Page 1 of 1
SEADAS pixel extraction
Posted: Thu Dec 08, 2022 3:56 pm America/New_York
I was curious if there was a way to import county boundaries/state boundaries into SEADAS .dim files? Also, was there a way to do pixel extraction within that particular region?
It seems like you can only pixel extract around a #x# grid around individual pins, and not within shapes.
Re: SEADAS pixel extraction
Posted: Tue Dec 13, 2022 7:16 am America/New_York
by OB SeaDAS - knowles
Yes you can import county/state boundaries and you can also export pixels for a particular region.
To import county/state boundaries you will need to find an ESRI shapefile from an external source which contains the geographic boundaries. For instance this site contains a shapefile of all the counties in the state of Maryland: https://data.imap.maryland.gov/datasets/4c172f80b626490ea2cff7b699febedb/
Load a satellite file into SeaDAS and then import the shapefile Menu > File > Import > Vector Data > ESRI Shapefile (load the file ending in .shp and you do need to keep together all 6 shapefiles of the shapefile dataset). This action will create masks in SeaDAS, one for each shape element contained within your shapefile. This is where you need to be careful in your selection of shapefile to use. If you were to load a shapefile of the entire US with all it's counties then this would result in a huge amount of masks being created in SeaDAS and would likely take a long time or just freeze up as it overloads your computer's memory.
Regarding your second question you will need to create a single ROI (region of interest) mask which covers the pixels which you wish to export. Then Menu > Raster > Export > Mask Pixels will take you to the tool which let's you select the ROI mask and exports the pixel data to a text file.
Note your single ROI mask can be a mask equation based on both region and quality. For example the equation in Mask Manager (for a Level-2 file): "geometry and !LAND and !STRAYLIGHT" would be a single composite ROI mask which represents both regional criteria and quality criteria.