added more data license info

Author: mayank2

samples/04_gis_analysts_data_scientists/detecting-airplanes-on-satellite-imagery-using-deep-learning.ipynb

@@ -49,7 +49,7 @@
     "id": "kCPaThDs2sPq"
    },
    "source": [
-    "The dataset we used in this notebook can be downloaded from [cosmiQ works](https://www.cosmiqworks.org/rareplanes/). We are going to use real training data that contains 5,815 training images. The images have dimensions of 512x512 and a resolution of 30cm. Tiled images have also been put into an images folder, and the annotations have been converted to the \"PASCAL_VOC_rectangles\" format and have been put into a labels folder. The dataset can be downloaded in the necessary format [here](https://geosaurus.maps.arcgis.com/home/item.html?id=9982c9a749f94f7797e82358a90527c1)."
+    "The dataset we used in this notebook is downloaded from [RarePlanes](https://www.cosmiqworks.org/rareplanes/). **RarePlanes** is an open-source machine learning dataset from **CosmiQ Works** and **[AI.Reverie](https://aireverie.com/)** that incorporates both real and synthetically generated satellite imagery. This data is licensed under the [CC-BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/). We are going to use real training data that contains 5,815 training images. The images have dimensions of 512x512 and a resolution of 30cm. Tiled images have also been put into an images folder, and the annotations have been converted to the \"PASCAL_VOC_rectangles\" format and have been put into a labels folder. The dataset can be downloaded in the necessary format [here](https://geosaurus.maps.arcgis.com/home/item.html?id=9982c9a749f94f7797e82358a90527c1)."
    ]
   },
   {