The Harris Geospatial maintenance program allows you to pay a reasonable yearly fee and receive new products versions and updates as they become available, as well as access to maintenance account managers.
Tuesday, December 15, 2015
This software release includes the new and enhanced features listed below. See the following sections:
ENVI reads and displays imagery from the following sensors and data formats:
Linux support for ENVI LiDAR has been added for the ENVI API. The ENVI LiDAR user interface is not available on Linux installations.
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 as 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 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.
The Cursor Value tool was redesigned as follows:
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:
The Dataset Browser now supports HDF5 one-dimensional datasets.
The ENVI API Programming Guide has a new "Frequently Asked Questions" topic.
The following ENVITasks are available:
Calculate a cloud mask for Landsat imagery using the Fmask algorithm.
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.
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.
Register a raster with GeoServer.
Register a vector with GeoServer.
Perform a refined RPC orthorectification by automatically generating GCPs from a reference image.
The following objects and methods are available:
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).
Construct an ENVIRaster from a source raster that has a simple mathematical expression applied on a pixel-by-pixel basis.
Save a raster layer to TIFF format.
Check if a specified metadata field exists.
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.
This is an abstract interface class that is subclassed by any class that wants to support serialization to a hash representation.
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.
Create a new ENVIRaster from a file or uniform resource indicator (URI).
Return a hash describing these objects. You can use this information in a later ENVI session to restore the objects using the ENVIHydrate function.
© 2015 Exelis Visual Information Solutions, Inc., a subsidiary of Harris Corporation. All Rights Reserved. This information is not subject to the controls of the International Traffic in Arms Regulations (ITAR) or the Export Administration Regulations (EAR). However, this information may be restricted from transfer to various embargoed countries under U.S. laws and regulations.
Number of views (5668)/Comments (3)
1/27/2016 9:56 AM
The new Cursor Value tool is awesome. That is pretty much exactly what I've been asking for quite a while! :)
ngoc Quang Chi
3/13/2016 12:31 AM
Link download Envi 5.3 Service Pack1 ?
4/12/2016 4:21 PM
please i really need to know how to perform haze removal on landsat images using the flaash atmoshperic correction wizard
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