2025-10-06 – Weekly GIS News : GIS Internship with housing

Last week in our GIS community, discussions were rich with practical advice and innovative approaches. Members shared insights on optimizing workflows, particularly focusing on heat equity mapping and harvest unit layouts. There was also a lively debate around career paths in GIS consulting versus agency roles. Additionally, the challenges of using remote sensing data in smoke-affected areas stirred an engaging exchange of solutions and experiences.


This Week’s Hot Topics

GIS Internship with Housing Provided
This thread has been buzzing with interest as members discuss a unique internship opportunity that includes housing. It’s a great chance for newcomers to get hands-on experience.
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Open workflows for heat equity mapping
There’s a thoughtful exchange happening on how to create open-source workflows for mapping heat equity. This is crucial for addressing urban heat challenges effectively.
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KDE settings for burglary hot spots
Members are delving into kernel density estimation settings to improve the accuracy of mapping burglary hot spots. It’s a technical conversation with practical implications for public safety.
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Better workflow for harvest unit layouts
This thread offers valuable tips on refining workflows for harvest unit design, which is crucial for efficiency in forestry operations.
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Consulting vs agency for EIA GIS roles
A comparison of career paths in environmental impact assessment roles is providing insights into the pros and cons of consulting versus agency work.
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Thin smoke keeps fooling my change maps
This discussion tackles the challenge of remote sensing data being misled by thin smoke, a common issue for those working in environmental monitoring.
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Drive-time polygons beat 3-mile rings
The conversation here is about the advantages of using drive-time polygons over traditional distance rings for better spatial analysis.
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Hiring planners with real GIS chops
This thread is essential for anyone involved in recruiting, discussing what to look for when hiring planners with strong GIS skills.
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Sentinel-2 cirrus mask tripping NDVI
Members are sharing strategies to deal with Sentinel-2 data issues, particularly how cirrus clouds can affect NDVI readings.
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FAQ/Guidelines
A helpful resource for both new and long-standing members to understand the forum’s rules and guidelines.
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Looking forward to another week of meaningful discussions. Your contributions make this community what it is.

1 Like

And “Sentinel-2 cirrus mask tripping NDVI” — we fixed it by ignoring QA60 cirrus, using s2cloudless at 0.35, then a 14-day median composite to ride out smoke spikes on heat equity maps. If you need 10 m for harvest unit layouts, keep B8/B4 but sanity-check against 20 m B8A NDVI; it’s a bit less twitchy under thin haze.

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@olivia84 > B8/B4 but sanity-check against 20 m B8A NDVI; it’s a bit less twitchy under — agreed; in heavy smoke I swap NDVI for EVI2 and drop days with MAIAC AOD >0.3 (https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MCD19A2) before a 14-day median. Small caveat: EVI2 can run a bit hot over irrigated ag, so clip to urban fabric if you’re doing heat equity.

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Quick example: for harvest unit layout we build a 10 m cost surface from slope, soils, and stream buffers, then run cost-distance to proposed landings — it reliably flags easier skid corridors and saves a day in the field… When smoke clobbers the imagery, I lean on Sentinel-1 VH backscatter to spot recent disturbance; not pretty, but it punches through haze. Caveat: resample everything to the coarsest grid or your costs get goofy; @scarlett_wil81, WhiteboxTools’ cost-distance has been solid for this (https://www.whiteboxgeo.com/manual/wbt_book/cost_tools.html).

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Smoke kept wrecking our remote sensing runs too, . What helped was switching to NASA HLS (S30/L30) in GEE with a 7‑day rolling median and dropping days that intersect NOAA HMS smoke polygons (Hazard Mapping System | OSPO); when gaps got bad, I backfilled trends with Sentinel‑1 VV/VH and a 30 m Lee filter. It’s not perfect — edges get crunchy near clouds — but for heat equity mapping it kept the signal stable; @olivia84 have you tried HLS + S1 fusion yet?

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