PAG Datasets (login required)
Datasets collected by the Pima Association of Governments are available for University affiliates only. To access these data, visit imagery.library.arizona.edu
NAIP Imagery (2005, 2007, 2010, 2013, 2015, 2017)
To access these data, you can use the index map to identify which tiles you need for your area of interest. If you have fewer than 10 tiles, you can email Jeff Oliver with the list of files to retrieve. Alternatively, you can retrieve the files yourself at https://data.cyverse.org/dav-anon/iplant/projects/azgs/GIS_Data_NP112_NP212/.
With the exception of the 2005 dataset which is 3-band imagery, the NAIP imagery provided here is four band (R,G, B, NIR) imagery covering the state of Arizona. Years 2007, 2010, 2013, and 2015 are provided at 1m spatial resolution with 2017 provided at 60cm. To download, select the year and click the map to identify the USGS quarter quadrangle you'd like to download. For more information regarding NAIP imagery, visit https://www.fpacbc.usda.gov/geo/index.html.
NAIP Point Cloud (2017)
To access these data, you can use the index map to identify which tiles you need for your area of interest. If you have fewer than 10 tiles, you can email Jeff Oliver with the list of files to retrieve. Alternatively, you can retrieve the files yourself at https://data.cyverse.org/dav-anon/iplant/projects/azgs/GIS_Data_NP112_NP212/.
Using the raw non-orthorectified aerial imagery captured during the 2017 NAIP acquisition, a point cloud was developed as a product using photogrammetric techniques. All PC tiles are provided for download in LAZ format. Note that LAZ files cannot be loaded into many GIS applications (i.e. AcrPro and ArcMap) and need to be converted into the LAS format. One option for this is by using the LASzip tool (USGS video tutorial on how to use this tool).
To be clear, this is a photo-interpreted point cloud. Although it is the same data format (.laz) as LiDAR it is not actually LiDAR and is not a classified product in the same way as traditional LiDAR. Example of how this data can be used: create DSM and difference against the 2015 DEM to get a rough height-above-ground product.