iNaturalist observations along hiking trails

Overview

iNaturalist observations along hiking trails

This tool reads the route of a hike and generates a table of iNaturalist observations along the trails. It also shows the observations and the route of the hike on a map. Moreover, it saves waypoints of the iNaturalist observations for offline navigation with a GPS device or smartphone.

Usage

This is a command-line tool. It is called with a .gpx file that describes the route. This .gpx file can be either after a hike downloaded from a gps device or smartphone or created before a hike by a mapping tool or website. The gpx files in the examples directory have been created with the free website caltopo.com.

Here is an example. This is the command for Linux and macOS

./inat_trails.py examples/Rancho_Canada_del_Oro.gpx

On Windows the command is:

python.exe .\inat_trails.py examples\Rancho_Canada_del_Oro.gpx

The output looks like this:

Reading 'examples/Rancho_Canada_del_Oro.gpx'...
Loaded 13 named roads and trails: Bald Peaks Trail, Canada Del Oro Cut-Off Trail, Canada Del Oro Trail, Casa Loma Road,
    Catamount Trail, Chisnantuk Peak Trail, Little Llagas Creek Trail, Llagas Creek Loop Trail, Longwall Canyon Trail,
    Mayfair Ranch Trail, Needlegrass Trail, Serpentine Loop Trail.
Loaded 2,708 iNaturalist observations of quality-grade 'research' within bounding box.
Excluded 1,694 observations not along route and 13 with low accuracy.
Loaded 829 taxa.
Waypoints written to './Rancho_Canada_del_Oro_Open_Space_Preserve_all_research_waypoints.gpx'.
Table written to './Rancho_Canada_del_Oro_Open_Space_Preserve_all_research_observations.html'.
Map written to './Rancho_Canada_del_Oro_Open_Space_Preserve_all_research_mapped_observations.html'.

This tools finds named trails along this route. It loads iNaturalist observations from the area of the hike and discards those that are not along the trails. It writes three output files, a waypoints file, a table of observations, and an interactive map. Both the table and the map will pop up in a browser.

The waypoint file can be loaded into the free offline navigation app OsmAnd. This will allow this offline navigation app to display the iNaturalist observations along the hiking trails.

The table of observations lists all the organisms that have been observed along the trails along with the trail names they are on. The table for the mammals seen in this park looks like this:

Scientific Name Common Name Observations
Canidae Canids
Canis latrans Coyote Mayfair Ranch Trail: 38860133, 38860889
Urocyon cinereoargenteus Gray Fox Mayfair Ranch Trail: 39391329
Cervidae Deer
Odocoileus hemionus ssp. columbianus Columbian Black-Tailed Deer Casa Loma Road: 80058758; Little Llagas Creek Trail: 68891936; Mayfair Ranch Trail: 19113219, 21319391, 44158629
Cricetidae Hamsters, Voles, Lemmings, and Allies
Neotoma fuscipes Dusky-Footed Woodrat Mayfair Ranch Trail: 52963985
Felidae Felids
Lynx rufus Bobcat Mayfair Ranch Trail: 15630740, 15689757, 38861135
Geomyidae Pocket Gophers
Thomomys bottae Botta's Pocket Gopher Mayfair Ranch Trail: 38869384, 38875049
Leporidae Hares and Rabbits
Sylvilagus bachmani Brush Rabbit Mayfair Ranch Trail: 73152597, 74462983
Sciuridae Squirrels
Neotamias merriami Merriam's Chipmunk Longwall Canyon Trail: 42605223; Mayfair Ranch Trail: 132863, 46538314
Otospermophilus beecheyi California Ground Squirrel Casa Loma Road: 47200360; Mayfair Ranch Trail: 2328803, 15629491, 53667091
Sciurus griseus Western Gray Squirrel Mayfair Ranch Trail: 73152599

The numbers are the observation ids; a click opens them on the iNaturalist website.

The interactive map shows the route and the iNaturalist observations along the hike. Like the iNaturalist website, the markers on the interactive map have different colors for different iconic taxa, e.g. markers for plants are green. Hoovering the mouse over a marker shows the identification, a click on a marker shows a thumbnail picture, the identification, the observer, the date and a special status like invasive or introduced. A further click on that thumbnail opens the observation in the iNaturalist website in another browser window.

Command-line options

This script is a command-line tool. It is called with options and file names as arguments. These options are supported:

usage: inat_trails.py [-h] [--quality_grade QUALITY_GRADE] [--iconic_taxon ICONIC_TAXON] gpx_file [gpx_file ...]

positional arguments:
  gpx_file              Import GPS track from .gpx file.

optional arguments:
  -h, --help            show this help message and exit
  --quality_grade QUALITY_GRADE
                        Observation quality-grade, values: all, casual, needs_id, research; default research.
  --iconic_taxon ICONIC_TAXON
                        Iconic taxon, values: all, Actinopterygii, Amphibia, Animalia, Arachnida, Aves, Chromista,
                        Fungi, Insecta, Mammalia, Mollusca, Plantae, Protozoa, Reptilia; default all.

Option --quality_grade spcifies the desired quality-grade of the observations to show. By default, only research-grade observations are shown. Alternatively, all quality grades, or only casual and needs_id can be requested.

Option --iconic_taxon allows to restrict the observations to an iconic taxon. This can be used to display observations of e.g. only birds or only plants.

Dependencies

A handful of dependencies need to be installed in order for inat_trails.py to run. Besides Python 3.7 or later, a few packages are needed. On Ubuntu or other Debian-based Linux distributions the dependencies can be installed with:

sudo apt install --yes python3-pip python3-aiohttp python3-fiona python3-shapely
pip3 install folium

On other operating systems, Python 3.7 or later and pip need to be installed first and then the dependencies can be installed with:

pip install aiohttp folium shapely
pip install fiona

Note that pip fails to install fiona on Windows. This blogpost has a workaround.

When appropriate pip3 should be called instead of pip to avoid accidentally installing packages for Python 2.

Simple CLI for Google Earth Engine Uploads

geeup: Simple CLI for Earth Engine Uploads with Selenium Support This tool came of the simple need to handle batch uploads of both image assets to col

Samapriya Roy 79 Nov 26, 2022
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

A ready-to-use curated list of Spectral Indices for Remote Sensing applications. GitHub: https://github.com/davemlz/awesome-ee-spectral-indices Docume

David Montero Loaiza 488 Jan 03, 2023
Python bindings to libpostal for fast international address parsing/normalization

pypostal These are the official Python bindings to https://github.com/openvenues/libpostal, a fast statistical parser/normalizer for street addresses

openvenues 651 Dec 16, 2022
Script that allows to download data with satellite's orbit height and create CSV with their change in time.

Satellite orbit height ◾ Requirements Python = 3.8 Packages listen in reuirements.txt (run pip install -r requirements.txt) Account on Space Track ◾

Alicja Musiał 2 Jan 17, 2022
Implemented a Google Maps prototype that provides the shortest route in terms of distance

Implemented a Google Maps prototype that provides the shortest route in terms of distance, the fastest route, the route with the fewest turns, and a scenic route that avoids roads when provided a sou

1 Dec 26, 2021
Build, deploy and extract satellite public constellations with one command line.

SatExtractor Build, deploy and extract satellite public constellations with one command line. Table of Contents About The Project Getting Started Stru

Frontier Development Lab 70 Nov 18, 2022
Earthengine-py-notebooks - A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping

earthengine-py-notebooks A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping Contact: Qiushen

Qiusheng Wu 1.1k Dec 29, 2022
Water Detect Algorithm

WaterDetect Synopsis WaterDetect is an end-to-end algorithm to generate open water cover mask, specially conceived for L2A Sentinel 2 imagery from MAJ

142 Dec 30, 2022
Solving the Traveling Salesman Problem using Self-Organizing Maps

Solving the Traveling Salesman Problem using Self-Organizing Maps This repository contains an implementation of a Self Organizing Map that can be used

Diego Vicente 3.1k Dec 31, 2022
Google Maps keeps old satellite imagery around for a while – this tool collects what's available for a user-specified region in the form of a GIF.

google-maps-at-88-mph The folks maintaining Google Maps regularly update the satellite imagery it serves its users, but outdated versions of the image

Noah Doersing 111 Sep 27, 2022
Tools for the extraction of OpenStreetMap street network data

OSMnet Tools for the extraction of OpenStreetMap (OSM) street network data. Intended to be used in tandem with Pandana and UrbanAccess libraries to ex

Urban Data Science Toolkit 47 Sep 21, 2022
Deal with Bing Maps Tiles and Pixels / WGS 84 coordinates conversions, and generate grid Shapefiles

PyBingTiles This is a small toolkit in order to deal with Bing Tiles, used i.e. by Facebook for their Data for Good datasets. Install Clone this repos

Shoichi 1 Dec 08, 2021
A NASA MEaSUREs project to provide automated, low latency, global glacier flow and elevation change datasets

Notebooks A NASA MEaSUREs project to provide automated, low latency, global glacier flow and elevation change datasets This repository provides tools

NASA Jet Propulsion Laboratory 27 Oct 25, 2022
A compilation of several single-beam bathymetry surveys of the Caribbean

Caribbean - Single-beam bathymetry This dataset is a compilation of several single-beam bathymetry surveys of the Caribbean ocean displaying a wide ra

Fatiando a Terra Datasets 0 Jan 20, 2022
This program analizes films database with adresses, and creates a folium map with closest films to the coordinates

Films-map-project UCU CS lab 1.2, 1st year This program analizes films database with adresses, and creates a folium map with closest films to the coor

Artem Moskovets 1 Feb 09, 2022
Bacon - Band-limited Coordinate Networks for Multiscale Scene Representation

BACON: Band-limited Coordinate Networks for Multiscale Scene Representation Project Page | Video | Paper Official PyTorch implementation of BACON. BAC

Stanford Computational Imaging Lab 144 Dec 29, 2022
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.

Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta

Chris Beaven 1.2k Jan 03, 2023
A ninja python package that unifies the Google Earth Engine ecosystem.

A Python package that unifies the Google Earth Engine ecosystem. EarthEngine.jl | rgee | rgee+ | eemont GitHub: https://github.com/r-earthengine/ee_ex

47 Dec 27, 2022
geemap - A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets.

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and folium

Qiusheng Wu 2.4k Dec 30, 2022
PySAL: Python Spatial Analysis Library Meta-Package

Python Spatial Analysis Library PySAL, the Python spatial analysis library, is an open source cross-platform library for geospatial data science with

Python Spatial Analysis Library 1.1k Dec 18, 2022