Update TLDRs in blogs. (#341)

pgzmnk · web-flow · commit ca5abdec562c · 2025-01-24T09:32:49.000-07:00
* Update TLDRs in blogs.

* Update TLDRs in blogs v2.
diff --git a/blog/2024-04-09-duckdb/index.mdx b/blog/2024-04-09-duckdb/index.mdx
@@ -6,6 +6,7 @@ tags: [duckdb]
 unlisted: false
 ---
 
+**TL;DR Fused extends DuckDB to bring quick serverless operations on any scale dataset. The result is a lightweight, portable, and flexible system that is simultaneously scalable, cost-efficient, and simple to integrate across the stack.**
 
 import ImageFlow from '/blog/2024-04-09-duckdb/system-diagram.png';
 
diff --git a/blog/2024-08-27-pachama/index.mdx b/blog/2024-08-27-pachama/index.mdx
@@ -10,7 +10,7 @@ keywords: [pachama, sustainability]
 ---
 
 
-
+**TL;DR Pachama uses Fused to create maps on-the-fly for their sustainability platform.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-08-29-kevin/index.mdx b/blog/2024-08-29-kevin/index.mdx
@@ -8,6 +8,7 @@ hide_table_of_contents: false
 keywords: [computer vision, vegetation analysis, segmentation]
 ---
 
+**TL;DR Kevin used Fused to create a global vegetation segmentation layer without machine learning, displaying results as an interactive web map.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-05-dl4eo/index.mdx b/blog/2024-09-05-dl4eo/index.mdx
@@ -9,6 +9,7 @@ hide_table_of_contents: false
 keywords: [object detection, deep learning, airplane, ai, computer vision]
 ---
 
+**TL;DR Jeff Faudi used Fused for real-time object detection on 50cm satellite imagery, displaying results as an interactive web map.**
 
 
 import ReactPlayer from 'react-player'
diff --git a/blog/2024-09-12-danieljahn/index.mdx b/blog/2024-09-12-danieljahn/index.mdx
@@ -9,6 +9,7 @@ hide_table_of_contents: false
 keywords: [blog]
 ---
 
+**TL;DR: Fused is a versatile platform that serves as a code catalog, a parallel data processing engine, an app creation tool, a serverless HTTP endpoint generator, and an IDE.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-17-milindsoni/index.mdx b/blog/2024-09-17-milindsoni/index.mdx
@@ -9,7 +9,7 @@ hide_table_of_contents: false
 keywords: [Similarity]
 ---
 
-
+**TL;DR Milind analyzes global precipitation patterns using H3 indexing, cosine similarity, and Earth Engine data to create an interactive rainfall comparison app.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-19-overture/index.mdx b/blog/2024-09-19-overture/index.mdx
@@ -9,7 +9,7 @@ hide_table_of_contents: false
 keywords: [overture]
 ---
 
-
+**TL;DR Fused enables on-the-fly enrichment of Overture datasets using simple spatial joins.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-23-kristin/index.mdx b/blog/2024-09-23-kristin/index.mdx
@@ -8,7 +8,7 @@ hide_table_of_contents: false
 keywords: [crop,yield,agriculture]
 ---
 
-
+**TL;DR Fused streamlined Kristin's workflow to integrate CSV and NetCDF data directly from S3.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-24-marie/index.mdx b/blog/2024-09-24-marie/index.mdx
@@ -9,6 +9,8 @@ keywords: [marie,sentinel,landsat,hls]
 ---
 
 
+**TL;DR Pachama partnered with Fused to generate cloud-free HLS image composites, improving tropical forest monitoring and canopy height mapping for carbon conservation projects.**
+
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-09-25-pacific/index.mdx b/blog/2024-09-25-pacific/index.mdx
@@ -8,7 +8,7 @@ hide_table_of_contents: false
 keywords: [pacific spatial]
 ---
 
-
+**TL;DR Pacific Spatial Solutions uses Fused to streamline data workflows and feature engineering to predict national traffic risk in Japan.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-10-22-kristin/index.mdx b/blog/2024-10-22-kristin/index.mdx
@@ -8,6 +8,7 @@ hide_table_of_contents: false
 keywords: [crop,yield,agriculture]
 ---
 
+**TL;DR Kristin created a UDF to mask cropland areas using USDA data and run a Zonal Statistics workflow for corn yield predictions.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-10-24-stefano/index.mdx b/blog/2024-10-24-stefano/index.mdx
@@ -5,6 +5,7 @@ authors: [stefano]
 image: https://fused-magic.s3.us-west-2.amazonaws.com/blog-assets/social_stefano.png
 ---
 
+**TL;DR GLS Studio uses Fused to optimize Snowflake queries. This enables route planning in their ParcelPlanner app with H3-partitioned geospatial data served to a Honeycomb Maps frontend.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-10-29-durkin/index.mdx b/blog/2024-10-29-durkin/index.mdx
@@ -6,7 +6,7 @@ image: https://fused-magic.s3.us-west-2.amazonaws.com/blog-assets/gabe_social.pn
 ---
 
 
-
+**TL;DR Fused simplifies how Earth Observation data is processed to curate training data for AI models. Gabriel Durkin shows a Streamlit app he created to train and run land use and crop detection models.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-10-30-elizabeth/index.mdx b/blog/2024-10-30-elizabeth/index.mdx
@@ -6,6 +6,10 @@ image: https://fused-magic.s3.us-west-2.amazonaws.com/blog-assets/elizabeth_soci
 ---
 
 
+**TL;DR Elizabeth Cultrone analyzed NYC Taxi pickup data to identify neighborhood boundaries based on activity patterns. She created a UDF to implement H3 binning and similarity metrics.**
+
+Neighborhoods within a city have consistent characteristics but often have ill-defined boundaries. Some neighborhoods are more similar than others even though they're not nearby. Understanding these local boundaries and the demographics, dynamics and behaviors of different areas affects a wide range of business applications, including advertising, site selection, business analytics, and many more.
+
 
 
 import ReactPlayer from 'react-player'
@@ -25,7 +29,6 @@ import ReactPlayer from 'react-player'
 
 <br/>
 
-Neighborhoods within a city have consistent characteristics but often have ill-defined boundaries. Some neighborhoods are more similar than others even though they’re not nearby. Understanding these local boundaries and the demographics, dynamics and behaviors of different areas affects a wide range of business applications, including advertising, site selection, business analytics, and many more.
 
 
 
diff --git a/blog/2024-11-04-kent/index.mdx b/blog/2024-11-04-kent/index.mdx
@@ -7,6 +7,10 @@ image: https://fused-magic.s3.us-west-2.amazonaws.com/blog-assets/kent_social2.p
 
 
 
+**TL;DR Stephen Kent shares his journey making maps with Fused using Python and SQL.**
+
+I am a self taught developer and data enthusiast. I first came across the spatial data community when I saw a [Matt Forrest](https://www.linkedin.com/in/mbforr/) video on LinkedIn where he demonstrated how to visualize buildings from the [Vida Combined Building Footprints](https://beta.source.coop/repositories/vida/google-microsoft-open-buildings/description/) dataset with DuckDB. Immediately I thought, what if you could see all the buildings in a country, say, Egypt? I set out to do just that and made this map with DuckDB and Datashader.
+
 
 import ReactPlayer from 'react-player'
 
@@ -29,8 +33,6 @@ import ReactPlayer from 'react-player'
 
 
 
-I am a self taught developer and data enthusiast. I first came across the spatial data community when I saw a [Matt Forrest](https://www.linkedin.com/in/mbforr/) video on LinkedIn where he demonstrated how to visualize buildings from the [Vida Combined Building Footprints](https://beta.source.coop/repositories/vida/google-microsoft-open-buildings/description/) dataset with DuckDB. Immediately I thought, what if you could see all the buildings in a country, say, Egypt? I set out to do just that and made this map with DuckDB and Datashader.
-
 {/* truncate */}
 
 import ImageKent1 from '/blog/2024-11-04-kent/kent1.png';
diff --git a/blog/2024-11-21-foursquare-poi/index.mdx b/blog/2024-11-21-foursquare-poi/index.mdx
@@ -9,6 +9,8 @@ keywords: [foursquare, poi]
 unlisted: false
 ---
 
+**TL;DR The Fused Team made Foursquare's open dataset of 100M global places accessible via GeoParquet files which you can access via a UDF.**
+
 Foursquare just released an [open dataset](https://opensource.foursquare.com/os-places/) of over 100M global places of interest.
 
 We at Fused have partitioned these points into easily accessible GeoParquet files, and hosted them on [Source Cooperative](https://source.coop/repositories/fused/fsq-os-places/description)
diff --git a/blog/2024-11-26-sameer/index.mdx b/blog/2024-11-26-sameer/index.mdx
@@ -8,6 +8,8 @@ hide_table_of_contents: false
 keywords: [digitaltwinsim]
 ---
 
+**TL;DR DigitalTwinSim uses Fused with Ibis and DuckDB to model high-resolution wireless networks.**
+
 Sameer, co-founder of DigitalTwinSim, leads the development of advanced geospatial analysis tools to support the telecom industry in strategic network planning. [DigitalTwinSim](http://www.digitaltwinsim.com) specializes in using high-resolution data to optimize the placement of network towers ensuring reliable, high-speed connectivity.
 
 In this blog post, Sameer shares how he leverages [Ibis](https://ibis-project.org/) with a [DuckDB](https://duckdb.org/) backend, and [Fused](https://www.fused.io/) to model wireless networks at high resolution. This approach enables him to quickly generate network coverage models for his clients. He explains and shares a Fused UDF that processes data in an H3 grid to evaluate optimal locations for network towers.
diff --git a/blog/2024-12-03-guillermo/index.mdx b/blog/2024-12-03-guillermo/index.mdx
@@ -8,12 +8,10 @@ hide_table_of_contents: false
 keywords: [neon, hyperspectral, gee]
 ---
 
-
+**TL;DR Guillermo used Fused to build an interactive tool for exploring NEON hyperspectral data, making large-scale geospatial analysis more accessible and actionable for researchers.**
 
 import ReactPlayer from 'react-player'
 
-
-
 <ReactPlayer
     playsinline={true}
     className="video__player"
@@ -28,9 +26,6 @@ import ReactPlayer from 'react-player'
 <br/>
 
 
-
-
-
 As a research specialist focused on remote sensing applications in semi-arid rangelands, I'm constantly seeking tools that can enhance our ability to process and analyze large-scale geospatial data. The excitement of discovering new platforms that streamline complex workflows never gets old, especially when dealing with the massive datasets typical in remote sensing research.
 
 My journey with Fused began unexpectedly through the "Minds Behind Maps" podcast, where host Maxime Lenormand interviewed Sina Kashuk, Co-Founder and CEO of Fused (see [episode](https://www.mindsbehindmaps.com/episode/the-ex-uber-data-scientist-who-wants-to-simplify-data-science-with-serverless-computing-sina-kashuk)). The conversation sparked my curiosity, leading me to explore Fused's community [examples](https://github.com/fusedio/udfs/tree/main) and [documentation](/). After joining their [waitlist](https://docs.google.com/forms/d/e/1FAIpQLSf9X-Tg-hDRW2ngMtewP--ZLjZx3gcVfEcfg2NdY3B_v2nnUQ/viewform) and receiving access, I knew exactly how I wanted to test it: an interactive tool for exploring NEON's [Airborne Observation Platform](https://www.neonscience.org/data-collection/airborne-remote-sensing) (AOP) data.
diff --git a/blog/2024-12-05-claudio/index.mdx b/blog/2024-12-05-claudio/index.mdx
@@ -8,6 +8,9 @@ hide_table_of_contents: false
 keywords: [osmnx, urban, mobility, network]
 ---
 
+**TL;DR Claudio used Fused to create an app to model road mobility networks in Lima, Peru, using GeoPandas, and OSMnx.**
+
+On December 2023, I visited the [Institute for Metropolitan Planning](https://portal.imp.gob.pe/) (IMP) in Lima. The director had invited me to share some of my geospatial analysis projects from my master's studies and explore potential collaborations. Around that time, Lima's mayor had announced a bold infrastructure initiative: building 60 flyover bridges to ease traffic congestion in one of the most gridlocked cities in Latin America.
 
 
 import ReactPlayer from 'react-player'
@@ -31,7 +34,6 @@ import ReactPlayer from 'react-player'
 
 
 
-On December 2023, I visited the [Institute for Metropolitan Planning](https://portal.imp.gob.pe/) (IMP) in Lima. The director had invited me to share some of my geospatial analysis projects from my master's studies and explore potential collaborations. Around that time, Lima's mayor had announced a bold infrastructure initiative: building 60 flyover bridges to ease traffic congestion in one of the most gridlocked cities in Latin America.
 
 When I asked how the city was simulating the impact of new network designs on urban mobility, the answer was: "We are not simulating anything, our budget is constrained, and there is no political will to solve this problem." I couldn't think of anything else after this meeting. I started thinking about how I could create an easy-to-use tool to simulate urban mobility using open-source data, tools with no subscriptions or licenses, and without data privacy concerns.
 
diff --git a/blog/2024-12-06-naty/index.mdx b/blog/2024-12-06-naty/index.mdx
@@ -8,7 +8,7 @@ hide_table_of_contents: false
 keywords: [ibis]
 ---
 
-
+**TL;DR Naty shares a UDF to use Ibis with DuckDB's spatial extension to query and explore Overture Maps data.**
 
 Naty is a Senior Software Engineer and a contributor to Ibis, the portable Python dataframe library. One of her main contributions was enabling the DuckDB spatial extension for Ibis in 2023.
 
diff --git a/blog/2024-12-10-qiusheng/index.mdx b/blog/2024-12-10-qiusheng/index.mdx
@@ -8,11 +8,10 @@ hide_table_of_contents: false
 keywords: [qiusheng, leafmap, foursquare, overture]
 ---
 
-
+**TL;DR Dr. Qiusheng walks through how you can call Fused UDFs to load data into leafmap maps using Jupyter Notebooks.**
 
 import ReactPlayer from 'react-player'
 
-
 <ReactPlayer
     playsinline={true}
     className="video__player"
@@ -26,18 +25,10 @@ import ReactPlayer from 'react-player'
 
 <br/>
 
-
-
-
-
-
 Dr. Qiusheng Wu is an Associate Professor of Geography and Sustainability at the [University of Tennessee](https://faculty.utk.edu/Qiusheng.Wu) and a Founding Editorial Board Member at the [Cloud-Native Geospatial Forum (CNG)](https://cloudnativegeo.org/). As part of his commitment to making open-source geospatial analysis and visualization more accessible, he has developed several widely used open-source packages, including [geemap](https://geemap.org/), [leafmap](https://leafmap.org/), and [segment-geospatial](https://samgeo.gishub.org/).
 
 In [this Notebook](https://colab.research.google.com/drive/1JUupA0f5xJ_2QMqI6xrsEnLqIGXhB6le?usp=sharing) Qiusheng shows a few examples of how Cloud Native Geospatial datasets help you easily load data into a Jupyter Notebook environment using leafmap. His practical examples showcase how you can call the [Overture Maps UDF](https://www.fused.io/workbench/catalog/Overture_Maps_Example-64071fb8-2c96-4015-adb9-596c3bac6787) and [Foursquare Places UDF](https://www.fused.io/workbench/catalog/Foursquare_Open_Source_Places-5cd75ead-e319-4279-8efc-04276de145bc) to load data into a custom area of interest and render it in a leaflet map.
 
-
-
-
 <br></br>
 
 {/* truncate */}
@@ -49,7 +40,6 @@ In [this Notebook](https://colab.research.google.com/drive/1JUupA0f5xJ_2QMqI6xrs
 
 :::
 
-
 ## Calling Fused UDFs to load data
 
 You first use leafmap to create a bounding box over an area of interest (AOI) `user_aoi` and create a GeoDataFrame `gdf_aoi` with it. Then, you can [run](https://docs.fused.io/core-concepts/run-udfs/) the [Overture Maps UDF](https://www.fused.io/workbench/catalog/Overture_Maps_Example-64071fb8-2c96-4015-adb9-596c3bac6787), passing the AOI as a parameter to define the area to fetch data for.
@@ -75,8 +65,4 @@ gdf_aoi = gpd.GeoDataFrame([user_aoi['properties']], geometry=[shape(user_aoi['g
 gdf = fused.run("UDF_Overture_Maps_Example", bbox=aoi)
 ```
 
-
-
-
-
 <br></br>
diff --git a/blog/2024-12-11-jacob/index.mdx b/blog/2024-12-11-jacob/index.mdx
@@ -8,6 +8,7 @@ hide_table_of_contents: false
 keywords: [vida, climate, risk]
 ---
 
+**TL;DR Jacob at VIDA uses Fused to streamline processing and rendering of CMIP6 climate risk models, improving data sharing and sanity checks.**
 
 import ReactPlayer from 'react-player'
 
diff --git a/blog/2024-12-12-kristin/index.mdx b/blog/2024-12-12-kristin/index.mdx
@@ -9,6 +9,8 @@ keywords: [crop, yield, corn, prediction, model]
 ---
 
 
+**TL;DR Kristin shares a UDF to create training data for a corn yield prediction model using Zonal Statistics.**
+
 import ReactPlayer from 'react-player'
 
 
diff --git a/blog/2025-01-09-antonius/index.mdx b/blog/2025-01-09-antonius/index.mdx
@@ -8,6 +8,8 @@ hide_table_of_contents: false
 keywords: [workflow,caching,h3]
 ---
 
+**TL;DR GLS uses Fused to create internal tooling to optimize routing for parcel delivery operations.**
+
 In the parcel delivery business, geospatial analyses are crucial to answer questions about daily operations. Do delivery drivers visit the same regions each day, letting them know their areas intimately? Or is there a high volatility of the regions? And of course, how do we optimize the routes of multiple drivers servicing the same region?
 
 Those are the questions Antonius is working on at GLS Studio, an innovation lab by GLS ([General Logistics Systems](https://www.gls-us.com/)) which is an international parcel delivery service provider.
diff --git a/blog/2025-01-14-overture/index.mdx b/blog/2025-01-14-overture/index.mdx
@@ -9,6 +9,8 @@ hide_table_of_contents: false
 keywords: [overture, spatial, join]
 ---
 
+**TL;DR The Overture docs show how you can easily integrate any Overture data into your workflows using Fused.**
+
 Fused has been working with the team at The [Overture Maps Foundation](https://overturemaps.org/) to enable direct access to their data through Fused UDFs. We are excited to share that the [Overture docs](https://docs.overturemaps.org/getting-data/fused/) now show examples on how to see how to integrate any Overture data into your workflows using Fused.
 
 
diff --git a/blog/2025-01-20-amico/index.mdx b/blog/2025-01-20-amico/index.mdx
@@ -8,6 +8,9 @@ hide_table_of_contents: false
 keywords: [h3, places, buffer]
 ---
 
+
+**TL;DR Chris Amico shows how to combine Overture Maps data with fire perimeters to analyze wildfire impact on buildings and businesses.**
+
 As communities continue to rebuild and recover from the devastation caused by natural disasters such as wildfires, the question remains: How can we quantify what was lost, especially in the built environment? With the ability to analyze detailed building footprints and overlay fire boundaries, we can begin to answer this by providing a rough estimate of the damage and identifying which structures were impacted by the flames.
 
 In this blog post, Chris Amico shows how by leveraging data such as Overture Building footprints and fire progression maps, we can gain insight into the extent of fire risk. This enables news agencies to derive insights such as count of shops or homes exposed or even assess the capacity of highway routes for residents to evacuate before a prospect fire reaches them.
diff --git a/blog/2025-01-21-elizabeth/index.mdx b/blog/2025-01-21-elizabeth/index.mdx
@@ -8,6 +8,9 @@ hide_table_of_contents: false
 keywords: [h3, overture, hot-spot]
 ---
 
+
+**TL;DR** Elizabeth Rosenbloom creates hotspot maps to identify key areas where Arundo donax is likely to spread, streamlining analysis to improve invasive species mitigation.
+
 In 2020 while working in Silicon Valley for the county of Santa Clara Valley, I became obsessed with improving monitoring and prevention efforts surrounding Arundo donax. The search and mitigation process this invasive plant species, Arundo donax, was a Sisophisian struggle that had been subject to the same procedures year in and year out, with no progress on beating the spread. To improve the efficacy and efficiency in battling against this notorious weed, I decided to build a tool that would identify the key areas for mitigation - both for the frequency of propagation (occurrence) and for spread potential.
 
 
diff --git a/blog/2025-01-22-blackprint/index.mdx b/blog/2025-01-22-blackprint/index.mdx
@@ -8,6 +8,9 @@ hide_table_of_contents: false
 keywords: [site suitability, real estate, overture, app]
 ---
 
+
+**TL;DR BlackPrint streamlines and transforms fragmented real estate data into actionable insights across Latin America.**
+
 [BlackPrint Technologies](https://www.blackprint.ai/) began its journey as a satellite mapping service designed to help municipalities modernize their property registries. Recognizing a greater opportunity, we transitioned into the private sector to address a significant gap in the commercial real estate market: the need for accessible, actionable data. Today, our platform empowers professionals with precise acquisition intelligence, transforming how decisions are made across Mexico and, soon, all of Latin America.
 
 import ReactPlayer from 'react-player'
diff --git a/blog/2025-01-22-danieljahn/index.mdx b/blog/2025-01-22-danieljahn/index.mdx
@@ -9,6 +9,8 @@ hide_table_of_contents: false
 keywords: [zarr, integration, tiles, streamlit]
 ---
 
+**TL;DR Sylvera quickly builds and tests new app features by serving data to DeckGL applications using Fused HTTP endpoints.**
+
 
 At its core, Sylvera rates carbon projects. Our ratings are powered by several earth observation and geospatial analysis data products. From climate risk data, and deforestation indicators, to biomass-predicting ML models, a wealth of data goes into generating a single-letter rating.
 
@@ -54,7 +56,7 @@ import Image2 from '/blog/2025-01-22-danieljahn/app-screenshot.png';
 
 Ultimately, we chose the most agile and powerful stack: an interactive [React](https://react.dev/) + [deck.gl](http://deck.gl) application powered entirely by Fused.
 
-We created a React dashboard, where each element displays the result of a different Fused UDF. This required an entire DAG of UDFs.
+We created a React dashboard, where each element renders the output of Fused UDFs. This required an entire DAG of UDFs.
 
 The core element is the Data UDF, which fetches raw data for a given area of interest. The subsequent UDFs then process this data for the application.
 
diff --git a/blog/2025-01-23-kyle/index.mdx b/blog/2025-01-23-kyle/index.mdx
diff --git a/blog/2025-02-21-jennings/index.mdx b/blog/2025-02-21-jennings/index.mdx
