Remote Sensing of the Environment

Introduction & Goal In this lab, the objective is to develop skills in performing photogrammetric tasks on vertical aerial photographs and satellite images. Overall, this lab will help students develop skills and understanding the mathematics behind the calculation of photographic scales, measurement of areas and perimeters of features, calculating relief displacement, and performing orthorectification on a blog of vertical aerial photographs.  Methods For the first part of this lab, JPEG images were used to calculate photographic scales when measuring real world areas, topographic relief displacement, and perimeters. Firstly, the image Eau Claire_West-se.img (an aerial photograph) was used to determine the distance between points A and B on the JPEG photograph to overall determine the scale. Because the given distance is 8822.47 ft, you must convert this to inches, and measure the distance from A-B with a ruler (inches). Afterwards, utilize the scale equation: Scale (S) = Photo di

Introduction & Goal The objective of this laboratory exercise is to help students develop skills in  Erdas Imagine 2020 and  ESRI ArcGIS Pro  software that include essential basic knowledge on LiDAR data structure and processing. This lab generally helps students understand processing and retrieval of surface and terrain models and processing and creation of intensity image and other products that derive from the point cloud. Methods & Data When opening Erdas Imagine, we displayed individually LAS files and examined whether there are overlapping points at the boundaries of the tiles, because Lidar data tiles mostly have overlaps at the tile boundary to prevent void areas. We added all the lidar point cloud files provided by the UWEC Geography department (.las). After loading the . las files into the viewer, we were able to zoom into any tile of choice to see individual lidar points. We then utilized ArcGIS Pro for the remainder of this lab because it contains easier workflows c

Introduction & Goal This lab introduces an image preprocessing method known as geometric correction. This lab generally helps students understand the two different types of this method that are performed on satellite images prior to gathering details or data on biological, physical, sociology, and cultural information from these images. Methods In this lab, we used a United States Geological Survey (USGS) 7.5-minute digital raster graphic (DRG) image of the Chicago metropolitan statistical area and surrounding areas to correct a Landsat TM image of the same area. We then utilized a Landsat TM image for eastern Sierra Leone, Africa to rectify a geometrically distorted image of that area. By opening Erdas Imagine 2020 and displaying the Chicago raster graphic (DRG) into the viewer, we first compared images side by side as well as utilizing the swipe  tool to observe the distortion of the two images. Figure 1) Display of Sierra Leone Africa from the second part of the lab with the Swi