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Start:Tutorial: Reading and Transforming Satellite Imagery in FME| Next:Making RGB Images with Sentinel data
In this exercise,the goal is to work with three available satellite image readers and provide some tips on dealing with their enormous datasets.Due to the number of satellite image services available,we will not read data from all of the services.Planet Data,Landsat-8 and Sentinel-2 will be discussed,and images read from Sentinel previews.
When reading satellite image formats,the FeatureReader is typically a better option than the traditional readers.Imagery providers have huge global datasets and reading using the traditional readers requires typing in the coordinates of a bounding box,which is not very convenient.With the FeatureReader,we can use a features geometry to initiate reading of a particular area,which is much easier.
Complete workspace:readingsentinel-2onaws.fmw
1) Open a blank workspace in FME Workbench.
2) Add a Creator.
3) Add two published parameters in the Navigator - LATITUDE and LONGITUDE.Create one and select "number" in the type,then right-click duplicate to create the other.We will use the configuration to restrict the values of longitude to be between -180 and 180,and latitude - from -80 to 80 (we don't want to go to polar regions).To learn more about published parameters check outthis article
4) Create a point with VertexCreator using LATITUDE and LONGITUDE parameters ('x' is longitude)
5) Add in a FeatureReader,we will compare some of the available formats and the required parameters.
地球上的数据
6) In the FeatureReader find and select the Planet Data format and open the parameters - some important things to know:
Planet Data Reader Parameters (as seen in the FeatureReader):Note that at the time of writing this article FME does not support all of the Asset/Feature Types,only those shown above are supported.
Landsat-8
7) Replace Planet Data with the Landsat-8 on AWS reader (here we will actually read the data):
Useful transformers for making RGB images:
AttributeCreator (_sort attribute) => Sorter => RasterBandCombiner => RasterInterpretationCoercer,=> RasterExpressionEvaluator.(This process is covered overhere in this article)
Landsat-8 on AWS reader parameters (as seen in the FeatreReader)
Sentinel-2
8) Replace Landsat-8 on AWS with Sentinel-2 on AWS.This looks similar to the Landsat reader with some slight differences
9) When setting Sentinel-2 parameters,choose to read Feature Type Names as 'Bands',uncheck the MGRS box,and choose 'Latest' for the date filter.
10) In the Feature Reader set "Spatial Filter" to "Envelope Intersects" and Feature Types to Read choose PREVIEW (you can experiment with this to see other images for the same tile)
FeatureReader parameters for Sentinel-2 on AWS
11) Connect an inspector to the PREVIEW port and run the workspace with Prompt enabled to set the LATITUDE and LONGITUDE (try Lat = 49 and Long = -123).
12) Inspect the preview,there is a big chance that the image will have a lot of cloud cover.
13) Scroll up in the log window,and find the link to the first metadata XML,click on it,once it opens,search for cloud,show
The finished workspace should look like this:
Finished Workspace
Making RGB Images with Sentinel Data
Raster Bit Masks: Making Sense of the Numbers
Comparing Rasters of Different Formats and Structures
Raster Calculations and Raster Palettes
Tutorial: Reading and Transforming Satellite Imagery in FME
Edge Detection with the RasterConvolver
Setting NoData and Adding Alpha Bands to Remove Black Borders
Tiling Raster Data with the RasterTiler
Change Detection with the RasterExpressionEvaluator
Raster to Raster Translation (Geotiff to JPEG) with Reprojection
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