Lidar of Pensacola Florida

This module covers one common active sensor: LIDAR or Light Detection and Ranging.

LIDAR is an active remote sensing system that uses laser light instead of microwaves to illuminate the target area. The reading covered basic information on how these processes work and the benefits of each method. A decent bit of literature to read is the Airborne Altimetric LIDAR Tutorial. This tutorial gives an overview of how LiDAR works, how data is collected, how it is processed and the many applications for LiDAR.

Supervised Classification

The links posted below are for a map created using ERDAS IMAGINE 2010 software and the ground control points as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly

Though the lab focused on a supervised classification, this module covers the different methods of classifying multispectral images into different patterns that represent clusters of statistically different sets of multiband data, which can be correlated into separable classes. The two main methods of classifying images are Unsupervised and Supervised Classification.

I found this lab more time consuming that expected.  I lost count of how many iterations were done to get to this point.  One thing that did work well for me was to create a flow chart for each of my steps and to take careful notes.  This ensured that precisely the same steps were taken for each class which intern created a MUCH more consistent set of results. Select .xps link below or .pdf map for a larger view. germantown_18d_classified.xps

GeoRectification

The links posted below are for a map created using ERDAS IMAGINE 2010 software and the ground control points as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly.

This week's lab objective is learning to use control points from one image or map to rectify another image.  In this case we were provided a USGS map of Pensacola as our ground control point source.

Pensacola_Rectified image (bands 3,2,1)

In the "real" world, one always wants to check and recheck work before it is submitted.  This is a little bit of a challenge since the image is a much coarser resolution than what seems to be available on the map.  In this case the ground "truth" comes from the map. So once I was satisfied with the selection of the WHICH points were to be used I let the imagery point position float until I was satisfied with the visual position and RMS error. Click here for a view the ground control point results. 

Fast forward to the completed image you see below (left side).  The RMS was excellent, (<1), the coordinates seemed right so one more step was taken.  The rectified image and the map image were placed in separate windows, linked and inquire cursors activated.  Voila a perfect match.  I could also have dropped them in the same window and looked to see how they overlaid each other but that will have to be for another day.

Look at the cross hairs on both images.  They are centered on the runway intersections

Module 2 - LandSat Band Combinations

The links posted below are for maps created using ERDAS IMAGINE 2010 software as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly.

This module covers satellite based sensors that operate in the visible in infrared wavelengths. 

"Features can be identified visually, by looking at the image, but also by examining the histograms under the layer information.  Certain features have definite and relatively constant reflective properties and therefore will always fall at a certain spot on the histogram.

In this exercise we examined the reflectance values found in the layer histograms to identify real features on the map." from lecture material

 Map of showing shadows on slopes of the Olympic Mountains using false Color Infrared (CIR).  I used layers 4, 3 and 2.  There was a spike between pixel values 12 and 18. 

 Map of Lake Tapps with dissolved calcium suspensions which appear as bright blue CIR and Black in layers 5 and 6. There was a spike around the pixel values of 9-11.

 Map of Grays Harbor shallow estuary showing basin bottom using the bathymetric combination with layers Red=3, Green = 2 & and Blue = 1.