In 2019 and 2020 I wrote two articles in this forum that described experimental work I was doing to pre-process Landsat and Sentinel2 multispectral imagery using virtual raster technology and then to display that imagery in MapInfo Pro using rendering algorithms.
After leaving Precisely in 2020, I started afresh. Today, after three years of hard work, I am pleased to announce the release of
ProRaster Scientific!
ProRaster Scientific uses advanced virtual rasters to implement an entire processing pipeline for satellite multispectral imagery, including:
Pre-processing each scene into a "Scene Assembly Virtual Raster".
We combine all of the supplied rasters into a single virtual raster.
We transform Digital Numbers into Reflectance and can compute Top of Atmosphere corrections.
From QA data, we build a set of standard masks that differentiate pixels by quality and sort them into Land, Water, and Snow.
Combine scenes into products using the concepts of collation, mosaicing, and sequencing.
Combine scenes spatially into mosaics or temporally into sequences.
Combine masked, temporally adjacent scenes into collated scenes and mosaics.
Combine mosaic or collated mosaics temporally into sequences.
Build branched and chained processing pipelines for your raster products.
Apply operations to mask, clip, and reproject.
Apply operations to compute spectral indices or general calculator expressions.
Apply operations to compute the difference between events in a sequence.
Compute comprehensive statistics and export to transportable raster formats.
Eliminating processing errors by automation.
Minimising processing and maximising efficiency.
Eliminating intermediate storage and minimising overall storage requirements.
Of course, you can render all and explore all of this data in multithreaded, hardware-accelerated map windows.
Landsat and Sentinel2 multispectral satellite imagery is provided for free to the world, but it takes effort to realise value from these incredible raster datasets. My goal, with
ProRaster Scientific, is to make it possible for users of any level of ability to acquire value from these datasets.
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Sam Roberts
Founder, Roberts Geospatial Engineering
Australia
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