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Printed Maps & App
Stay found. Stay informead. Our premium printed topographic maps and matching app for a once in a lifetime adventure

OnLine Data Books
Free online data books for your favorite trail, distances, elevation, climate, way points, terrain & fauna

Interactive Maps
GPS aware interactive maps, your location, topo, hybrid, satellite, trail track, way points, road, weather/snow overlays

Active Fires & Smoke
Know before you go! Get the lastest active fire & smoke information for your favorite trail

Snow Conditions
Get the lastest snow conditions for your favorite trail. Quantity, coverage, SNODAS, MODIS, historical and multi-year comparisons

Trip Planners
Create an extensive hike plan easily configurable to your hiking style. Distances, days, resupply, access points, etc

Gear Builder
Create your own fully customizable gear list with weight, pricing and divisable by section.

Trail Animals
Exhaustive resource for species ranges along your favorite trail. Includes amphibians, birds, mammals and reptiles.

Complete Gear Lists
Hundreds of complete gear lists by those that walked the walk.

Elevations Profiles
The big picture. Single elevation profile of your favorite trail.

Journal Tools
Search for a journal, create a journal, add/edit an entry, configure your journal, EMail updates, integrated interactve trail map, PLB locations and more

Wall Maps
Print out your favorite trail to 6 feet high. Elevation chart and resupply locations.

Postholer Forum
Source for trail and site information or just talk about your favorite trail

About
Where it all begins.

Why GeoParquet Is Not A Cloud Native Format

(Geo)Parquet is an extremely useful column oriented data format. When working with local, massive data sets having many millions of features, the performance of this format is second to none.

"The whole idea of cloud native data is to transfer the minimal amount of data from the cloud to the client."

The whole idea of cloud native data is to transfer the minimal amount of data from the cloud to the client. Put another way, a subset of the original source is transferred, this is either truncated or a sampling of the original data set. You would never transfer millions of features (or pixels) over the internet without serious performance consquences.

Ideally, on the client you would be dealing with a few thousand features or less. In modern JavaScript, doing spatial analysis or other types of processing on that many features is often trivial.

"GeoParquet's columnar format provides no performance benefit in a cloud native setting."

GeoParquet's columnar format performance shines on millions of features, not thousands. GeoParquet's columnar format provides no performance benefit in a cloud native setting. Your development environment will require the non-trivial addition of packages like Apache Arrow. The reality is GeoParquet offers no advantage over an SOZip'ed cloud native .fgb file (FlatGeobuf). SOZip reading and FlatGeobuf read/write are both internal to GDAL, GeoParquet is not.

"GeoParquet requires you to download the entire data set to extract a spatial subset of that data."

GeoParquet has no file level Spatial Reference System (SRS). Geometry columns have their own SRS and may be different. Try to request a bounding box of parquet data of a given SRS. The bounding box SRS will have to be transformed to every column SRS. Now, try this with a million columns...over a network...in a timely manner.

GeoParquet requires you to download the entire data set to extract a subset of that data. This is not a cloud native format. It's disheartening to see GeoParquet being pushed as some extraordinary cloud native format. No cloud native data sources will benefit from Parquet. Let's not manipulate folks to flush resources down another 'Big Data' rabbit hole they don't need.

Note, the term cloud native refers to processing cloud data with a app/web client without intermediate backend servers/services.

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