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LandPlanner.ai - Instant Parcel Analysis
LandPlanner.ai - Instant Parcel Analysis
What FEMA flood zone designations mean for development feasibility, insurance, construction costs, and lender requirements.
·landplanner.ai·
LandPlanner.ai - Instant Parcel Analysis
LandPlanner.ai - Instant Parcel Analysis
LandPlanner.ai - Instant Parcel Analysis
How SSURGO soil surveys predict agricultural productivity and construction costs before you close on land.
·landplanner.ai·
LandPlanner.ai - Instant Parcel Analysis
geospatial-software-engineering-101/chapters/02-modern-geospatial-technology.md at main · geoinformatica-consulting/geospatial-software-engineering-101
geospatial-software-engineering-101/chapters/02-modern-geospatial-technology.md at main · geoinformatica-consulting/geospatial-software-engineering-101
This repo provides an exhaustive look and comparison of all the history of geospatial software and gets non-spatial software engineers up-to-speed in geospatial technologies and concepts in this ne...
·github.com·
geospatial-software-engineering-101/chapters/02-modern-geospatial-technology.md at main · geoinformatica-consulting/geospatial-software-engineering-101
geoviz: thematic cartography
geoviz: thematic cartography
This package is an implementation of the geoviz javascript library. can be used to create a wide range of interactive, zoomable vector maps, taking advantage of d3’s many features: proportional symbols, pictograms, typologies, choropleth maps, spikes, tiles, Dorling cartograms, etc. It can also be used to create pretty static vectorial maps in SVG format, suitable for editorial cartography.
·riatelab.github.io·
geoviz: thematic cartography
aurora
aurora
Shiny-style authoring, stateless API deployment. Build the UI in R with bslib, compile it to a static asset, and serve it plus JSON routes with plumber2.
·aurora-govpe.github.io·
aurora
R Shiny and Google Cloud Run
R Shiny and Google Cloud Run
This tutorial walks through a simple point-and-click workflow starting from a GitHub repository with an app.R and Dockerfile and then shows how to connect it to Cloud Run.
·firsa.eu·
R Shiny and Google Cloud Run
The 4 Layers of Testing Every R Package Needs
The 4 Layers of Testing Every R Package Needs
Discover the essential layers of testing for robust R packages: unit tests, acceptance tests, code coverage, and mutation testing.
·appsilon.com·
The 4 Layers of Testing Every R Package Needs
From Data Analysis to Publication: Reproducible Research with R and Quarto – R-Ladies Rome
From Data Analysis to Publication: Reproducible Research with R and Quarto – R-Ladies Rome
In this workshop in partnership with RLadies BA, participants learned how to build reproducible research workflows with R and Quarto, integrating code, results, figures, and narrative into a single document for publishing manuscripts, reports, presentations, and more.
·rladiesrome.org·
From Data Analysis to Publication: Reproducible Research with R and Quarto – R-Ladies Rome
DuckLake
DuckLake
DuckLake delivers advanced data lake features without traditional lakehouse complexity by using Parquet files and your SQL database. It's an open, standalone format from the DuckDB team.
·ducklake.select·
DuckLake
Quack Remote Protocol
Quack Remote Protocol
We released Quack on May 12, 2026. Read the announcement blog post! The Quack extension turns a DuckDB instance into a server that other DuckDB instances (clients) can connect to over HTTP. This page covers the protocol at a glance and walks through basic usage on both sides of the wire. For the full list of functions, settings, and logging knobs, see the Reference. For configuring TLS and authentication / authorization, see Security. For user guides, see Guides. Warning Quack is under active development and the protocol, function names, settings, and defaults are still subject to change. This page documents…
·duckdb.org·
Quack Remote Protocol
Quack Remote Protocol
Quack Remote Protocol
The Quack protocol turns DuckDB into a client-server database.
·duckdb.org·
Quack Remote Protocol
vectra: Columnar Query Engine for Larger-than-RAM Data
vectra: Columnar Query Engine for Larger-than-RAM Data
A minimal columnar query engine with lazy execution on datasets larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(), group_by(), summarise(), joins, window functions) and common aggregations (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a pure C11 pull-based execution engine and a custom on-disk format ('.vtr'). Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a tiled raster format ('.vec') with overview pyramids and time cubes for larger-than-RAM raster data. Streams vector operations (spatial transforms, point-in-polygon and nearest-feature joins including a two-sided grid-partitioned join, select-by-location, clip, erase, dissolve, 'rasterization', 'polygonization', and contouring) through 'sf', and runs raster operations (zonal statistics, focal windows, terrain derivatives, resample or 'reproject' warp, polygon masking, map algebra, and 'mosaicking') in native C or over the tiled '.vec' format, one batch or tile at a time for data larger than RAM.
·gcol33.r-universe.dev·
vectra: Columnar Query Engine for Larger-than-RAM Data
Second Brain: Crafted, Curated, Connected, Compounded
Second Brain: Crafted, Curated, Connected, Compounded
A crafted digital vault of curated knowledge where insights and ideas connect and compound, modeled after a Zettelkasten to inspire learning and discovery.
·ssp.sh·
Second Brain: Crafted, Curated, Connected, Compounded
Escaping Walled Chat Gardens—A Chat History Converter
Escaping Walled Chat Gardens—A Chat History Converter
All my AI conversations were trapped inside various bot models, and my PKM had no access to them. Here is a converter that exports your chat history to local files for your knowledge management system.
·rodneydyer.com·
Escaping Walled Chat Gardens—A Chat History Converter
How to Backup All Your AI Conversations (ChatGPT, Claude, Gemini, and More)
How to Backup All Your AI Conversations (ChatGPT, Claude, Gemini, and More)
Your AI conversations contain decisions, solutions, and research that took real time to generate. Backing them up protects against account loss, platform changes, and the natural drift of conversation history. This guide covers backup options for every major AI platform.
·llmnesia.com·
How to Backup All Your AI Conversations (ChatGPT, Claude, Gemini, and More)
Keiran Flynn
Keiran Flynn
Keiran Flynn is the founder of LLMnesia, a local-first Chrome extension that indexes and searches AI conversations across ChatGPT, Claude, Gemini, and other platforms.
·llmnesia.com·
Keiran Flynn
How to Organise Perplexity Conversation History
How to Organise Perplexity Conversation History
Perplexity conversation history grows quickly with research threads, Pages, and Spaces. This guide covers every available method for organising your Perplexity history — from Library features to external tools — so you can find past research when you need it.
·llmnesia.com·
How to Organise Perplexity Conversation History
Practical Utilities for Package Development and Session Auditing
Practical Utilities for Package Development and Session Auditing
Provides a comprehensive collection of practical R utilities designed to streamline the full life cycle of package development, interactive data analysis, and session management. It offers tools for package management, development workflows, debugging, data processing, and system optimization. These utilities help R developers and data scientists automate release tasks, manage and scan dependencies, audit session states, optimize memory usage, and scramble sensitive Personally Identifiable Information (PII).
·zankrut20.github.io·
Practical Utilities for Package Development and Session Auditing
mapcn - Beautiful maps made simple
mapcn - Beautiful maps made simple
A collection of beautifully designed, accessible, and customizable map components. Built on MapLibre GL. Styled with Tailwind CSS. Works with shadcn/ui.
·mapcn.dev·
mapcn - Beautiful maps made simple
OGC NSDI Modernization Project | Advancing U.S. Spatial Data
OGC NSDI Modernization Project | Advancing U.S. Spatial Data
The OGC NSDI Modernization Project supports the U.S. FGDC in advancing a modern, interoperable national spatial data infrastructure that improves access, integration, and AI-ready geospatial resources.
·ogc.org·
OGC NSDI Modernization Project | Advancing U.S. Spatial Data
SDI Modernization Gateway - Open Geospatial Consortium
SDI Modernization Gateway - Open Geospatial Consortium
The Open Geospatial Consortium (OGC), in partnership with the U.S. Federal Geographic Data Committee (FGDC) and our members, is spearheading an ambitious
·ogc.org·
SDI Modernization Gateway - Open Geospatial Consortium
Know Your Data: The First Challenge in Geospatial Integration
Know Your Data: The First Challenge in Geospatial Integration
Discover why understanding your data is the first challenge in geospatial integration projects, from metadata gaps to CRS identification and stakeholder engagement.
Before we can integrate, publish, or analyze datasets, we need to understand what we are working with. This involves answering questions such as: Does the dataset contain Personally Identifiable Information (PII)? What is its size on disk? Is it spatially enabled? What Coordinate Reference System (CRS) does it use? What is the update frequency? What are the spatial and temporal resolutions? What file format is it stored in? Who is responsible for the dataset?
File size, file format, and in some structured formats, the CRS can be determined through direct inspection.
·ogc.org·
Know Your Data: The First Challenge in Geospatial Integration
stac-spec/best-practices.md at master · radiantearth/stac-spec
stac-spec/best-practices.md at master · radiantearth/stac-spec
SpatioTemporal Asset Catalog specification - making geospatial assets openly searchable and crawlable - radiantearth/stac-spec
Enable Cross-origin resource sharing (CORS)
·github.com·
stac-spec/best-practices.md at master · radiantearth/stac-spec