Introduction In this project, I completed a full ortho mapping workflow in ArcGIS Pro to create accurate satellite imagery products. The goal was to correct geometric distortion in raw satellite images so they can be reliably used for mapping, analysis, and measurement. This workflow included creating an ortho mapping workspace, performing block adjustment, adding ground control points, generating a digital
Most people think GIS is about making maps. In reality, the most valuable GIS work happens when spatial analysis supports real decisions. This lab focused on a practical problem faced by many communities: how to identify open-space parcels inside flood-prone areas that may qualify for FEMA Community Rating System (CRS) credits and potentially reduce flood insurance costs. What makes this
Introduction In a recent lab exercise, I worked with GeoDa, developed by the University of Chicago Center for Spatial Data Science, to examine spatial structure in geographic data. The objective was not simply to map values, but to determine whether patterns were statistically clustered, dispersed, or random. A map shows distribution. Spatial analysis tests whether that distribution has structure. What
In this lab for REM-617-01: Image Analysis & Information Extraction, we performed image manipulation and atmospheric correction using a Landsat ETM+ scene in ENVI. The assignment required stacking spectral bands, interpreting RGB composites, creating a Region of Interest (ROI), building a mask, computing statistics, and applying Dark Object Subtraction (DOS). The objective was to move from raw satellite data to
Abstract This study examines the relationship between median rent in 2008 and the percentage of households with children in 2008 across New York City sub-boroughs. Exploratory spatial data analysis was conducted using GeoDa to assess the distribution of data, identify outliers, and evaluate statistical relationships among variables. Results indicate that median rent is positively skewed, while the percentage of households
Abstract This study examines the spatial distribution of Airbnb listings in Albany, New York, and evaluates their statistical clustering using the Getis-Ord Gi* local indicator of spatial association. Listing locations were aggregated into 8,000-foot hexagonal areal units to address spatial structure and mitigate point-level noise. A fixed distance band of 12,000 feet with row-standardized spatial weights was applied to identify
Florida’s interstates are among the deadliest in the United States, and Brevard County has seen an increasing number of traffic accidents in recent years. In this lab, I focused on the workflow itself: taking crash points and road segments and using ArcGIS Pro analysis tools to turn them into defensible hot spot maps (including fatality hot spots and peak-time hot
Here we go again, dressed up as responsibility. This week, The Manila Times reported that the Philippines is considering mandatory social media user verification to curb abuse. The pitch is neat and comforting. Order over chaos. Safety over noise. Names over anonymity. The subtext is even clearer: if everyone can be identified, everyone can be managed. That is not about
Somewhere inside Malacañang Palace, there is a comforting belief that corruption can be outsmarted by software. Not confronted. Not dismantled. Outcoded. Just add blockchain, say transparency a few times, roll out a pilot, and suddenly decades of theft, patronage, and selective justice politely excuse themselves and leave. It never works that way, but we pretend it does. Yes, Filipinos might
Last week I finished reading If Anyone Builds It, Everyone Dies by Eliezer Yudkowsky, and it unsettled me in a very specific way. Not because it was alarmist or introduced a fear I had never considered, but because it exposed how much of our confidence in managing AI is borrowed from stories we tell ourselves about past revolutions. Stories that