GIS
Chapter 6 Mapping Census data with R | Analyzing US Census Data
Data from the United States Census Bureau are commonly visualized using maps, given that Census and ACS data are aggregated to enumeration units. This chapter will cover the process of map-making...
Chapter 5 Census geographic data and applications in R | Analyzing US Census Data
As discussed in previous chapters of this book, Census and ACS data are associated with geographies, which are units at which the data are aggregated. These defined geographies are represented in...
2255 STONE MOUNTAIN LITHONIA RD, LITHONIA, GA 30058 | Climate Risk Report | First Street
2255 STONE MOUNTAIN LITHONIA RD, LITHONIA, GA 30058 has risk from flooding, risk from wildfire, and risk from windstorms
APIs
rspatialdata
Bookdowns
TLDRLegal - Software Licenses Explained in Plain English
Lookup open source licenses summarized & explained in plain English.
List federal state county city GIS servers
An open and universal framework for processing spatial omics data. — spatialdata
AI
What Is Emergence? - John Templeton Foundation
The Perfect Modern OpenAPI Workflow
Discover how OpenAPI can revolutionize your API development process with a streamlined, Git-centric workflow. Learn about design, governance, and automated deployment of documentation, mocks, and SDKs, all while maintaining a single source of truth.
Learn - OpenAPI Spec
OpenAPI helps speed up API development. You Define, mock, and test REST APIs using a single truth/specification. Ideal for dev and QA teams adopting contract-first workflows.
Deeply nested schemas can become unwieldy and hard to maintain. For instance, a User object containing an Address object, which in turn contains a Location object, can quickly become complex.
Why it matters: Simplifying schemas enhances readability and maintainability, making it easier for both developers and consumers to understand and work with the API.
Defining schemas, parameters, and responses inline repeatedly instead of using the components section leads to redundancy and potential inconsistencies.
Why it matters: Leveraging components promotes reusability and consistency across the API specification.
Logically group your APIs into smaller, domain-specific specs — like auth.yaml, payment.yaml, orders.yaml.
Use tags in OpenAPI to group related endpoints (like Order, Customer, Admin) even within a single file if needed.
/openapi
├── auth.yaml
├── customer.yaml
├── orders.yaml
└── components/
└── common-schemas.yaml
LandRise (LightPath)
R - ShinyIntroduction to GIS Programming — Introduction to GIS Programming
Kong's AI-powered OpenAPI spec builder
Generate high-quality OpenAPI specs in seconds that are ready to share, test, and ship.
OpenAPI Spec Generator - AI Prompt
Generates OpenAPI 3.1.0 specifications from diverse inputs. Free Programming & Code prompt for ChatGPT, Gemini, and Claude.
Chapter 9 Use httptest2 | HTTP testing in R
In this chapter we aim at adding HTTP testing infrastructure to exemplighratia2 using httptest2. For this, we start from the initial state of exemplighratia2 again. Back to square one!...
Intro to GIS and Spatial Analysis
This is a compilation of lecture notes that accompany my Intro to GIS and Spatial Analysis course.
Welcome | Geocomputation with R
Welcome | Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data.
Cursor – Working with Context
How to work with context in Cursor
Intent context defines what the user wants to get out of the model. For example, a system prompt usually serves as high-level instructions for how the user wants the model to behave. Most of the “prompting” done in Cursor is intent context. “Turn that button from blue to green” is an example of stated intent; it is prescriptive.
State context describes the state of the current world. Providing Cursor with error messages, console logs, images, and chunks of code are examples of context related to state. It is descriptive, not prescriptive.
Together, these two types of context work in harmony by describing the current state and desired future state, enabling Cursor to make useful coding suggestions.