENVI 5.4 Hands-On Exercises: Software Environment...<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":18,"menu_order":7,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":"","footnotes":""},"class_list":["post-792","page","type-page","status-publish","hentry"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"post-thumbnail":false,"cd-small":false,"cd-medium":false,"cd-standard":false},"uagb_author_info":{"display_name":"S\u00f6ren Hese","author_link":"https:\/\/jenacopterlabs.de\/?author=1"},"uagb_comment_info":0,"uagb_excerpt":"IMPRS 2018 MPI BGC Jena, 3.9.2018 PD Dr. S. Hese (Friedrich-Schiller-University Jena, Department for Earth Observation, soeren.hese@uni-jena.de) Introduction to image processing for Earth observation data analysis:\u00a0– Landcover Classification and Multispectral Data Analysis using the ENVI\/IDL Image Processing Environment Data: Landsat TM5 subset (LS-TM5-02071993-SUBSET-UTM32.envi.hdr), 30 m spatial resolution, UTM 32, Datum:WGS84, BSQ file structure.   ENVI…","_links":{"self":[{"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/pages\/792","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=792"}],"version-history":[{"count":6,"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/pages\/792\/revisions"}],"predecessor-version":[{"id":798,"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/pages\/792\/revisions\/798"}],"up":[{"embeddable":true,"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=\/wp\/v2\/pages\/18"}],"wp:attachment":[{"href":"https:\/\/jenacopterlabs.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=792"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}