This software release includes the new and enhanced features listed below. See the following sections:
Sensors and Data Formats
ENVI reads and displays imagery from the following sensors and data formats:
- Windows only: COLLADA 1.4.1 and 1.5. Support is provided for building extraction when using the ENVI LiDAR API. See the PointCloudFeatureExtraction Task and PointCloudProductsInfo help topics for details.
Platform Support
Linux support for ENVI LiDAR has been added for the ENVI API. The ENVI LiDAR user interface is not available on Linux installations.
Image Processing and Display
You can use the Data Manager to display an RGB layer using bands from different coregistered images. Example use cases include medical imagery, microscopy imagery, time series imagery, or any scenario where imagery is distributed with separate bands in separate files. See the "Manage Raster Layers" help topic for instructions. This only creates a layer for display. To create an RGB layer that you can export, continue to use the Layer Stacking tool or the ENVIMetaspectralRaster routine in the API.
Landsat GeoTIFF files with metadata (*MTL.txt) are displayed with the data ignore value header field set to 0. As a result, scan line and background pixels display as 'No Data'.
Use the Calculate Cloud Mask Using Fmask Algorithm tool to create a cloud mask for all Landsat sensors. ENVI uses the Fmask algorithm cited in the following references:
Zhu, Z., S. Wang, and C. E. Woodcock. "Improvement and Expansion of the Fmask Algorithm: Cloud, Cloud Shadow, and Snow Detection for Landsats 4-7, 8, and Sentinel 2 Images." Remote Sensing of Environment 159 (2015): 269-277, doi:10.1016/j.rse.2014.12.014 (paper for Fmask version 3.2).
Zhu, Z., and C. E. Woodcock. "Object-based cloud and cloud shadow detection in Landsat imagery." Remote Sensing of Environment 118 (2012): 83-94, doi:10.1016/j.rse.2011.10.028 (paper for Fmask version 1.6).
The ENVI LiDAR application automatically reprojects any background shapefiles that you import to match the projection of the current project.
Use the Generate GCPs From Reference Image tool to automatically generate ground control points (GCPs) for an input raster. The process works by matching and using the geographic coordinates of an orthorectified base image. The elevation values of the GCPs are calculated from a DEM raster. The input raster must have an RPC spatial reference. This tool allows you to generate GCPs for further manipulation or for immediate use with applications such image-to-map registration, Rigorous Orthorectification, DEM Extraction, and the RPC Orthorectification workflow.
Use the RPC Orthorectification Using Reference Image tool to perform a refined RPC orthorectification by automatically generating GCPs from an orthorectified reference image. This is an automated end-to-end solution; continue to use the RPC Orthorectification workflow if you want to edit GCPs and to review error statistics in an interactive environment.
The RPC Orthorectification tutorial uses new data files: an OrbView-3 source image, a National Agriculture Imagery Program (NAIP) reference image, and a National Elevation Dataset (NED) DEM at 1/9 arc-second resolution. The tutorial shows how to automatically generate GCPs in the RPC Orthorectification Workflow and with the RPC Orthorectification Using Reference Image tool.
User Interface
The Cursor Value tool was redesigned as follows:
- The main toolbar no longer contains a Crosshairs button. Instead, the Cursor Value dialog has an On demand updates button. When this button is active, you can click on a pixel or vector record in the display and a set of crosshairs (now called a probe) is displayed over that location. The Cursor Value dialog reports information for the selected pixel or vector record.
- When the On demand updates button is active, you can copy cursor value information to the system clipboard.
- Disable the On demand updates button to turn off the probe and to report real-time pixel information as you move around the display.
- You can report cursor value information for the top layer only or all available layers.
- When multiple views of georeferenced data are displayed and the On demand updates button is active, you can link the views. Moving the probe in one view will move it to the corresponding location in the other views.
The File > Open As menu was divided into different categories of sensors and data formats.
The Data Manager, Layer Manager, and Spectral Profiles show wavelength colors next to each listed band if wavelengths are defined in the header file. Bands with invisible wavelengths are colored black. If an image has bad bands defined in the header file, those bands are marked with a warning symbol.
Spectral Profiles have a new Wavelength Color option to display visible wavelength colors along the x-axis.
Right-click on the View icon in the Layer Manager and select Show All Layers and Hide All Layers to show/hide all layers at once.
Right-click on a raster layer in the Layer Manager and select Export Layer to TIFF to save the full raster layer extent and image enhancements to a TIFF file, at full resolution.
Use the File > Export View To > Image File menu option to export all contents of a view to an RGB 24-bit image file in ENVI or TIFF/GeoTIFF format. The output image preserves any vector layers, annotation layers, feature counting layers, raster color slices, and image enhancements. You can set the output zoom factor, or if the view has a base standard map projection, you can set the output map scale.
The Navigation window of the ENVI LiDAR application contains a View Point Density setting that allows you to preview different point-density settings in the Main window. It does not affect the point density for final processing.
When distinct point classifications are present in the input file, click on the new Color by Classification button in the ENVI LiDAR application toolbar to color points by classification.
The Edit Raster Color Slices dialog was updated as follows:
Click on any color to display a color selection dialog where you can choose a different color for a specific range of values.
A new Export drop-down button lets you export the color slices to a shapefile or classification image.
The Dataset Browser now supports HDF5 one-dimensional datasets.
Programming
The ENVI API Programming Guide has a new "Frequently Asked Questions" topic.
The following ENVITasks are available:
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Task |
Description |
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CalculateCloudMaskUsingFmask
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Calculate a cloud mask for Landsat imagery using the Fmask algorithm.
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GenerateGCPsFromTiePoints
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Generate two sets of ground control points (GCPs) from input tie points. You can use the resulting GCPs in ENVI applications such as RPC Orthorectification and image-to-map registration.
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GenerateGCPsFromReferenceImage
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Generate GCPs for an input raster by matching and using the geographic coordinates of a reference image. You can use the resulting GCPs in ENVI applications such as RPC Orthorectification and image-to-map registration.
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RegisterRasterWithGeoServer
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Register a raster with GeoServer.
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RegisterVectorWithGeoServer
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Register a vector with GeoServer.
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RPCOrthorectificationUsingReferenceImage
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Perform a refined RPC orthorectification by automatically generating GCPs from a reference image.
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The following objects and methods are available:
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Object/Method |
Description |
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ENVINITFMetadata
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Return an IDL dictionary of NITF metadata from one or more NITF rasters. The top-level dictionary is a collection of IDL lists and dictionaries that contain the various segments of metadata: header, image, text, annotation (graphics), and data extension segments (DESes).
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ENVIPixelwiseBandMathRaster
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Construct an ENVIRaster from a source raster that has a simple mathematical expression applied on a pixel-by-pixel basis.
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ENVIRasterLayer::Export
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Save a raster layer to TIFF format.
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ENVIRasterMetadata::HasTag
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Check if a specified metadata field exists.
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ENVIView::Export
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Export all contents of a view to an RGB 24-bit image file. The output image preserves any vector layers, annotation layers, feature counting layers, raster color slices, and image enhancements.
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ENVIHydratable |
This is an abstract interface class that is subclassed by any class that wants to support serialization to a hash representation.
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ENVIHydrate |
Create ENVI objects from a hash description of their properties instead of using their dedicated routines. This allows you to store the object state and restore it in a later IDL session, or apply a virtual raster chain of processes by building a hash instead of calling multiple functions.
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ENVIURLRaster |
Create a new ENVIRaster from a file or uniform resource indicator (URI).
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ENVICoordSys::Dehydrate
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Return a hash describing these objects. You can use this information in a later ENVI session to restore the objects using the ENVIFactory function.
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ENVIGCPSet::Dehydrate
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ENVIGridDefinition::Dehydrate
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ENVIMosaicRaster::Dehydrate
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ENVIPseudoRasterSpatialRef::Dehydrate
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ENVIRaster::Dehydrate
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ENVIRasterSeries::Dehydrate
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ENVIRasterMetadata::Dehydrate
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ENVIROI::Dehydrate
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ENVIRPCRasterSpatialRef::Dehydrate
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ENVIStandardRasterSpatialRef::Dehydrate
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ENVISpectralLibrary::Dehydrate
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ENVITiePointSet::Dehydrate
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ENVIVector::Dehydrate
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