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fix: Jupyter Geocube client data access #5

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fix: Jupyter Geocube client data access #5

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19 changes: 9 additions & 10 deletions Jupyter/Geocube-Client-DataAccess.ipynb
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Expand Up @@ -10,7 +10,7 @@
"\n",
"**Short description**\n",
"\n",
"This notebook introduces you to the Geocube Python Client. You will learn how to list available layers, construct a query over an aoi and a time interval and retrieve cubes of data.\n",
"This notebook introduces you to the Geocube Python Client. You will learn how to list available layers, construct a query over an AOI (area of interest) and a time interval and retrieve cubes of data.\n",
"\n",
"-------\n",
"\n",
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"import os\n",
"from datetime import datetime\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"%matplotlib inline"
"from matplotlib import pyplot as plt"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 2 - Records\n",
"## 3 - Records\n",
"A record defines a data-take by its geometry, its sensing time and user-defined tags that describe the context in more detail.\n",
"\n",
"More details in the [Indexation Tutorial # Records](./Geocube-Client-DataIndexation.ipynb#3---Records).\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 3 - Variables\n",
"## 4 - Variables\n",
"A variable describes the kind of data stored in a product, for example _a spectral band, NDVI, RGB, backscatter, classification_...\n",
"\n",
"It stores the information needed to **describe**, **process** and **visualize** the product.\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 4 - Raster data\n",
"## 5 - Raster data\n",
"\n",
"As we saw in introduction of this notebook, an image is defined by a **record** and an **instance** of a variable. The data is retrieved as 2D array, that is defined by a **rectangle extent in a given CRS** and a **resolution**.\n",
"If necessary, the datasets that composed an image are reprojected or scaled on the fly.\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 5 - Get data covering a large AOI with tiling\n",
"## 6 - Get data covering a large AOI with tiling\n",
"\n",
"If the AOI is too large to be retrieve in one time, it must be tiled.\n",
"\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 6 - Some useful functions\n",
"## 7 - Some useful functions\n",
"\n",
"### Get a tile, a dataset or a cube from the aoi of a record\n",
"### Get a tile, a dataset or a cube from the AOI of a record\n",
"The function `Tile.from_record` creates a tile covering the aoi of the record.\n",
"Then, a dataset can be easily downloaded using `CubeParam.from_tile`.\n",
"\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"## 7 - Conclusion\n",
"## 8 - Conclusion\n",
"In this notebook, you have learnt to list records, load variable and retrieve cubes of data over a large AOI."
]
}
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