Posts

Lab 8: Spectral Signature Analysis & Resource Monitoring

Image
Introduction: This lab is set to help familiarize students with spectral reflectance signatures of various objects found on the Earth's surface that can be made visible in aerial photographs. Student will first collect these signatures from remotely sensed images before graphing and analyzing their outputs in order to confirm their validity using the spectral separability test. In analyzing the combination of these remotely sensed images and object signatures, students will ultimately determine and further monitor the health conditions of various vegetation and soils. Methods: Part One: Spectral Signature Analysis- For Part One of the lab, students used the Polygon and Raster Supervised Signature Editor tools synced with Google Earth in Erdas to collect spectral signatures of various feature objects. From a satellite image of Eau Claire county, students collected a total of 12 signatures, including those from standing water, still water, deciduous forests, coniferous forests...
Post a Comment
Read more

Lab 7: Photogrammetry

Image
Introduction: The purpose of this lab is to provide students with a foundation in the performance of photogrammetry tasks, including the calculation of image scale and relief displacement, and measuring areas and perimeters of aerial imagery features. Additionally, the lab introduces students to stereoscopy and orthorectification tasks for satellite imagery.  Methods & Results: This lab ultimately consisted of three parts: Part 1 : Scales, Measurements, and Relief Displacement, required students to calculate scales and relief displacement using formulas provided to us in lecture. Limited information was given pertaining to measurements taken from the real world, and then using the aerial photographs, direct measurements could be made with something as simple as a ruler for comparison in completing the formula for scale. Figure One shows an example of the relief displacement we observed between two photos. On the left, we can clearly visualize the relief displace...
Post a Comment
Read more

Lab 6: Geometric Correction

Image
Introduction The goal of this lab is to familiarize students with an image pre-processing technique known as as geometric correction. Students are able to exercise this skill using two different types of rectification pre-processing: image-to-map and image-to-image rectification. Methods For both sections, students use the Control Points tool under the Multispectral toolset to begin the geometric correction process. Using a Polynomial Geometric Model, Erdas users have the option to choose the number of polynomials they wish to model in their rectification transformation. The number of polynomials required for use may vary based on the extent of the distortion between the original and referenced image.  In Part One , the distortion that exists between the original image and the referenced map is minimal. Students use a 1st order polynomial equation to rectify the desired image. A 1st order polynomial equation requires a minimum of three Ground Control Points (GCPs) betw...
Post a Comment
Read more

Lab 5: LiDAR and Remote Sensing

Image
Introduction: For this lab, students experiment with LiDAR in remote sensing, learning to process and generate a number of surface models, terrain models, and intensity images through the use of point cloud data.  Methods: Part 1: Point Cloud Visualization in Erdas Imagine- In Part 1 of the lab, students upload the LAS dataset into ArcMap and examine its properties. Special notes are taken regarding information found in the Metadata and the Tile Index of the dataset. Since there is no particular projection for the original dataset, one will have to be prescribed. Part 2: Generating a LAS Dataset and Exploring LiDAR Point Clouds with ArcGIS- Using ArcCatalog, students generate a new LAS dataset in their Lab 5 folder. All LAS files used in Part 1 are selected for the new dataset, and statistics are calculated for input into the new LAS Dataset. The Metadata, examined in Part 1, revealed the intended projection to be used for the files collected in the dataset: NAD 1983 H...
Post a Comment
Read more

Lab 4: Remote Sensing of the Environment

Image
Introduction: The purpose of this lab is to further familiarize students with ERDAS photo analysis capabilities, including image pre-processing, stitching, and optimizing. In the following exercise, students will execute a series of several new capabilities:      1. Image Subsetting      2. Image Fusion      3. Radiometric Enhancement      4. Syncing Image Viewer with Google Earth      5. Resampling      6. Image Mosaicking, and      7. Binary Change Detection (or Image Differencing) Methods & Results: Part One: Image Subsetting of a Study Area- There are two different methods that can be used for subsetting satellite images:       1. The use of an Inquiry Box      2. Delineating an area of interest (AOI) with the use of a shapefile Figure 1: Inquiry Box Method of Image Subsetting The each method can be easily execute...
Post a Comment
Read more