{"_id":"597a120e70fc9c003827519f","project":"55faeacad0e22017005b8265","version":{"_id":"55faeacad0e22017005b8268","project":"55faeacad0e22017005b8265","__v":33,"createdAt":"2015-09-17T16:31:06.800Z","releaseDate":"2015-09-17T16:31:06.800Z","categories":["55faeacbd0e22017005b8269","55faf550764f50210095078e","55faf5b5626c341700fd9e96","55faf8a7825d5f19001fa386","560052f91503430d007cc88f","560054f73aa0520d00da0b1a","56005aaf6932a00d00ba7c62","56005c273aa0520d00da0b3f","5601ae7681a9670d006d164d","5601ae926811d00d00ceb487","5601aeb064866b1900f4768d","5601aee850ee460d0002224c","5601afa02499c119000faf19","5601afd381a9670d006d1652","561d4c78281aec0d00eb27b6","561d588d8ca8b90d00210219","563a5f934cc3621900ac278c","5665c5763889610d0008a29e","566710a36819320d000c2e93","56ddf6df8a5ae10e008e3926","56e1c96b2506700e00de6e83","56e1ccc4e416450e00b9e48c","56e1ccdfe63f910e00e59870","56e1cd10bc46be0e002af26a","56e1cd21e416450e00b9e48e","56e3139a51857d0e008e77be","573b4f62ef164e2900a2b881","57c9d1335fd8ca0e006308ed","57e2bd9d1e7b7220000d7fa5","57f2b992ac30911900c7c2b6","58adb5c275df0f1b001ed59b","58c81b5c6dc7140f003c3c46","595412446ed4d9001b3e7b37"],"is_deprecated":false,"is_hidden":false,"is_beta":false,"is_stable":true,"codename":"v1","version_clean":"1.0.0","version":"1"},"category":{"_id":"573b4f62ef164e2900a2b881","__v":0,"project":"55faeacad0e22017005b8265","version":"55faeacad0e22017005b8268","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-05-17T17:05:38.443Z","from_sync":false,"order":7,"slug":"algorithm-guide","title":"Certified Algorithms"},"user":"55fae9d4825d5f19001fa379","__v":0,"parentDoc":null,"updates":[],"next":{"pages":[],"description":""},"createdAt":"2017-07-27T16:17:18.493Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"settings":"","results":{"codes":[]},"auth":"required","params":[],"url":""},"isReference":false,"order":7,"body":"## Table of Contents\n\n\nSection | Description\n--- | ---\n[Imagery Examples](#Imagery Examples) | Before and after examples\n[Quickstart](#Quickstart) | Get started with a Python-based quickstart tutorial\n[Task Runtime](#Task Runtime) | Benchmark runtimes for the algorithm\n[Input Options](#Input Options) | Required and optional task inputs\n[Outputs](#Outputs) | Task outputs and example contents\n[Advanced Options](#Advanced Options) | Additional information for advanced users\n[Known Issues](#Known Issues) | Issues users should be aware of\n\n\n## <a name=\"Imagery Examples\"></a>Imagery Examples\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/b1181e1-SF_Final_1B_Animations.gif\",\n        \"SF_Final_1B_Animations.gif\",\n        609,\n        800,\n        \"#233e3f\"\n      ],\n      \"caption\": \"This 5 second animation shows the two unprocessed 1B multispectral images in geotiff format\"\n    }\n  ]\n}\n[/block]\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/7db9ad5-AOP_Animation.gif\",\n        \"AOP_Animation.gif\",\n        565,\n        909,\n        \"#203023\"\n      ],\n      \"caption\": \"Intermediate: These are the same two images after running the Advanced Image Preprocessor. These will be used as inputs for the Change Detection Preparation task\"\n    }\n  ]\n}\n[/block]\n\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/8571709-SF_Final_cd_prep_Animations.gif\",\n        \"SF_Final_cd_prep_Animations.gif\",\n        526,\n        678,\n        \"#192811\"\n      ],\n      \"caption\": \"After: This 5 second animation shows the 2 output files from the Change Detection Preparation task called pre_image_cdprep.tif and post_image_cdprep.tif\"\n    }\n  ]\n}\n[/block]\n\n## <a name=\"Quickstart\"></a>Quickstart Tutorial\n\n\nExample Script: Run in a python environment (i.e. - IPython) using the gbdxtools interface.\n\nThese basic settings will run cd_prep from a pair of input orthorectified, AComped image output from the Advanced Image Preprocessor. See also examples listed under the [Advanced Options](#advanced-options).\n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"# Run The Change Detection Preparation Task on a pair of images\\nfrom gbdxtools import Interface\\ngbdx = Interface()\\n\\n# The data input and lines must be edited to point to an authorized customer S3 location)\\ncd_prep = gbdx.Task('cd_prep', \\n                    pre_image_dir='s3://gbd-customer-data/CustomerAccount#/PathToPreImage/',\\n                    post_image_dir='s3://gbd-customer-data/CustomerAccount#/PathToPostImage')\\n    \\nworkflow = gbdx.Workflow([cd_prep])\\n#Edit the following line(s) to reflect specific folder(s) for the output file (example location provided)\\nworkflow.savedata(cd_prep.outputs.final_pre_image_dir, location='CDPrep/pre_image_dir')\\nworkflow.savedata(cd_prep.outputs.final_post_image_dir, location='CDPrep/post_image_dir')\\nworkflow.execute()\\n\\nprint workflow.id\\nprint workflow.status\",\n      \"language\": \"python\"\n    }\n  ]\n}\n[/block]\n**Example Run in IPython:**\n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"**Example Run in IPython:**\\n\\n    In [1]: from gbdxtools import Interface\\n    In [2]: gbdx = Interface()\\n    In [3]: cd_prep = gbdx.Task('cd_prep', \\n                                 pre_image_dir='s3://gbd-customer-data/7d8cfdb6-13ee-4a2a-bf7e-0aff4795d927/jkoenig/cd_prep_test/Borneo/test2/AOP/pre/', \\n                                 post_image_dir = 's3://gbd-customer-data/7d8cfdb6-13ee-4a2a-bf7e-0aff4795d927/jkoenig/cd_prep_test/Borneo/test2/AOP/post/')\\n    In [4]: workflow = gbdx.Workflow([cd_prep])\\n    In [5]: workflow.savedata(cd_prep.outputs.final_pre_image_dir, location='cd_prep_test/pub_test/pre_image_dir')\\n    In [6]: workflow.savedata(cd_prep.outputs.final_post_image_dir, location='cd_prep_test/pub_test/post_image_dir')\\n    In [7]: workflow.execute()\\n    Out [7]: \\n    u'4498407427801810318'\\n    In [8]: print workflow.status\\n    {u'state': u'running', u'event': u'started'} [9]:\",\n      \"language\": \"python\"\n    }\n  ]\n}\n[/block]\n## <a name=\"Task Runtime\"></a>Task Runtime\nThere is no benchmark runtime data for this task. Standard benchmarks are sensor-specific, and this task can take images from multiple sensors.\n\n## <a name=\"Input Options\"></a>Input Options\n\nThis task takes as input two orthorectified, atmospherically compensated images in geotiff format.\nIt is intended to work as a following task to the Advanced Image Preprocessor (AOP_Strip_Processor,) with only the AComp option specified.\n\n**Description of Basic Input Parameters for the Change Detection Preparation GBDX task**\n\nThe following table lists the cd_prep GBDX inputs.\nAll inputs are optional with default values, with the exception of\n'pre_image_dir', 'post_image_dir', 'final_pre_image_dir', and 'final_post_image_dir'\nwhich specify the task's input and output data locations.\n\nName        | Required             |       Default         |        Valid Values             |   Description\n------------|-------------|:---------------------:|---------------------------------|-----------------\npre_image_dir   | Yes     |  N/A  |  S3 URL | Pre-image input directory containing one or more TIFF files\npost_image_dir   |  Yes     | N/A  |  S3 URL | Post-image input directory containing one or more TIFF files\n\n\n## <a name=\"Outputs\"></a>Outputs\n\nOn completion, the processed imagery will be written to your specified S3 Customer \nLocation (i.e., s3://gbd-customer-data/unique customer id/pre_image_dir/, s3://gbd-customer-data/unique customer id/post_image_dir/).\nEach output directory will contain a single geotiff file with one of the names: pre_image_cdprep.tif or post_image_cdprep.tif.\n\n\nName        | Required             |       Default         |        Valid Values             |   Description\n------------|-------------|:---------------------:|---------------------------------|-----------------\nfinal_pre_image_dir |  Yes    |N/A | S3 URL | Pre-image output directory for cd_prep\nfinal_post_image_dir | Yes     |N/A | S3 URL | Post-image output directory for cd_prep \n\n\n\n## <a name=\"Advanced Options\"></a>Advanced Options\n\nThe options in the following table provide additional control over the resulting output.  All of the directories are generally\nfor diagnostic purposes.\n\nName                     |       Default         |        Valid Values             |   Description\n-------------------------|:---------------------:|---------------------------------|-----------------\nbuffer_in_meters   |   1500.0  |  string | Amount in meters by which to buffer the intersection polygon of the initial crop\nresampling_method   |   near  |  string | Method for resampling the images to a common grid.  Choices are 'near', 'bilinear', 'cubic', 'cubicspline', 'lanczos', 'average' \nresolution_in_meters   |   2.0  |  string | The resolution in meters of the pair of output images\nenable_cloud_mask   |   true |  string | Enable/disable cloud mask. Choices are 'true' or 'false'\nshrink_buffer_in_meters   |   0.0  |  string | Distance in meters by which to shrink the final intersection polygon for final crop\ncrop_pre_image_dir | N/A | S3 URL | Pre-image output directory for the cropping task (for diagnostic purposes)\ncrop_post_image_dir | N/A | S3 URL | Post-image output directory for the cropping task (for diagnostic purposes)\ncrop_work_dir | N/A | S3 URL | Working output directory for the initial cropping task (for diagnostic purposes)\ncrop_log_dir | N/A | S3 URL | Log output directory for the initial cropping task (for diagnostic purposes)\nimage2image_dir | N/A | S3 URL | Log output directory for the image2image task (for diagnostic purposes)\n\n#### Advanced Script\n\nThis script runs the Advanced Image Preprocessor and Change Detection Preparation end to end.  Note that you must write the output from the Advanced Image Preprocessor to a file which the Change Detection Preparation task will read.\n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"# Runs the Advanced Image Preprocessor end to end with Change Detection Preparation Task\\n# This example uses the posted data from India.\\nfrom gbdxtools import Interface\\ngbdx = Interface()\\n\\n#Edit the following path to reflect a specific path to an image\\ndata1 = \\\"s3://receiving-dgcs-tdgplatform-com/054661384050_01_003\\\" # Hyderabad GE01\\ndata2 = \\\"s3://receiving-dgcs-tdgplatform-com/055775971010_01_003\\\" # Hyderabad WV03\\n\\n# Run the Advanced Image Preprocessor\\naoptask1 = gbdx.Task(\\\"AOP_Strip_Processor\\\", data=data1, enable_acomp=True, enable_pansharpen=False, enable_dra=False, bands='MS', ortho_epsg=\\\"UTM\\\")\\naoptask2 = gbdx.Task(\\\"AOP_Strip_Processor\\\", data=data2, enable_acomp=True, enable_pansharpen=False, enable_dra=False, bands='MS', ortho_epsg=\\\"UTM\\\")\\n\\n# Edit the following path to reflect a specific path to an image\\ndata1A = \\\"s3://gbd-customer-data/full path to customer's s3 bucket containing preprocessed imagery\\\"\\ndata2A = \\\"s3://gbd-customer-data/full path to customer's s3 bucket containing preprocessed imagery\\\"\\n\\n# The data input and lines must be edited to point to an authorized customer S3 location)\\ncd_preptask = gbdx.Task('cd_prep', pre_image_dir=data1A, post_image_dir=data2A)\\n    \\nworkflow = gbdx.Workflow([ aoptask1, aoptask2, cd_preptask ])\\n    \\n# Edit the following line(s) to reflect specific folder(s) for the output file (example location provided)\\nworkflow.savedata(aoptask1.outputs.data, location='path to customers3 bucket for preprocessed imagery/')\\nworkflow.savedata(aoptask2.outputs.data, location='path to customer s3 bucket for preprocessed imagery/')\\nworkflow.savedata(cd_prep_test.outputs.final_pre_image_dir, location='customer final output directory/end2end/GE01_Hyderabad/pre/')\\nworkflow.savedata(cd_prep_test.outputs.final_post_image_dir, location='customer final output directory/end2end/WV03_Hyderabad/post/')\\n\\nworkflow.execute()\\n\\nprint workflow.id\\nprint workflow.status\\n\",\n      \"language\": \"python\"\n    }\n  ]\n}\n[/block]\n\n\n\n##<a name=\"Known Issues\"></a>Known Issues\n\n\n\n#### Contact Us   \nIf you have any questions or issues with this task, please contact [**gbdx-support:::at:::digitalglobe.com** ](mailto:gbdx-support@digitalglobe.com).","excerpt":"The Change Detection Preparation task performs a series of operations on a pair of input images to prepare them for the application of downstream change detection algorithms. It accomplishes this via the following operations:\n\n1. Initial crop of the input images to their region of overlap  \n2. Image-to-image registration\n3. Alignment of the images to a common grid, cloud removal and final cropping.\n\nThe input imagery for this task is two multispectral orthorectified, atmospherically compensated images in geotiff format and UTM projection typically output from the [Advanced Image Preprocessor](doc:advanced-image-preprocessor) \n\t\n**GBDX Registered Name**: cd_prep\n**Provider**: GBDX\n**Inputs**: tiff or vrt output from the [Advanced Image Preprocessor](doc:advanced-image-preprocessor) \n**Outputs**: Tiff file with the image name format:  pre_image_cdprep.tif and post_image_cdprep.tif.\n**Compatible bands & sensors**: WorldView-2, WorldView-3, GeoEye-1, QuickBird. Change Detection Preparation can process images with different numbers of bands. The output files will have the same number of bands as the input files.","slug":"change-detection-imagepairalignment","type":"basic","title":"Change Detection Image Pair Alignment"}

Change Detection Image Pair Alignment

The Change Detection Preparation task performs a series of operations on a pair of input images to prepare them for the application of downstream change detection algorithms. It accomplishes this via the following operations: 1. Initial crop of the input images to their region of overlap 2. Image-to-image registration 3. Alignment of the images to a common grid, cloud removal and final cropping. The input imagery for this task is two multispectral orthorectified, atmospherically compensated images in geotiff format and UTM projection typically output from the [Advanced Image Preprocessor](doc:advanced-image-preprocessor) **GBDX Registered Name**: cd_prep **Provider**: GBDX **Inputs**: tiff or vrt output from the [Advanced Image Preprocessor](doc:advanced-image-preprocessor) **Outputs**: Tiff file with the image name format: pre_image_cdprep.tif and post_image_cdprep.tif. **Compatible bands & sensors**: WorldView-2, WorldView-3, GeoEye-1, QuickBird. Change Detection Preparation can process images with different numbers of bands. The output files will have the same number of bands as the input files.

## Table of Contents Section | Description --- | --- [Imagery Examples](#Imagery Examples) | Before and after examples [Quickstart](#Quickstart) | Get started with a Python-based quickstart tutorial [Task Runtime](#Task Runtime) | Benchmark runtimes for the algorithm [Input Options](#Input Options) | Required and optional task inputs [Outputs](#Outputs) | Task outputs and example contents [Advanced Options](#Advanced Options) | Additional information for advanced users [Known Issues](#Known Issues) | Issues users should be aware of ## <a name="Imagery Examples"></a>Imagery Examples [block:image] { "images": [ { "image": [ "https://files.readme.io/b1181e1-SF_Final_1B_Animations.gif", "SF_Final_1B_Animations.gif", 609, 800, "#233e3f" ], "caption": "This 5 second animation shows the two unprocessed 1B multispectral images in geotiff format" } ] } [/block] [block:image] { "images": [ { "image": [ "https://files.readme.io/7db9ad5-AOP_Animation.gif", "AOP_Animation.gif", 565, 909, "#203023" ], "caption": "Intermediate: These are the same two images after running the Advanced Image Preprocessor. These will be used as inputs for the Change Detection Preparation task" } ] } [/block] [block:image] { "images": [ { "image": [ "https://files.readme.io/8571709-SF_Final_cd_prep_Animations.gif", "SF_Final_cd_prep_Animations.gif", 526, 678, "#192811" ], "caption": "After: This 5 second animation shows the 2 output files from the Change Detection Preparation task called pre_image_cdprep.tif and post_image_cdprep.tif" } ] } [/block] ## <a name="Quickstart"></a>Quickstart Tutorial Example Script: Run in a python environment (i.e. - IPython) using the gbdxtools interface. These basic settings will run cd_prep from a pair of input orthorectified, AComped image output from the Advanced Image Preprocessor. See also examples listed under the [Advanced Options](#advanced-options). [block:code] { "codes": [ { "code": "# Run The Change Detection Preparation Task on a pair of images\nfrom gbdxtools import Interface\ngbdx = Interface()\n\n# The data input and lines must be edited to point to an authorized customer S3 location)\ncd_prep = gbdx.Task('cd_prep', \n pre_image_dir='s3://gbd-customer-data/CustomerAccount#/PathToPreImage/',\n post_image_dir='s3://gbd-customer-data/CustomerAccount#/PathToPostImage')\n \nworkflow = gbdx.Workflow([cd_prep])\n#Edit the following line(s) to reflect specific folder(s) for the output file (example location provided)\nworkflow.savedata(cd_prep.outputs.final_pre_image_dir, location='CDPrep/pre_image_dir')\nworkflow.savedata(cd_prep.outputs.final_post_image_dir, location='CDPrep/post_image_dir')\nworkflow.execute()\n\nprint workflow.id\nprint workflow.status", "language": "python" } ] } [/block] **Example Run in IPython:** [block:code] { "codes": [ { "code": "**Example Run in IPython:**\n\n In [1]: from gbdxtools import Interface\n In [2]: gbdx = Interface()\n In [3]: cd_prep = gbdx.Task('cd_prep', \n pre_image_dir='s3://gbd-customer-data/7d8cfdb6-13ee-4a2a-bf7e-0aff4795d927/jkoenig/cd_prep_test/Borneo/test2/AOP/pre/', \n post_image_dir = 's3://gbd-customer-data/7d8cfdb6-13ee-4a2a-bf7e-0aff4795d927/jkoenig/cd_prep_test/Borneo/test2/AOP/post/')\n In [4]: workflow = gbdx.Workflow([cd_prep])\n In [5]: workflow.savedata(cd_prep.outputs.final_pre_image_dir, location='cd_prep_test/pub_test/pre_image_dir')\n In [6]: workflow.savedata(cd_prep.outputs.final_post_image_dir, location='cd_prep_test/pub_test/post_image_dir')\n In [7]: workflow.execute()\n Out [7]: \n u'4498407427801810318'\n In [8]: print workflow.status\n {u'state': u'running', u'event': u'started'} [9]:", "language": "python" } ] } [/block] ## <a name="Task Runtime"></a>Task Runtime There is no benchmark runtime data for this task. Standard benchmarks are sensor-specific, and this task can take images from multiple sensors. ## <a name="Input Options"></a>Input Options This task takes as input two orthorectified, atmospherically compensated images in geotiff format. It is intended to work as a following task to the Advanced Image Preprocessor (AOP_Strip_Processor,) with only the AComp option specified. **Description of Basic Input Parameters for the Change Detection Preparation GBDX task** The following table lists the cd_prep GBDX inputs. All inputs are optional with default values, with the exception of 'pre_image_dir', 'post_image_dir', 'final_pre_image_dir', and 'final_post_image_dir' which specify the task's input and output data locations. Name | Required | Default | Valid Values | Description ------------|-------------|:---------------------:|---------------------------------|----------------- pre_image_dir | Yes | N/A | S3 URL | Pre-image input directory containing one or more TIFF files post_image_dir | Yes | N/A | S3 URL | Post-image input directory containing one or more TIFF files ## <a name="Outputs"></a>Outputs On completion, the processed imagery will be written to your specified S3 Customer Location (i.e., s3://gbd-customer-data/unique customer id/pre_image_dir/, s3://gbd-customer-data/unique customer id/post_image_dir/). Each output directory will contain a single geotiff file with one of the names: pre_image_cdprep.tif or post_image_cdprep.tif. Name | Required | Default | Valid Values | Description ------------|-------------|:---------------------:|---------------------------------|----------------- final_pre_image_dir | Yes |N/A | S3 URL | Pre-image output directory for cd_prep final_post_image_dir | Yes |N/A | S3 URL | Post-image output directory for cd_prep ## <a name="Advanced Options"></a>Advanced Options The options in the following table provide additional control over the resulting output. All of the directories are generally for diagnostic purposes. Name | Default | Valid Values | Description -------------------------|:---------------------:|---------------------------------|----------------- buffer_in_meters | 1500.0 | string | Amount in meters by which to buffer the intersection polygon of the initial crop resampling_method | near | string | Method for resampling the images to a common grid. Choices are 'near', 'bilinear', 'cubic', 'cubicspline', 'lanczos', 'average' resolution_in_meters | 2.0 | string | The resolution in meters of the pair of output images enable_cloud_mask | true | string | Enable/disable cloud mask. Choices are 'true' or 'false' shrink_buffer_in_meters | 0.0 | string | Distance in meters by which to shrink the final intersection polygon for final crop crop_pre_image_dir | N/A | S3 URL | Pre-image output directory for the cropping task (for diagnostic purposes) crop_post_image_dir | N/A | S3 URL | Post-image output directory for the cropping task (for diagnostic purposes) crop_work_dir | N/A | S3 URL | Working output directory for the initial cropping task (for diagnostic purposes) crop_log_dir | N/A | S3 URL | Log output directory for the initial cropping task (for diagnostic purposes) image2image_dir | N/A | S3 URL | Log output directory for the image2image task (for diagnostic purposes) #### Advanced Script This script runs the Advanced Image Preprocessor and Change Detection Preparation end to end. Note that you must write the output from the Advanced Image Preprocessor to a file which the Change Detection Preparation task will read. [block:code] { "codes": [ { "code": "# Runs the Advanced Image Preprocessor end to end with Change Detection Preparation Task\n# This example uses the posted data from India.\nfrom gbdxtools import Interface\ngbdx = Interface()\n\n#Edit the following path to reflect a specific path to an image\ndata1 = \"s3://receiving-dgcs-tdgplatform-com/054661384050_01_003\" # Hyderabad GE01\ndata2 = \"s3://receiving-dgcs-tdgplatform-com/055775971010_01_003\" # Hyderabad WV03\n\n# Run the Advanced Image Preprocessor\naoptask1 = gbdx.Task(\"AOP_Strip_Processor\", data=data1, enable_acomp=True, enable_pansharpen=False, enable_dra=False, bands='MS', ortho_epsg=\"UTM\")\naoptask2 = gbdx.Task(\"AOP_Strip_Processor\", data=data2, enable_acomp=True, enable_pansharpen=False, enable_dra=False, bands='MS', ortho_epsg=\"UTM\")\n\n# Edit the following path to reflect a specific path to an image\ndata1A = \"s3://gbd-customer-data/full path to customer's s3 bucket containing preprocessed imagery\"\ndata2A = \"s3://gbd-customer-data/full path to customer's s3 bucket containing preprocessed imagery\"\n\n# The data input and lines must be edited to point to an authorized customer S3 location)\ncd_preptask = gbdx.Task('cd_prep', pre_image_dir=data1A, post_image_dir=data2A)\n \nworkflow = gbdx.Workflow([ aoptask1, aoptask2, cd_preptask ])\n \n# Edit the following line(s) to reflect specific folder(s) for the output file (example location provided)\nworkflow.savedata(aoptask1.outputs.data, location='path to customers3 bucket for preprocessed imagery/')\nworkflow.savedata(aoptask2.outputs.data, location='path to customer s3 bucket for preprocessed imagery/')\nworkflow.savedata(cd_prep_test.outputs.final_pre_image_dir, location='customer final output directory/end2end/GE01_Hyderabad/pre/')\nworkflow.savedata(cd_prep_test.outputs.final_post_image_dir, location='customer final output directory/end2end/WV03_Hyderabad/post/')\n\nworkflow.execute()\n\nprint workflow.id\nprint workflow.status\n", "language": "python" } ] } [/block] ##<a name="Known Issues"></a>Known Issues #### Contact Us If you have any questions or issues with this task, please contact [**gbdx-support@digitalglobe.com** ](mailto:gbdx-support@digitalglobe.com).