Questions tagged [geospatial]
pertaining to the geographic location and characteristics of natural or constructed features and boundaries on, above, or below the earth's surface; esp. referring to data that is geographic and spatial in nature.
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How to filter rows using custom function in pyarrow
I've a parquet dataset that contains latitude and longitude values as separate columns. And I want to filter those rows that are inside a polygon, I'm able to do this in pandas dataframe but unable to ...
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How to forecast a timeseries with geolocation data?
I have created a dataset with my geolocations from the last three months. The data set contains longitude, latitude, and timestamp, with a frequency of every 5 minutes. Based on this data, I want to ...
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Classification Algorithms for Geospatial Vector Data
I am new to the world of Geospatial Analysis.
As such, I am interested in Machine Learning / Deep Learning techniques for classifying geospatial vector data specifically (as opposed to raster data). I'...
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Spatial Join Pandas Dataframes of Bounding Boxes (cross match)
Problem Statement
Imagine there are two almost identical images with annotations (bounding boxes for certain objects), where one is so-called golden image (template) containing all must-have objects (...
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How to best train a CNN with longitude/latitude output
Problem
I am new to CNNs and I'm starting off with a geolocation problem where the input is an image and the output should be a longitude value and a latitude value.
I am unsure of the best way to ...
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How to denoise overrepresented lines in sample of 2D (geospatial) data?
I have some geospatial data in lat/lon form accurate to 6th decimal place.
As shown in the picture below, there are some over-represented lines of points at specific latitudes which appear in the ...
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Group people driving together based on GPS data
I need to group together people driving together based on GPS data. Data are collected by mobile phones. From each user we receive them in batches every 10 seconds. Each batch have list of GPS data (...
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Hex-binning Geospatial Data
Okay, I feel like this maybe a very easy to answer for many of you. If you feel tempted to downvote this question, please know I tried earnestly for a dozen hours to find what I think should have been ...
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What is purpose of diffusion matrix? What is its role in graph clustering? How do it serve its purpose by equation?
As titled, I am not quite sure what is purpose of Diffusion Matrix, which is support to clustering graph.
From this article (https://arxiv.org/pdf/2006.05582v1.pdf) I am might able to compute the ...
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Filter relevant geojson data based on a selected datapoint
I'll outline the situation and challenge I have a bit more clearly. I have multiple different datasets:
A set of locations where products are sold (name, long, lat)
A geojson dataset with geometry (...
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Clustering latitude, longitude along with numeric and categorical data
I am working on clustering the customer base of a business-to-business company.
I have data on customers that consists of both numerical (e.g. # of purchases made, avg. spend per purchase) and ...
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How to calculate relative humidity from satellite data
I am trying to spatially calculate wet bulb temperature in a given city. I have temperature data at a decent resolution from LANDSAT-8. Where can I get the relative humidity index I need, even if it's ...
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Interpolate a point in time for two given geolocations and their times in python
Let's say I have two geolocations at given times. How can I interpolate these two geolocation and find any location for a given time time3 in python?
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How to create an A* Algorithm on geospatial data using custom heuristics
So my ultimate objective is to create an algorithm that can calculate the SAFEST route between two points on a map. I have created a dataset of unique lat,lng values and their "crime score" ...
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How to classify a "Trip" from multiple GPS pings of each Unique ID?
I have a huge file of lat/long & timestamp data from vehicles and I need to identify "Trips" from these multiple pings of Each vehicle ID. Trips have a "Start" & "end&...
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Sampling from earths landmass
Given a sphere which resembles earth, I want to sample points where land would be. I am struggling to find a dataset to sample from, and even to find a dataset which I could use to generate a set of ...
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How to use LAT/LNG as predictor variables
I'm working on geographic data where I need to predict the average income per geo key/zip code. The data I have consisted of more than 30 million unique geo keys in Zip+4 format. As per my ...
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How to cluster time series of ordered data?
There are a few hundred time series of a large set of different locations (irregularly distributed) with the following properties:
ordered factor (5 levels)
between 5 and 25 observations per series
...
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How to divide earth into polygons based on a collection of labeled coordinates?
I have around one million labeled coordinates(latitude, longitude) all around the world, with around 10,000 unique labels(location_id).
Each point corresponds to exactly one class(location_id). Each ...
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How to deal with address (like zip-code) for training a model?
To me it doesn't make sense to normalize it even if it is a numerical variable like Zip Code. An address should be interpreted as categorical features like "neighborhood"... ?
Suppose I have ...
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Machine learning cost/benefit for including priors in input vector
Is there a trade-off in accuracy/generalisation/performance when providing priors to a general machine learning algorithm vs training the machine learning algorithm with enough data so that it could ...
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Can pre-trained transformers (I.e., BERT) handle numerical/spatial data
I’m curious to know if pre-trained transformers could handle search queries that include numerical data or make references to spatial relationships.
Take an example dataset of a list of restaurants, ...
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use cases of geocoding maps
Tableau has interactive maps that can be used for custom geocoding. I know companies often divide regions for sales and marketing purposes but could anyone think of any specific use cases or examples ...
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How to use Lat/Lon in machine learning prediction?
I am research meteorologist working with hurricane model forecasts of track (millions of lat/lon pairs) and their verified lat/lon pairs (essentially where the hurricane actually went).
With the ...
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Geospatial clustering plot with zoom in Python?
I need to construct an interactive clustering plot. Ideally as the user zooms in the clusters would split-up into smaller clusters at certain zoom levels.
I am planning to have several discrete levels ...
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Save CSVs as hyper file
I have three separate CSV files (Points.csv, PointsSynonym.csv, and LocalDataPoints.csv). I made these files after extracting data from shape files and .gpkg files.
I would like to save them all a ...
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Metrics for spatial datasets
I'm working on a dataset of computer game replays. Each replay file describes the game of two players as a timeseries of game commands, where each command has a type and coordinates, like so: ...
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What is a good way to handle nominal spatial data with a changing number of categories to use in prediction model?
For a project I'm going to be working with spatial data with a nominal attribute (land use). Every year the number of categories for this attribute changes because categories split or merge. I do have ...
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Finding Correlations in two Datasets
I have an assignment where I am trying to find correlations between Lightning Strikes and Telecommunication damage. The two datasets consist of many columns (especially the human-recorded ...
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Destination prediction with Naive Bayes and sparse output matrix
Given a dataset of historical cab rides, I'm trying to predict the final zip code destination of a ride based on the following features:
origin zip code (e.g. 10006 Wall Street, Manhattan)
pickup ...
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How to handle multi-channel 2-D geo-spatial grid like data samples in machine learning with number of features associated with each grid?
I am looking into a problem wherein the whole geographic area is divided into number of bins/pixels so we get nxn matrix covering whole region. Now each bin/pixel has number of parameters/features ...
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Spatially constrained geospatial similarity
What's the current methodology for clustering geospatial data by features?
Example: I have some demographic dataset. Let's say this contains average home price and population density.
So, an example ...
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Data Engineering Stack - collect, transform and visualize geospatial data
I'm making a side project, where I collect geospatial data by web scrapping and from OSM API. I've started with simple Java application, however, I would like to make it as a data flow, purely for ...
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Derivative of multi-output Gaussian Process
I am working on a project where I estimate transition and measurements models for a kalman filter using Gaussian Processes.
In order to linearize the models I require the Jacobian of the estimated ...
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Geo Add-on Choropleth Widget not found
I am trying to create a Choropleth map using the Chorolpeth widget from the Geo Add-on in Orange. However, this widget is not appearing? Any ideas?
My current version: Orange version 3.24.1 for ...
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How to measure the distance (in generalized sense) between geographical regions? [closed]
I need to construct a distance matrix for a few U.S. counties that are adjacent to one or another, and choosing the definition of distance is very tricky. The shortest path (i.e the minimum number of ...
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"Smearing" probabilities or how to handle imprecise locations for canonically classification-type problems
I am trying to predict failures at different nodes on a line. Each node has different weather features and hardware/configuration features. For a little under half of the historical failures I have, I ...
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Train building classifier for imagerial data
I am using the https://www.arcgis.com/ api for accessing imagery of aerial data.
I would like to train a model that can caputure on the imagery if the provided ...
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How to plot a world map with cities in the right locations?
The data source is a CSV with cities in various countries in the world, each city has some numeric data associated with it. df.columns looks like:
...
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How to best use geographical information as a factor?
I am trying to predict crime rates and I have naively used lat and long as two separate factors (which seem to work well!). Are there any best practices for location as a factor?
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Can a machine learning model be trained on Call Detail Record(CDR) Data to predict user's daily locations?
I have a CDR data for two months and my goal is to extract daily or frequent locations(cell towers) of the user along with the departure and arrival time on those locations. The spatial resolution of ...
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Is there an alternative to Google Maps to find GPS coordinates of a place in Germany?
For probably any place on Earth, you can search it in Google Maps, make right-click, pick the option "What's here" and you get GPS coordinates.
If I don't want to use Google Maps API, is there an ...
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Unsupervised Learning::Satellite Images::Single Bands
Has anyone has success with building models using KMeans for classification? I have images that only have one band and it continues to fail. My guess is that the issue is with both size of the image ...
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fast processing: changing the column value in a geospatial environment
I have a table whose header looks like this: complaint_type, borough, street_name, incident_zip, latitude, longitude
1) I want to check if the "incident_zip" column of each row is in a specific list ...
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Changing the value of a column based on the condition on another column
I have a table whose header looks like this:
complaint_type borough street_name incident_zip latitude longitude
I want to check if the "incident_zip" column of each row is in a specific ...
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How do I get the latitude and longitude information contained csv file? [closed]
I have already done a project on "Segmenting and Clustering Neighborhoods in Toronto" using the latitude and longitude information contained CSV file link attached with the question[http://cocl.us/...
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High Level Discussion: Generate synthetic sensor data using data from surrounding sensors
Let's assume I have readings coming from sensors. For every sensor, I have the following information:
all the data it reads
its location
Now, given an arbitrary sensor at an arbitrary location ...
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GPS Data Preprocessing Recommandations?
GPS Data Preprocessing
I got gps traces of busses which traveled from one place (bus station) to another. This file contains relevant(eg:- Data recorded between the starting bus station and ends ...
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Create Nodes/Edges From CSV (latitude and longitude) for Graphs
The Ultimate Goal: I want to find the shortest and coolest (in terms of temperature) path between two points (for a given pair of latitudes and longitudes on the map)!
I am aware of algorithms like ...
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