{"id":2778182,"date":"2025-04-29T17:26:48","date_gmt":"2025-04-30T00:26:48","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2778182"},"modified":"2025-05-30T12:09:23","modified_gmt":"2025-05-30T19:09:23","slug":"amd-mapping","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping","title":{"rendered":"Mapping the Sources of Acid Mine Drainage (AMD) Using Raster Function Template"},"author":10352,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,22931,22771],"tags":[774672,774652,432762,537362,339872],"industry":[],"product":[36551,36561],"class_list":["post-2778182","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-imagery","category-natural-resources","tag-emit","tag-hyperspectral","tag-image-analyst","tag-raster-function","tag-rft","product-arcgis-online","product-arcgis-pro"],"acf":{"show_article_image":false,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/baner_small.jpg","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/Banner_larger.jpg","authors":[{"ID":10352,"user_firstname":"Hong","user_lastname":"Xu","nickname":"Hong Xu","user_nicename":"hxu","display_name":"Hong Xu","user_email":"hxu@esri.com","user_url":"","user_registered":"2019-12-20 16:44:39","user_description":"Hong Xu is a Principal Software Product Engineer on Esri\u2019s imagery team, where she has been contributing since 1999. Her work focuses on advancing analytical methods for Earth observation data, including image time series (image cubes), hyperspectral imagery, multidimensional raster analysis, and altimetry data. She is passionate about bridging scientific research and software development to help users better understand environmental change through geospatial analysis.","user_avatar":""},{"ID":8452,"user_firstname":"Vinay","user_lastname":"Viswambharan","nickname":"Vinay Viswambharan","user_nicename":"vinayv","display_name":"Vinay Viswambharan","user_email":"vinayv@esri.com","user_url":"https:\/\/www.esri.com\/arcgis-blog\/author\/vinayv\/","user_registered":"2018-10-04 22:28:54","user_description":"Principal Product manager on the Imagery team at Esri, with a zeal for remote sensing, AI and everything imagery.","user_avatar":""}],"short_description":"Leverage ArcGIS Raster Function Template for AMD mapping.","flexible_content":[{"acf_fc_layout":"content","content":"

What is AMD?<\/h2>\n

If you\u2019ve never heard of AMD, you\u2019re not alone. While the term might sound highly technical, it\u2019s something that affects many aspects of daily life. Acid Mine Drainage is a toxic, acidic liquid that forms when sulfide minerals are exposed to air and water. This phenomenon is especially prevalent in abandoned mines and areas where mining has disrupted sulfide-bearing rocks. Unfortunately, AMD doesn\u2019t just stay where it\u2019s formed\u2014it carries heavy metals that can contaminate water, harm aquatic ecosystems, damage infrastructure, and degrade soil health.<\/p>\n

The AMD Assessment Model<\/h2>\n

To address this issue, NASA\u2019s Jet Propulsion Laboratory (JPL) has developed an innovative AMD assessment model. By leveraging mineral products derived from EMIT hyperspectral imagery, this model can classify and map sulfide minerals linked to AMD.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2778362,"id":2778362,"title":"diagtam-2","filename":"diagtam-2.jpg","filesize":10925,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/diagtam-2","alt":"model diagram","author":"10352","description":"","caption":"","name":"diagtam-2","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:37:16","modified":"2025-04-29 23:37:32","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":450,"height":159,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2-213x159.jpg","thumbnail-width":213,"thumbnail-height":159,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","medium-width":450,"medium-height":159,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","medium_large-width":450,"medium_large-height":159,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","large-width":450,"large-height":159,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","1536x1536-width":450,"1536x1536-height":159,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","2048x2048-width":450,"2048x2048-height":159,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","card_image-width":450,"card_image-height":159,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/diagtam-2.jpg","wide_image-width":450,"wide_image-height":159}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

AMD Assessment Function Template<\/h2>\n

We\u2019ve implemented the AMD assessment model as a raster function template<\/a>, making it simple to generate AMD assessment maps based on EMIT mineral products. Specifically, the AMD assessment template is designed to work seamlessly with EMIT L2B Mineral, EMIT L2B Uncertainty and EMIT L2A Mask products to create AMD assessment maps.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2778372,"id":2778372,"title":"function_diagram-2","filename":"function_diagram-2.png","filesize":38565,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/function_diagram-2","alt":"RFT diagram","author":"10352","description":"","caption":"","name":"function_diagram-2","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:38:12","modified":"2025-04-29 23:38:27","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":580,"height":406,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","medium-width":373,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","medium_large-width":580,"medium_large-height":406,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","large-width":580,"large-height":406,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","1536x1536-width":580,"1536x1536-height":406,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","2048x2048-width":580,"2048x2048-height":406,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","card_image-width":580,"card_image-height":406,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/function_diagram-2.png","wide_image-width":580,"wide_image-height":406}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

To demonstrate the power of this AMD assessment template, we used a study area in Iron Mountain Mine, California, to further illustrate the inputs and outputs of this processing templates.<\/p>\n

Input<\/h3>\n
    \n
  1. EMIT L2B \u2013 Mineral ID ( mineral identification variable in which each value corresponds to a specific mineral)<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2778382,"id":2778382,"title":"input_bandid-2","filename":"input_bandid-2.jpg","filesize":19653,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/input_bandid-2","alt":"band ID","author":"10352","description":"","caption":"","name":"input_bandid-2","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:38:47","modified":"2025-04-29 23:38:58","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":300,"height":254,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","medium-width":300,"medium-height":254,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","medium_large-width":300,"medium_large-height":254,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","large-width":300,"large-height":254,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","1536x1536-width":300,"1536x1536-height":254,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","2048x2048-width":300,"2048x2048-height":254,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","card_image-width":300,"card_image-height":254,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_bandid-2.jpg","wide_image-width":300,"wide_image-height":254}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    2. EMIT L2B MIN \u2013 Band Depth ( a variable in which each pixel value describes the abundance of the corresponding material)<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2778312,"id":2778312,"title":"input_banddepth","filename":"input_banddepth.jpg","filesize":17840,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/input_banddepth","alt":"band depth","author":"10352","description":"","caption":"","name":"input_banddepth","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:30:01","modified":"2025-04-29 23:30:14","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":300,"height":252,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","medium-width":300,"medium-height":252,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","medium_large-width":300,"medium_large-height":252,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","large-width":300,"large-height":252,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","1536x1536-width":300,"1536x1536-height":252,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","2048x2048-width":300,"2048x2048-height":252,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","card_image-width":300,"card_image-height":252,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_banddepth.jpg","wide_image-width":300,"wide_image-height":252}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    3. EMIT L2B Uncertainty \u2013 Fit ( a model-fit variable that describes accuracy and reliability of the products)<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2778322,"id":2778322,"title":"input_uncertainty","filename":"input_uncertainty.jpg","filesize":22815,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/input_uncertainty","alt":"Uncertainty Fit","author":"10352","description":"","caption":"","name":"input_uncertainty","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:31:22","modified":"2025-04-29 23:31:40","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":300,"height":253,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","medium-width":300,"medium-height":253,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","medium_large-width":300,"medium_large-height":253,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","large-width":300,"large-height":253,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","1536x1536-width":300,"1536x1536-height":253,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","2048x2048-width":300,"2048x2048-height":253,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","card_image-width":300,"card_image-height":253,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_uncertainty.jpg","wide_image-width":300,"wide_image-height":253}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    4. EMIT L2A \u2013 Quality Masks (a multiband raster in which each band contains image quality indicators, such as clouds and shadows)<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2778332,"id":2778332,"title":"input_qa","filename":"input_qa.jpg","filesize":14849,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/input_qa","alt":"QA mask","author":"10352","description":"","caption":"","name":"input_qa","status":"inherit","uploaded_to":2778182,"date":"2025-04-29 23:32:30","modified":"2025-04-29 23:33:04","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":300,"height":251,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","medium-width":300,"medium-height":251,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","medium_large-width":300,"medium_large-height":251,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","large-width":300,"large-height":251,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","1536x1536-width":300,"1536x1536-height":251,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","2048x2048-width":300,"2048x2048-height":251,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","card_image-width":300,"card_image-height":251,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/input_qa.jpg","wide_image-width":300,"wide_image-height":251}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    Output<\/h3>\n

    The input raster layers are processed using the AMD Assessment template to create thematic rasters with 10 mineral groups associated with acid mine drainage.\u00a0 \u00a0Since EMIT products group minerals into two groups, we process for each group, and two resulted rasters are displayed below:<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2816052,"id":2816052,"title":"result-new1","filename":"result-new1.jpg","filesize":67943,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/imagery\/amd-mapping\/result-new1","alt":"AMD result","author":"10352","description":"","caption":"","name":"result-new1","status":"inherit","uploaded_to":2778182,"date":"2025-05-30 16:38:54","modified":"2025-05-30 16:39:23","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":600,"height":316,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","medium-width":464,"medium-height":244,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","medium_large-width":600,"medium_large-height":316,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","large-width":600,"large-height":316,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","1536x1536-width":600,"1536x1536-height":316,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","2048x2048-width":600,"2048x2048-height":316,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","card_image-width":600,"card_image-height":316,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/result-new1.jpg","wide_image-width":600,"wide_image-height":316}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    Left screenshot displays both Group 1 and Group 2 minerals that are associated with AMD. The top-right screenshot is the Group 1 mineral results at the Iron Mountain mining site, corresponding to the yellow rectangle in the left screenshot. The bottom-right screenshot represents the Group 2 minerals from the same location.<\/p>\n

    Why This Matters<\/h2>\n

    Using the raster function template with the AMD assessment model, researchers and environmental planners can pinpoint potential AMD hotspots more effectively. This means quicker and more informed decisions to mitigate AMD\u2019s impact, protect ecosystems, and prioritize remediation efforts. Whether you\u2019re an environmental scientist, a planner, or just someone passionate about protecting our natural resources, this tool offers a significant step forward in tackling AMD.<\/p>\n

    Getting Started<\/h2>\n

    The Acid Mine Drainage Raster Function Template simplifies complex analysis workflows, empowering users to address critical environmental challenges using EMIT hyperspectral data and ArcGIS capabilities.<\/p>\n

    Want to learn more? Check out the AMD Assessment raster function template<\/a>\u00a0for a step-by-step walkthrough of the process.<\/p>\n

     <\/p>\n"}],"related_articles":[{"ID":2554012,"post_author":"10352","post_date":"2024-11-11 11:57:03","post_date_gmt":"2024-11-11 19:57:03","post_content":"","post_title":"Map Oaks Using AVIRIS Hyperspectral Imagery","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"map-oaks","to_ping":"","pinged":"","post_modified":"2024-11-12 09:59:04","post_modified_gmt":"2024-11-12 17:59:04","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2554012","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":2213372,"post_author":"10352","post_date":"2024-01-02 23:13:20","post_date_gmt":"2024-01-03 07:13:20","post_content":"","post_title":"Cloud-Based Aboveground Biomass Mapping using Landsat and GEDI Data","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"biomass-mapping","to_ping":"","pinged":"","post_modified":"2024-03-15 09:43:53","post_modified_gmt":"2024-03-15 16:43:53","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2213372","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1833172,"post_author":"10352","post_date":"2023-02-05 23:21:24","post_date_gmt":"2023-02-06 07:21:24","post_content":"","post_title":"Create a cloud-free image composite from satellite imagery","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"cloud-free-image-composite","to_ping":"","pinged":"","post_modified":"2024-01-05 15:22:58","post_modified_gmt":"2024-01-05 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