From b51241ec040e301376c42b5dbd5be40e7627b881 Mon Sep 17 00:00:00 2001 From: heyarne Date: Wed, 17 Mar 2021 12:37:41 +0100 Subject: [PATCH] =?UTF-8?q?Improve=20intro=20to=20chapter=201=E2=80=A6=20e?= =?UTF-8?q?ven=20more?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- sources/01-overview.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sources/01-overview.md b/sources/01-overview.md index 68dbb27..d2533a4 100644 --- a/sources/01-overview.md +++ b/sources/01-overview.md @@ -4,6 +4,6 @@ The first chapter contains notebooks that document the data retrieval process fr It explains how to use the [`sentinelsat`](https://github.com/sentinelsat/sentinelsat) library to interact with the HTTP API: How to specify what kind of data we are interested in with the aide of open map data from [OpenStreetMap](https://www.openstreetmap.org/) and [`geopandas`](https://geopandas.org/) and how to download it. It then goes on to show how to use [`rasterio`](https://rasterio.readthedocs.io/) and [`numpy`](https://numpy.org/) to read and process the downloaded data and [`matplotlib`](https://matplotlib.org/stable/index.html) to visualize it. -The Sentinel-2 mission is a part of the [Copernicus earth observation missions of the ESA](http://www.esa.int/Applications/Observing_the_Earth/Copernicus), which provide open satellite data to anyone. Sentinel-2 is a group of satellites that capture electromagnetic radiation. A part of this is visible light, so it can be used to create detailed satellite maps, but a large part of this is invisible. It can be used to infer information on all kinds of ground-level phenomena where other data sources are scarce +The Sentinel-2 mission is a part of the [Copernicus Earth observation program](http://www.esa.int/Applications/Observing_the_Earth/Copernicus), which provides open earth observation data to anyone. Sentinel-2 is a group of satellites that capture electromagnetic radiation. A part of this is visible light, so it can be used to create detailed satellite maps, but a large part of the captured data is invisible. It can be used to infer information on all kinds of ground-level phenomena where other data sources are scarce. This chapter will detail how to retrieve, interpret and manipulate this data, and ends with a notebook that can create a true color image using recent satellite data for any area.