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heyarne 2021-03-13 15:36:14 +01:00
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sources/01a-download-process.ipynb
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@ -39,7 +39,8 @@
"## Defining the Region of Interest\n",
"\n",
"The Copernicus Open Access Hub API expects a point or area that designates the region of interest.\n",
"We use the [OpenStreetMap Nominatim API](https://nominatim.org/) to query for the administrative boundaries of Berlin using the `search_osm` function defined in `sentinel_helpers.py`:"
"The [OpenStreetMap Nominatim API](https://nominatim.org/) provides a HTTP-based interface to the OpenStreetMap data set, which can be queried for the administrative boundaries of Berlin.",
"The `search_osm` function defined in `sentinel_helpers.py` allows retrieving these geometries by location name:"
]
},
{
@ -241,13 +242,12 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"OpenStreetMap contains geoinformation at vastly different scales and of very different types.\n",
"We can use it to query outlines of parks or entire countries.\n",
"OpenStreetMap contains geoinformation at vastly different scales and of very different types, which range from outlines of parks to entire countries.\n",
"The [OpenStreetMap wiki](https://wiki.openstreetmap.org/wiki/Main_Page) contains exhaustive information about the architectural design of OpenStreetMap.\n",
"Using the `search_osm` function we are very flexible in the type of query information we can retrieve.\n",
"This empowers the `search_osm` function to retrieve geoinformation on places that would otherwise be widely scattered across a myriad of sources, if available at all.\n",
"\n",
"The first result is the city's centroid.\n",
"We use the `type` to select the administrative boundaries."
"The property listed in the `type` column can be used to select the administrative boundaries."
]
},
{
@ -424,7 +424,7 @@
"metadata": {},
"source": [
"The region of interest is given as the `footprint` parameter.\n",
"We use a simplified version of the geometry retrieved from OpenStreetMap - its convex hull - due to restrictions in URL lengths that don't allow us to query for arbitrarily detailed geometries:"
"The geometry retrieved from OpenStreetMap is simplified by calculating convex hull due to restrictions in URL lengths that don't allow querying for arbitrarily detailed geometries:"
]
},
{
@ -483,7 +483,7 @@
"The criteria for selecting a product depends on the specific use case.\n",
"The first use case is to plot an image of Berlin, so want to make sure that as much of the city as possible is visible in the data we download.\n",
"\n",
"We convert the list of products to a `GeoDataFrame`, for which `gdf` is an acronym:"
"The list of products to a `GeoDataFrame` (`gdf`):"
]
},
{
@ -508,9 +508,9 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"`plot_downloaded_products` is a helper that allows us to draw downloaded products along with a designated area of interest.\n",
"`plot_downloaded_products` allows plotting the tile geometry of downloaded or available products over with a designated area of interest.\n",
"\n",
"We can use it to get a quick visual impression of the result:"
"This provides quick visual impression of the result:"
]
},
{
@ -550,8 +550,8 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Because products are are large (roughly 1GB), we want to skip unnecessary downloads wherever possible.\n",
"We are selecting products based on two criteria:\n",
"Because products are large (roughly 1GB), it is desirable to skip unnecessary downloads whenever possible.\n",
"Products are therefore filtered by two criteria:\n",
"\n",
"- How much of the area of interest is visible in the product (i.e. area of the intersection of a product's tile and our area of interest)\n",
"- Cloud coverage (the less the better)"
@ -962,7 +962,7 @@
"metadata": {},
"source": [
"`downloads` contains a dictionary, mapping each product's UUID to detailed information about the downloaded product.\n",
"We can use it to calculate the total download size:"
"This information can be used to calculate the total download size:"
]
},
{