Due to several requests for how best to create an nDSM from given digital surface model (DSM) and digital terrain model (DTM) data, I decided to write this blog article [in previous GeoNet] for use as a future reference - and re-publish here in the community today. The article will assume that you organize your elevation data using mosaic datasets (MD) and raster functions for visualization/analysis.
If you create or modify a mosaic dataset in Pro 2.3, it can only be read and modified by ArcGIS Pro 2.3 and ArcMap 10.7 and served with ArcGIS Image Server 10.7 or newer. If you intend to publish your mosaic dataset to an image server prior to 10.7, do not create or edit it using Pro 2.3.
Note that for ArcGIS Pro 2.3, significant changes were made to the internal structure of the mosaic dataset so once modified using Pro 2.3, the updated mosaic dataset cannot be read on older versions.
In general, mosaic datasets created with older versions of ArcGIS can be read and handled with newer versions of ArcGIS. However, a mosaic dataset created with a newer version of ArcGIS may not be backwards compatible with older versions.
See the table below for mosaic dataset compatibility:
Users utilizing a mosaic dataset created with a new version that does not use any new features in that version, have been able to read a mosaic dataset with an older version. However, this may cause incompatibility issues.
The ArcGIS Pro 2.3.2 software patch enables mosaic datasets created or modified by Pro 2.3 and 10.7 to be read and modified by earlier versions (ArcGIS Pro 2.1 and 10.5 or later). Read more about it by clicking here.
Planet’s high-resolution satellite constellations image the entire world every single day. If you rely on imagery from Planet, managing this wealth of available data can be a challenge. That’s why Esri has added tools for managing PlanetScope and RapidEye imagery to its array of free, open-source tools that simplify image management in ArcGIS.
With the Python toolbox for managing Planet imagery, users can create mosaic datasets to manage Planet imagery within the familiar ArcGIS environment. With these scripts, data managers can streamline or automate the creation of scalable mosaic datasets, which can then be shared as image services with internal users or users outside your organization.
Imagery from Planet’s PlanetScope and RapidEye satellite constellations supports numerous applications—including mapping, deep learning, disaster response, precision agriculture, or simple temporal image analytics—which generate rich information products. Once managed with mosaic datasets, it’s straightforward for GIS or image analysts to exploit the temporal aspects of Planet imagery via an image service, to analyze the spectral data to draw actionable conclusions, to use the imagery to provide context within a GIS, and more.
The Python tools work by drawing on the Planet API to query, activate, and download PlanetScope or RapidEye Basic scenes over a given timeframe and area of interest. The imagery is then made accessible to users via the Planet Explorer app or the Planet API. The Planet toolbox is supported in ArcMap 10.5, and can also be used in ArcGIS Pro.
Ready to get started? Download the Python toolbox for managing Planet imagery, learn more about Planet’s high-resolution imagery, or try ArcGIS’s imagery capabilities with a free 60-day trial of ArcGIS Desktop.