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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,115 @@ | ||
| { | ||
| "title": "CoastSeg: An Accessible and Extendable Hub for Satellite-Derived Shoreline (SDS) Detection and Mapping", | ||
| "description": "CoastSeg is an interactive browser-based program that aims to broaden the adoption of satellite-derived shoreline (SDS) detection workflows among coastal scientists and coastal resource management practitioners. SDS is a sub-field of coastal sciences that aims to detect and post-process a time-series of shoreline locations from publicly available satellite imagery.", | ||
| "creators": [ | ||
| { | ||
| "name": "Fitzpatrick, Sharon", | ||
| "orcid": "0000-0001-6513-9132", | ||
| "affiliation": "Contracted to U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Buscombe, Daniel", | ||
| "orcid": "0000-0001-6217-5584", | ||
| "affiliation": "Contracted to U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Warrick, Jonathan A.", | ||
| "orcid": "0000-0002-0205-3814", | ||
| "affiliation": "U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Lundine, Mark A.", | ||
| "orcid": "0000-0002-2878-1713", | ||
| "affiliation": "U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Vos, Kilian", | ||
| "orcid": "0000-0002-9518-1582", | ||
| "affiliation": "New South Wales Department of Planning and Environment, Sydney, Australia" | ||
| } | ||
| ], | ||
| "contributors": [ | ||
| { | ||
| "name": "Doran, K.S.", | ||
| "orcid": "0000-0001-8050-5727", | ||
| "affiliation": "U.S. Geological Survey St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL 33701, United States" | ||
| }, | ||
| { | ||
| "name": "Janda, Catherine", | ||
| "orcid": "0009-0004-5153-3680", | ||
| "affiliation": "U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Gibbs, Ann", | ||
| "orcid": "0000-0002-0883-3774", | ||
| "affiliation": "U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Weber, Kathryn M.", | ||
| "orcid": "0000-0002-5498-7117", | ||
| "affiliation": "U.S. Geological Survey Woods Hole Coastal and Marine Science Center, Woods Hole, MA 02543, United States" | ||
| }, | ||
| { | ||
| "name": "O'Neill, Andrea", | ||
| "orcid": "0000-0003-1656-4372", | ||
| "affiliation": "U.S. Geological Survey Pacific Coastal and Marine Science Center, Santa Cruz, California, United States" | ||
| }, | ||
| { | ||
| "name": "Heslin, Julia L.", | ||
| "orcid": "0000-0002-6895-800X", | ||
| "affiliation": "U.S. Geological Survey Woods Hole Coastal and Marine Science Center, Woods Hole, MA 02543, United States" | ||
| }, | ||
| { | ||
| "name": "Burgess, Joseph", | ||
| "affiliation": "U.S. Geological Survey St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL 33701, United States" | ||
| }, | ||
| { | ||
| "name": "Floris R. Calkoen", | ||
| "orcid": "0000-0002-7155-6247", | ||
| "affiliation": "Deltares | Delft, Netherlands" | ||
| }, | ||
| { | ||
| "name": "Himmelstoss, Emily A.", | ||
| "orcid": "0000-0002-1760-5474", | ||
| "affiliation": "U.S. Geological Survey Woods Hole Coastal and Marine Science Center, Woods Hole, MA 02543, United States" | ||
| }, | ||
| { | ||
| "name": "Bishop-Taylor, Robbi", | ||
| "orcid": "0000-0002-1533-2599", | ||
| "affiliation": "Geoscience Australia" | ||
| }, | ||
| { | ||
| "name": "Lazarus, Eli D.", | ||
| "orcid": "0000-0003-2404-9661", | ||
| "affiliation": "University of Southampton" | ||
| }, | ||
| { | ||
| "name": "Ku, Venus", | ||
| "orcid": "0000-0002-7454-8277" | ||
| }, | ||
| { | ||
| "name": "Goldstein, Evan B.", | ||
| "orcid": "0000-0001-9358-1016", | ||
| "affiliation": "Sediment-Science" | ||
| } | ||
| ], | ||
| "license": { | ||
| "id": "GPL-3.0-only" | ||
| }, | ||
| "keywords": [ | ||
| "CoastSeg", | ||
| "Satellite-Derived Shoreline", | ||
| "SDS", | ||
| "Coastal Mapping", | ||
| "Remote Sensing" | ||
| ], | ||
| "access_right": "open", | ||
| "communities": [ | ||
| { | ||
| "identifier": "coastal-science" | ||
| } | ||
| ], | ||
| "upload_type": "software", | ||
| "language": "eng" | ||
| } | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,91 @@ | ||
| import os | ||
| from coastseg import coastseg_logs | ||
| from coastseg import zoo_model | ||
| from coastseg.tide_correction import compute_tidal_corrections | ||
| from coastseg import file_utilities | ||
|
|
||
| # The Zoo Model is a machine learning model that can be used to extract shorelines from satellite imagery. | ||
| # This script will only run a single ROI at a time. If you want to run multiple ROIs, you will need to run this script multiple times. | ||
|
|
||
| # Extract Shoreline Settings | ||
| settings ={ | ||
| 'min_length_sl': 100, # minimum length (m) of shoreline perimeter to be valid | ||
| 'max_dist_ref':500, # maximum distance (m) from reference shoreline to search for valid shorelines. This detrmines the width of the buffer around the reference shoreline | ||
| 'cloud_thresh': 0.5, # threshold on maximum cloud cover (0-1). If the cloud cover is above this threshold, no shorelines will be extracted from that image | ||
| 'dist_clouds': 100, # distance(m) around clouds where shoreline will not be mapped | ||
| 'min_beach_area': 50, # minimum area (m^2) for an object to be labelled as a beach | ||
| 'sand_color': 'default', # 'default', 'latest', 'dark' (for grey/black sand beaches) or 'bright' (for white sand beaches) | ||
| "apply_cloud_mask": True, # apply cloud mask to the imagery. If False, the cloud mask will not be applied. | ||
| } | ||
|
|
||
|
|
||
| # The model can be run using the following settings: | ||
| model_setting = { | ||
| "sample_direc": None, # directory of jpgs ex. C:/Users/username/CoastSeg/data/ID_lla12_datetime11-07-23__08_14_11/jpg_files/preprocessed/RGB/", | ||
| "use_GPU": "0", # 0 or 1 0 means no GPU | ||
| "implementation": "BEST", # BEST or ENSEMBLE | ||
| "model_type": "global_segformer_RGB_4class_14037041", # model name from the zoo | ||
| "otsu": False, # Otsu Thresholding | ||
| "tta": False, # Test Time Augmentation | ||
| "use_local_model": True, # Use local model (not one from zeneodo) | ||
| "local_model_path": r"C:\development\doodleverse\coastseg\CoastSeg\src\coastseg\downloaded_models\non_validation_model", # path to the local model | ||
| } | ||
|
|
||
| # Available models can run input "RGB" # or "MNDWI" or "NDWI" | ||
| img_type = "RGB" # make sure the model name is compatible with the image type | ||
| # percentage of no data allowed in the image eg. 0.75 means 75% of the image can be no data | ||
| percent_no_data = 0.75 | ||
|
|
||
| # 1. Set the User configuration Settings | ||
| # --------------------------- | ||
| # a. ENTER THE NAME OF THE SESSION TO SAVE THE MODEL PREDICTIONS TO | ||
| model_session_name = "sample_session_demo1" | ||
| # b. ENTER THE DIRECTORY WHERE THE INPUT IMAGES ARE STORED | ||
| # - Example of the directory where the input images are stored ( this should be the /data folder in the CoastSeg directory) | ||
| sample_directory = r"C:\development\doodleverse\coastseg\CoastSeg\data\ID_wra5_datetime03-04-24__03_43_01\jpg_files\preprocessed\RGB" | ||
|
|
||
|
|
||
| # 2. Save the settings to the model instance | ||
| # ----------------- | ||
| # Create an instance of the zoo model to run the model predictions | ||
| zoo_model_instance = zoo_model.Zoo_Model() | ||
| # Set the model settings to read the input images from the sample directory | ||
| model_setting["sample_direc"] = sample_directory | ||
| model_setting["img_type"] = img_type | ||
|
|
||
| # save settings to the zoo model instance | ||
| settings.update(model_setting) | ||
| # save the settings to the model instance | ||
| zoo_model_instance.set_settings(**settings) | ||
|
|
||
|
|
||
| # OPTIONAL: If you have a transects and shoreline file, you can extract shorelines from the zoo model outputs | ||
| transects_path = "" # path to the transects geojson file (optional, default will be loaded if not provided) | ||
| shoreline_path = "" # path to the shoreline geojson file (optional, default will be loaded if not provided) | ||
| shoreline_extraction_area_path= "" # path to the shoreline extraction area geojson file (optional) | ||
|
|
||
| # 3. Run the model and extract shorelines | ||
| # ------------------------------------- | ||
| zoo_model_instance.run_model_and_extract_shorelines( | ||
| model_setting["sample_direc"], | ||
| session_name=model_session_name, | ||
| shoreline_path=shoreline_path, | ||
| transects_path=transects_path, | ||
| shoreline_extraction_area_path = shoreline_extraction_area_path | ||
| ) | ||
|
|
||
| # 4. OPTIONAL: Run Tide Correction | ||
| # ------------------------------------------ | ||
| # Tide Correction (optional) | ||
| # Before running this snippet, you must download the tide model to the CoastSeg/tide_model folder | ||
| # Tutorial: https://github.com/Doodleverse/CoastSeg/wiki/09.-How-to-Download-and-clip-Tide-Model | ||
| # You will need to uncomment the line below to run the tide correction | ||
|
|
||
| beach_slope = 0.02 # Slope of the beach (m) | ||
| reference_elevation = 0 # Elevation of the beach Mean Sea Level (M.S.L) (m) | ||
|
|
||
| # UNCOMMENT THESE LINES TO RUN THE TIDE CORRECTION | ||
| # roi_id = file_utilities.get_ROI_ID_from_session(session_name) # read ROI ID from the config.json file found in the extracted shoreline session directory | ||
| # compute_tidal_corrections( | ||
| # session_name, [roi_id], beach_slope, reference_elevation | ||
| # ) |
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