Remote Sensing Terminology
The Landsat program is a series of American satellites that use the visible and infrared parts of the spectrum to record images of the Earth's surface. It is the longest running enterprise for acquisition of satellite imagery, and started back in 1972. The most recent, Landsat 8, was launched in 2013.
Landsat satellites are located in a polar orbit, which allows them to provide images of almost all of the Earth's geography. As the satellite orbits the Earth from pole to pole, it appears to move from east to west because of the Earth’s rotation. This apparent movement allows the satellite to view a new area with each orbit.
Determining land cover has become one of the most common uses of Landsat Imagery and remotely sensing generated images all around the world.
The LiDAR sensor produces a series of point measurements that consists of geographic location (X & Y) and height (Z) of both natural and man-made features, and can be further processed to produce several different products and integrated into a Geographic Information System (GIS).
Click here to learn more about LiDAR
The amount of energy returning to the sensor (known as backscatter) is dependent upon the topography, roughness, and dielectric properties (moisture). Areas of an image with low backscatter appear dark (such as water), while areas of high backscatter appear as light gray levels approximating white shades. By interpreting the various gray tones, textures and patterns, the user can detect information regarding to the regions geologic lithology and structure.
In much of remote sensing, the process involves an interaction between incident radiation and the targets of interest. This is exemplified by the use of imaging systems where the following seven elements are involved. Note, however that remote sensing also involves the sensing of emitted energy and the use of non-imaging sensors. Click here to learn more about Remote Sesning
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Below are a few 3D Toronto images from a demonstration that I gave comparing Esri Arc Scene with FLY in PCI Geomatica. I generated the digital surface model (DSM) from some demo LIDAR all hits data that we had. The coverage area is for a small portion of downtown Toronto centered around Toronto City Hall.
This simple EASI script used with the MODEL command in PCI will batch convert vector files stored in PCIDSK (PIX) format into Shape File (SHP) format with the exact same file name as the input files. This was originally created for PCI Geomatica v9.1 but was last tested and working with no problems in PCI Geomatica v10.0
! Batch Export PIX Vector to SHP Script
! This script will export vector segments from PIX files located in a
! given directory into Shape files and place the new files into the same
! directory. The script assumes that no SHP files with the same names
! already exist and all the input files are setup the same with the
! vector segments stored the same.
! Define variables
!to store location of input & output files
local string in_files
!for the file format and extension types
local string type, ext
local string bn, fn
!to store directory listing of input files
local mstring dirlist
!to store vector segment number
local integer vec
local integer i
! Clear the EASI window and then show the header information
PRINT @(1 ,1,CLREOS)
print @reverse,” ‘Batch export PIX vector to SHP’ EASI Script “,@alloff
print ” This script will export vectors from PIX files in a given directory ”
print ” into SHP format using the same file names as the input files. ”
print ” All input vector files are expected to be setup the same with all ”
print ” vectors to be exported, stored using the same segment number.”
! Collect input from user
print “Enter the directory that contains the PIX files to export to SHP:”
input “>” in_files
print “Enter the vector segment number that the vector is stored in:”
input “>” vec
! Get the contents of the directory
dirlist = getdirectory(in_files)
let $Z = “\
for i = 1 to f$len(dirlist)
! Extract parts of the filenames
fn = in_files + $Z + dirlist[i]
ext = getfileextension(fn)
bn = getfilebasename(fn)
if (ext ~= type) then
print “Exporting:”, bn, “from PIX to SHP”
! Set up the parameters and execute the FEXPORT command
fili = in_files + $Z + dirlist[i]
filo = in_files + $Z + bn
dbvs = vec
PRINT @(1 ,1,CLREOS)
PRINT @(1 ,1,CLREOS)
print @reverse,” ‘Batch export PIX vector to SHP’ EASI Script Finished “,@alloff
Below is a simple EASI script that when used with the MODEL command in PCI will clip the unnecessary excess portions of an air photo mosaic created from Ortho Engine to an irregular buffered shape around a set study area. This was originally created for PCI Geomatica v9.1 but was last tested and working with no problems in PCI Geomatica v10.0 – Just copy the code below into a blank text file and edit as needed.
! Irregular_Polygon_Clip [bitmap_clip.eas]
! Ted MacKinnon – tmackinnon.com
! This simple script used with the MODEL command in PCI EASI
! will clip the unnecessary excess portions of an airphoto mosaic
! to an irregular buffered shape around the study area.
! The working file ‘working-file.pix’ has the existing
! mosaic image located in the first three channels,
! an existing irregular shaped polygon bitmap and
! three empty 8 bit channels.
! %%2 is the bitmap mask of the irregular shape
! %1, %2, %3 are the RGB existing image channels
! %4, %5, %6 will be the new modeled RGB image channels
! the RGB value of 255, 255, 255 will set the background to white
! Simply change the file name to use this script with a different
! file and ensure that the channels and segments are setup the same
! Set up and run the model
MODEL ON “working-file.pix” OVER dbiw
if %%2 = 1 then
%4 = %1;
%5 = %2;
%6 = %3;
%4 = 255;
%5 = 255;
%6 = 255;
! Export the resultant channels to a new file
FILI = “working-file.pix
FILO = “mosaic_clipped.tif
DBIC = 4,5,6
FTYPE = “TIF
FOPTIONS = “”
Color shaded relief (CSR) model created using a DEM of Vancouver Island, British Columbia using PCI Geomatica software. The …
A pansharpened image fused with a DEM to help provide an extra 3D effect making the topographic features of Gatineau Park stand out more …
The following images are enhanced LandSAT images of Trout Lake, Nova Scotia (popular fishing place on the South Mountain – south of the town of Middleton) created using PCI Geomatica. The first image is a True Color Composite (TCC) showing bands 3,2 an 1. The second one is a False Color Composite (TCC) showing bands 7,4 and 3 and helping to clearly define the various clear cuts in the area. [Both images beloware actually low res versions of the original images]
The two images above represent artificial three dimensional perspective views perspective views from different points of origin featuring color shaded relief models that were created from high resolution LIDAR digital surface models as part of a LIDAR flood modeling graduate research project.
The study area for the project consisted of the coastal Gulf Shore region of southeastern New Brunswick from Kouchibouguac National Park south to Jourimain Island (location of the Confederation Bridge). The coastal zone of New Brunswick is a picturesque fishing region that boasts several kilometers of sandy beaches with some of the warmest salt water temperatures north of Virginia.