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Merge pull request #76 from SpaceNetChallenge/dlindenbaum-readme-update
download instructions readme update
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## Hosting
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[SpaceNet](https://aws.amazon.com/public-datasets/spacenet/) is a corpus of commercial satellite imagery and labeled training data to use for machine learning research. The dataset is currently hosted as an [Amazon Web Services (AWS) Public Dataset](https://aws.amazon.com/public-datasets/).
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[SpaceNet](https://spacenetchallenge.github.io/) is a corpus of commercial satellite imagery and labeled training data to use for machine learning research. The dataset is currently hosted as an [Amazon Web Services (AWS) Public Dataset](https://aws.amazon.com/public-datasets/spacenet/).
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For additonal information about the datasets visit the [SpaceNet Challenge Website](https://spacenetchallenge.github.io/)
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## Catalog
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1. Area of Interest 1 (AOI 1) - Location: Rio de Janeiro. 50cm imagery collected from DigitalGlobe’s [WorldView-2 satellite](http://satimagingcorp.s3.amazonaws.com/site/pdf/WorldView-2_datasheet.pdf). The dataset includes building footprints and 8-band multispectral data.
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## Dependencies
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The [AWS Command Line Interface (CLI)](https://aws.amazon.com/cli/) must be installed with an active AWS account. Configure the AWS CLI using 'aws configure'
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## [The SpaceNet Roads Dataset](https://spacenetchallenge.github.io/datasets/spacenetRoads_summary.html)
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Visit the [SpaceNet Roads Dataset website](https://spacenetchallenge.github.io/datasets/spacenetRoads_summary.html) for additional information about the dataset including instructions on how to access and download the data.
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## SpaceNet Simple Storage Service (S3) Directory Structure (AOI 1)
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```
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s3://spacenet-dataset/
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-- AOI_1_Rio
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|-- processedData
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| -- processedBuildingLabels.tar.gz # Compressed 3band and 8band 200m x 200m tiles with associated building foot print labels # This dataset is the Training Dataset for the first Top Coder Competition
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`-- srcData
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|-- rasterData
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| |-- 3-Band.tar.gz # 3band (RGB) Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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| -- 8-Band.tar.gz # 8band Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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-- vectorData
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|-- Rio_BuildingLabels.tar.gz # Source Dataset that contains Building the building foot prints traced from the Mosaic
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|-- Rio_HGIS_Metro.gdb.tar.gz # Source Point of Interest Dataset in GeoDatabase Format. Best if Used with ESRI
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-- Rio_HGIS_Metro_extract.tar # Source Point of Interest Dataset in GeoJSON with associated .jpg. Easy to Use without ESRI toolset
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-- AOI_1_Rio
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|-- processedData
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| -- processedBuildingLabels.tar.gz # Compressed 3band and 8band 200m x 200m tiles with associated building foot print labels # This dataset is the Training Dataset for the first Top Coder Competition
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`-- srcData
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|-- rasterData
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| |-- 3-Band.tar.gz # 3band (RGB) Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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| -- 8-Band.tar.gz # 8band Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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-- vectorData
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|-- Rio_BuildingLabels.tar.gz # Source Dataset that contains Building the building foot prints traced from the Mosaic
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|-- Rio_HGIS_Metro.gdb.tar.gz # Source Point of Interest Dataset in GeoDatabase Format. Best if Used with ESRI
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-- Rio_HGIS_Metro_extract.tar # Source Point of Interest Dataset in GeoJSON with associated .jpg. Easy to Use without ESRI toolset
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-- AOI_1_Rio
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|-- processedData
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| -- processedBuildingLabels.tar.gz # Compressed 3band and 8band 200m x 200m tiles with associated building foot print labels # This dataset is the Training Dataset for the first Top Coder Competition
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`-- srcData
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|-- rasterData
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| |-- 3-Band.tar.gz # 3band (RGB) Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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| -- 8-Band.tar.gz # 8band Raster Mosaic for Rio De Jenairo area (2784 sq KM) collected by WorldView-2
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-- vectorData
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|-- Rio_BuildingLabels.tar.gz # Source Dataset that contains Building the building foot prints traced from the Mosaic
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|-- Rio_HGIS_Metro.gdb.tar.gz # Source Point of Interest Dataset in GeoDatabase Format. Best if Used with ESRI
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-- Rio_HGIS_Metro_extract.tar # Source Point of Interest Dataset in GeoJSON with associated .jpg. Easy to Use without ESRI toolset
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```
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## SpaceNet Simple Storage Service (S3) Directory Structure (AOI 2-5)
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```
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├── AOI_[Num]_[City]_Train
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│ ├── geojson
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│ │ └── buildings # Contains GeoJson labels of buildings for each tile
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│ ├── MUL # Contains Tiles of 8-Band Multi-Spectral raster data from WorldView-3
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│ ├── MUL-PanSharpen # Contains Tiles of 8-Band Multi-Spectral raster data pansharpened to 0.3m
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│ ├── PAN # Contains Tiles of Panchromatic raster data from Worldview-3
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│ ├── RGB-PanSharpen # Contains Tiles of RGB raster data from Worldview-3
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│ └── summaryData # Contains CSV with pixel based labels for each building in the Tile Set.
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```
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## Download instructions
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### AOI 1 - Rio de Janeiro
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To download processed 200mx200m tiles of AOI 1 (3.4 GB) with associated building footprints do the following:
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/processedData/processedBuildingLabels.tar.gz --request-payer requester processedBuildingLabels.tar.gz
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```
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To download the Source Imagery Mosaic (3-band = 2.3 GB and 8-band = 6.5 GB):
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/srcData/rasterData/3-Band.tar.gz --request-payer requester 3-Band.tar.gz
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/srcData/rasterData/8-Band.tar.gz --request-payer requester 8-Band.tar.gz
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```
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To download the Source Vector Data (0.18 GB):
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/srcData/vectorData/Rio_BuildingLabels.tar.gz --request-payer requester Rio_BuildingLabels.tar.gz
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```
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### AOI 2 - Vegas
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To download processed 200mx200m tiles of AOI 2 (23 GB) with associated building footprints do the following:
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_2_Vegas/AOI_2_Vegas_Train.tar.gz --request-payer requester AOI_2_Vegas_Train.tar.gz
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```
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### AOI 3 - Paris
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To download processed 200mx200m tiles of AOI 3 (5 GB) with associated building footprints do the following:
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```
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## Warning this file is 5 GB
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aws s3api get-object --bucket spacenet-dataset --key AOI_3_Paris/AOI_3_Paris_Train.tar.gz --request-payer requester AOI_3_Paris_Train.tar.gz
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```
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### AOI 4 - Shanghai
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To download processed 200mx200m tiles of AOI 4 (23 GB) with associated building footprints do the following:
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_4_Shanghai/AOI_4_Shanghai_Train.tar.gz --request-payer requester AOI_4_Shanghai_Train.tar.gz
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```
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### AOI 5 - Khartoum
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To download processed 200mx200m tiles of AOI 5 (4 GB) with associated building footprints do the following:
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_5_Khartoum/AOI_5_Khartoum_Train.tar.gz --request-payer requester AOI_5_Khartoum_Train.tar.gz
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```
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### Point of Interest Dataset in ESRI GeoDatabase Form (31 GB)
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/srcData/vectorData/Rio_HGIS_Metro.gdb.tar.gz --request-payer requester Rio_HGIS_Metro.gdb.tar.gz
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```
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## [The SpaceNet Catalog](https://spacenetchallenge.github.io/datasets/datasetHomePage.html)
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Visit the [SpaceNet Data Corpus website](https://spacenetchallenge.github.io/datasets/spacenetRoads_summary.html) for additional information about all SpaceNet datasets including instructions on how to access and download the data.
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### Point of Interest Dataset Extracted into GeoJSONs with associated .jpg (29 GB)
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```
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aws s3api get-object --bucket spacenet-dataset --key AOI_1_Rio/srcData/vectorData/Rio_HGIS_Metro_extract.tar --request-payer requester Rio_HGIS_Metro_extract.tar
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```
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