3D City Modeling

I'll be hosting a webinar on December 9th entitled: "3D City Construction Workflows: From Collection to Presentation". This will be an opportunity for us to explore workflows for planning projects and developing 3D building content data, which can then be fed into various GIS and mapping applications. We'll also take a look at data presentation: methods for visualizing and sharing the data.

3D city modeling is a rather nebulous topic, and there are many ways to create 3D city models. Here are a few different options:

- Automatically extruding 2D building polygons digitized from an ortho, either from a rooftop Z value or guesstimating the height. This is the "quick and dirty" method.
- Manually model each building individually and tag it with an XY location (often guesstimating the spatial dimensions). These models may be based on ground photos, oblique imagery, or a combination.
- Photogrammetrically measure and extrude buildings.
- Photogrammetrically measure and extrue buildings, and then model further detail and add elements such as photo-texture.

The webinar will primarily focus on the 3rd option: using photogrammetric tools to measure buildings. In addition to the actual extraction process, other discussion points such as data capture, data quality, accuracy, and other topics will be outlined as well.

If you're a GIS/photogrammetry/mapping professional, please tune in to one of the scheduled webinars. You can sign up here.

LPS 9.3.1 Now Available!

We've just released our first Service Pack for LPS 9.3, called LPS 9.3.1. It is available from our support site and is located in the "Fixes and Enhancements" section. In addition to numerous bug fixes, LPS 9.3.1 (which is a shared Service Pack with ERDAS IMAGINE) also contains the following features and improvements:

LPS Core

• Added required entry of Average Terrain Elevation when creating a block file for Orbital Pushbroom sensors. This entry overrides the generally less accurate method of using the sensor metadata to derive a mean elevation.

Stereo Point Measurement/Classic Point Measurement

• Improved and simplified image loading.
• Added “Create Ground Control Point” feature that calculates 3D ground coordinates from image points which are measured in at least two images. This is particularly useful in transferring control points from more accurately oriented imagery into lower accuracy imagery.
• Improved several icons to maintain consistency with other dialogs in LPS and IMAGINE.
• Improved image tracking to use the mouse wheel to adjust the image positions in relation to each other and remove the x-parallax.

RPC Generation

• Added fields to give the user the ability to control parameters of the RPC fit cube. This can help improve the fit accuracy.
• Added an option to output a report file that shows where higher residuals are falling, check point and fit point statistics, and other information that help to refine the results on subsequent generations.

LPS Core Triangulation

• Improved RPC refinement by automatically detecting points with parallel rays and using these parallel rays as an additional constraint. This eliminates the need to manually delete points with no convergence.

ERDAS MosaicPro

• Improved memory management during Image Dodging and seamline generation.
• Faster seamline refreshing after editing and undo.
• Improved performance when running MosaicPro with a shapefile or an AOI with multiple polygons as a single output mosaic.

Defense Productivity Module

Image Slicer

• Added capability to input active area.
• Named all segment IDs from West to East regardless of how images were captured.
• Improved quality of segment boundary computation.
• Added an option to trim the nonoverlapping portions of the stereo segment image pairs.
• Changed the pyramid generation so it is driven by the IMAGINE preferences rather than always making pyramids after segmentation.

TFRD AMSD Calibrator

• Eliminated requirement that LPS be installed to generate an Image Slicer project file (.isproj).
• Added an option to output the rectangle and stereopair accuracy values from AMSD to a text file.

IMAGINE Radar Mapping Suite

• You can now use the Subset Processing Step to extract portions of the input images in InSAR from which to generate a DEM.
• Multilook factors are now displayed directly on the Reference DEM Processing Step of InSAR.
• Coherence window values are now edited within the Interfere Processing Step of InSAR, and a working Coherence image is generated and available for viewing.
• The Register step in InSAR has been renamed Coregister in which the match image is coregistered to the reference image.
• In the Coregister step, there are now two tabs named Coregistration Input Parameters and Coregistration Output Coefficients. The Coregistration Output Coefficients tab contains a CellArray reporting polynomial coefficients which describe the pixel shift of the match image along the x-direction and along the y-direction.
• In the Height step of InSAR, you can now select an interpolation method for the resample process as part of the chosen rectification method.

ERDAS IMAGINE – General

• Chooser icons, such as those for selecting colors or Annotation styles, now have two portions. Click the top portion to open the Chooser dialog directly; or click the bottom portion to open the selection menu as before.

IMAGINE GLT

• GeoPoint Annotation has a new Properties dialog where you can select a template for the text to be displayed. You can also configure options indicating where the label is to be placed and whether or not there is a leader line from the label to the point. The text template can be a dynamic coordinate (as before), an incrementing number, a static string or a combination of coordinate or incrementing number and static string.

IMAGINE Viewer

• In addition to the Annotation Alignment tool, the Annotation menu and tool palette now contain separate options for aligning annotation vertically or horizontally.
• You can now save a Footprint layer in the Viewer/GLT as Annotation or as a shapefile.

IMAGINE Composer

• Leading zeros are now displayed for coordinates in Grid/Ticks.
• You are now able to specify the text to be displayed for the units in an Annotation Scale Bar.
• When generating an Annotation Grid/Tick, you can now specify a rotation angle for the coordinate labels.

ERDAS on Twitter

If you want to follow ERDAS news and updates on Twitter, feel free to check us out at www.twitter.com/erdas.

Chandrayaan-1 Moon Probe

I've seen a lot of mainstream media coverage of India's Chandrayaan-1 moon probe recently. The significance for the mapping community is the mission goal of creating a 3D lunar surface model.

This page on the Indian Space Research Organization's site outlines the specifications of the various payloads:
1) Terrain Mapping Camera (TMC)
2) Hyperspectral Imager (HySI)
3) Lunar Laser Ranging Instrument (LLRI)
4) High Energy X-ray Spectrometer (HEX)
5) Moon Impact Probe (MIP)

Of particular interest are the TMC and the LLRI.

The TMC will have a 5 meter spatial resolution and pushbroom sensors in forward, nadir and reverse directions. This will allow for stereo data collection that can be used for topographic mapping applications. A concise summary document is here, which I would recommend for anyone interested in the topic.

The LLRI will is an excellent complementary sensor to the TMC, and as one would expect from the name, is essentially a on-board LIDAR sensor. A summary document is available here.

It is also interesting to note that the Chandrayaan-1 mission is the first in a series of five planned missions. These are all outlined on the ISRO page here.

It'll certainly be interesting to see the data products Chandrayaan-1 will produce. To my knowledge this is the first lunar mapping project since the Clementine mission in 1994, which collected much of the lunar surface at 7-20 meters GSD with it's camera (not in stereo, I believe). LIDAR data was collected during that mission as well.

Sensor Spotlight: CARTOSAT

Today's post will highlight the CARTOSAT-1 and CARTOSAT-2 sensors. CARTOSAT-1 was launched in 2005 and features two panchromatic cameras for stereo imagery capture. The cameras cover a 30 meter swath and the resolution is approximately three meters. Many of the sensor features and are located on the ISRO site here. For a good white paper on CARTOSAT-1, presented at the ISPRS conference in Beijing, see here. The authors outline the processing workflow for CARTOSAT-1 data in LPS, consisting of setting up the orientation, performing automatic terrain extraction, and finally orthorectifying the images. While the processing was performed on CARTOSAT-1 data, the workflow would also be very similar for CARTOSAT-2.
The paper highlights some software improvements we implemented between LPS 9.0 and 9.2 SP1, as some of the initial processing was performed in LPS 9.0. The improvements specifically pertained to the LPS ATE (Automatic Terrain Extraction) module, where we added quality improvements in the correlator. The authors found the ATE results with LPS 9.2 SP1 to be acceptable, with errors general under 2m. It is also important to note that we made Adaptive ATE available for satellite sensor models with the recent release of LPS 9.3, so I suspect the accuracy could even be further improved.

Here is another ISPRS paper from 2007 outlining some advances in CARTOSAT-1 data processing. It also highlights the use of LPS for the terrain processing component of the workflow.

CARTOSAT-2 was launched in early 2007 and also features two panchromatic sensors, featuring a greatly improved resolution of under one meter. A spec sheet from ISRO is here. The wikipedia article makes some interesting statements about resolution (80cm) and pricing, but I haven't been able to verify these statements. This paper, also from the ISPRS conference in Beijing, has some great information on both satellites, as well as some further details on the terrain processing workflow. LPS was used as well in this paper, although it does not state the version number.

Note that in addition to using LPS ATE for automatic terrain extraction, the LPS Terrain Editor can be used to view the imagery in stereo and perform interactive terrain editing (from manual compilation to editing an automatically correlated surface).
Note that in addition to the CARTOSAT-1 and 2 sensors, there is also a CARTOSAT-2a sensor that is reserved for military usa.

ERDAS Photogrammetry Movies