1,720,997 research outputs found
samapriya/gfw: Simple CLI for Global Fishing Watch Data
No full textThe Global Fishing Watch map is the first open-access online platform for visualization and analysis of vessel-based human activity at sea, including fishing activity, encounters between vessels, night light vessel detection, and vessel presence. This tool is designed to help interact programmatically with the Global Fishing Watch data and is not based on any official API so expect features to break once in a while.
Disclaimer: This is an unofficial tool. Is not licensed or endorsed by Global Fishing Watch. It is created and maintained by Samapriya Roy.
gfw -h
usage: gfw [-h] {auth,data-list,file-list,download} ...
Simple CLI for Global Fishing Watch Data
positional arguments:
{auth,data-list,file-list,download}
auth Authenticates and saves your username and password
data-list Generate data list with Dataset ID & timestamp
file-list File list for dataset
download Download datasets
optional arguments:
-h, --help show this help message and exit
Changelog
v0.0.4
added readme pages
updated tool description and readme
v0.0.3
added nested check for JSON objects from data list
auto updation of datasets.json file as new datasets become available
updated Readme
v0.0.2
added tabulate to print dataset id and last updated table
added offline JSON parser for 500 Internal Server Error from GFW
general improvements and cleanu
samapriya/appeears: Simple CLI for NASA AppEEARS API
No full textThe Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) offers a simple and efficient way to access and transform geospatial data from a variety of federal data archives. AppEEARS enables users to subset geospatial datasets using spatial, temporal, and band/layer parameters. Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons. Sample requests submitted to AppEEARS provide users not only with data values but also associated quality data values.
NASA appears API provides endpoints to automate and use this tool in a programmatic environment. This command line tool attempts at creating an implementation of the overall API design.
Disclaimer: Whole or part of the description is provided by the original owners of the product. This is an unofficial tool. Is not licensed or endorsed by NASA or any other orgs providing the NASA Appeears service. It is created and maintained by Samapriya Roy.
Readme Docs available online
Changelog
v0.0.3
general improvements and error logging
added layer index option for task submission
fixed authentication inpu
samapriya/cloud-utils: cloud-utils: Cloud utils for Planet UDM-2
No full textPlease note: This tool is in no way an official tool or Planet offering, but is a personal project created and maintained by Samapriya Roy
Cloud utils are tools to work with Planet's UDM-2 dataset. The Usable Data Mask v2 are an 8 bit 8 band image with the following bands. These tools are designed as modules that can be imported directly into any Google Earth Engine script and can then be used in a plug and play manner.
Band
Description
Pixel Value Range
Interpretation
Band 1
Clear map
[0, 1]
0: not clear, 1: clear
Band 2
Snow map
[0, 1]
0: no snow or ice, 1: snow or ice
Band 3
Shadow map
[0, 1]
0: no shadow, 1: shadow
Band 4
Light haze map
[0, 1]
0: no light haze, 1: light haze
Band 5
Heavy haze map
[0, 1]
0: no heavy haze, 1: heavy haze
Band 6
Cloud map
[0, 1]
0: no cloud, 1: cloud
Band 7
Confidence map
[0-100]
percentage value: per-pixel algorithmic confidence in classification
Band 8
Unusable pixels
--
Equivalent to the UDM asset: see Planet's Imagery Specification for complete details
UDM-2 classification stems from a supervised machine learning technique and is designed to seperate the the above classes. Things to note:
All classes are mutually exclusive meaning you can be either of the classes in Band-1 to Band -6
The clases (Band-1 to Band-6) are binary as mentioned in the band list.
The Confidence map value therefore refers to a single class and has a 1:1 correlation to the underlying imagery.
To read more about the UDM-2 Classification Methodology you can go here at our Developers Center.
Eventually this will allow you to apply cloud masking to PlanetScope Scenes and their related UDM-2 masks to create cloud free composites
samapriya/pyaqua: Simple CLI for Aqualink Org
No full textAqualink is a philanthropic engineering organization working on building ocean conservation technology. Read more about their inspiration, smart buoy, and web application. This tool is designed to help interact programmatically with the Aqualink.org map and is not based on any official API so expect features to break once in a while. This tool is designed for only only those sites associated with a spotter.
Disclaimer: This is an unofficial tool. Is not licensed or endorsed by Aqualink org. It is created and maintained by Samapriya Roy.
usage: pyaqua [-h] {site-list,site-info,site-live,site-daily,site-timeseries} ...
Simple CLI for Aqualink API
positional arguments:
{readme,site-list,site-alert,site-info,site-live,site-daily,site-timeseries,site-argo}
readme Go to the web based pyaqua readme page
site-list Print lists of Site Name and ID with spotters
site-alert Print site alerts for sites with spotters
site-info Print detailed information for a site
site-live Get most recent/live info from a site
site-daily Print daily data info for a site
site-timeseries Exports timeseries data for a site
site-argo Exports coincident argofloat data for a site
optional arguments:
-h, --help show this help message and exit
Changelog
v0.0.8
added site-argo tool for argofloat exports for sites
v0.0.7
added readme tool to CLI for browser redirect
v0.0.6
added site alert tool
v0.0.5
added status filter to site-list tool
added lat long for site-timeseries export
v0.0.4
Fixed tool descriptor for timeseries tool.
v0.0.3
Added site info tool for detailed information on site.
v0.0.2
added readme page to doc
samapriya/argofloats: Simple CLI for ArgoVis and Argofloats
No full textArgo is an international program that collects information from inside the ocean using a fleet of robotic instruments that drift with the ocean currents and move up and down between the surface and a mid-water level. Each instrument (float) spends almost all its life below the surface. The name Argo was chosen because the array of floats works in partnership with the Jason earth observing satellites that measure the shape of the ocean surface. (In Greek mythology Jason sailed on his ship the Argo in search of the golden fleece). To learn more about Argo, how it works, its data and technology, and its scientific and environmental impact, click here.
The argofloats tool builds on the argovis API and allows the user to perform basic operations like search for and export platform and profile data, parse metadata and so on and more functionality will be added to this tool in the future.
Disclaimer: This is an unofficial tool. It is created and maintained by Samapriya Roy.
As usual, to print help:
argofloats -h
usage: argofloats [-h] {readme,overview,pm,plm,global-search,platform-profiles,profile-export} ...
Simple CLI for ArgoVis & Argofloats
positional arguments:
{readme,overview,pm,plm,global-search,platform-profiles,profile-export}
readme Go the web based porder readme page
overview Get overview of platforms and profiles
pm Get Platform metadata
plm Get Platform Profile metadata
global-search Global search reports using platform, profile or BGC type
platform-profiles Export all profiles for a given platform
profile-export Export profile based on Platform Profile ID, Lat, Long or Geometry GeoJSON file
optional arguments:
-h, --help show this help message and exit
Changelog
v0.0.7
added BGC export for profiles apart from core export
added Global search capability for quick filter and export using keywords
v0.0.6
Improved error handling
Better readout if search yields nothing
General improvements & file skipping if exists
v0.0.5
Added readme tool to open in browser
v0.0.4
Fixed relative import of geopandas.
Added platform profiles export tool.
Minor general improvements.
v0.0.3
Added readme to the overall tool.
Improved profile metadata parsing
Added version check for all future pypi versions
v0.0.2
Added readme and created new branch
open-oceans/pycoral: Simple CLI for Allen Coral Atlas
No full text<p>The Allen Coral Atlas was conceived and funded by the late Paul Allen's Vulcan Inc. and is managed by the Arizona State University Center for Global Discovery and Conservation Science. Along with partners from Planet, the University of Queensland, and the National Geographic Society, the Atlas utilizes high-resolution satellite imagery and advanced analytics to map and monitor the world's coral reefs in unprecedented detail. These products support coral reef science, management, conservation, and policy across the planet. This tool is designed to help interact programmatically with the Allen Coral Atlas and is not based on any official API so expect features to break once in a while.</p>
<p>Disclaimer: This is an unofficial tool. Is not licensed or endorsed by Allen Coral Atlas. It is created and maintained by Samapriya Roy.</p>
<pre><code>usage: pycoral [-h]
{readme,auth,aoi-find,aoi-create,aoi-stat,aoi-delete,aoi-download}
...
Simple CLI for Allen Coral Atlas
positional arguments:
{readme,auth,aoi-find,aoi-create,aoi-stat,aoi-delete,aoi-download}
readme Go to the web based pycoral readme page
auth Saves your username and password
aoi-find Find AOI name and ID or list all
aoi-create Use a GeoJSON geometry file to create My Area AOI
aoi-stat Print summary statistics for AOI using geoemtry file,
name or ID
aoi-delete Delete AOI from My Areas list
aoi-download Download files using name or ID
optional arguments:
-h, --help show this help message and exit
</code></pre>
<h2>Changelog</h2>
<h4>v0.2.0</h4>
<ul>
<li>Improved area and file format parsing</li>
<li>Better logging support and error reporting</li>
<li>Added support for GeoJSON, shapefile and CSV imports</li>
<li>Added new aoi statistics support tool for stats export</li>
<li>Major overall improvements and updates</li>
</ul>
<h4>v0.1.0</h4>
<ul>
<li>Better site parsing</li>
<li>Better error handling for Download</li>
<li>Increase wait time for download to 2 minutes</li>
</ul>
<h4>v0.0.9</h4>
<ul>
<li>Better error handling and now users user agent.</li>
<li>Download tool for system polygon now creates a user copy to allow for all file types.</li>
</ul>
samapriya/pycoral: Simple CLI for Allen Coral Atlas
No full textThe Allen Coral Atlas was conceived and funded by the late Paul Allen's Vulcan Inc. and is managed by the Arizona State University Center for Global Discovery and Conservation Science. Along with partners from Planet, the University of Queensland, and the National Geographic Society, the Atlas utilizes high-resolution satellite imagery and advanced analytics to map and monitor the world's coral reefs in unprecedented detail. These products support coral reef science, management, conservation, and policy across the planet. This tool is designed to help interact programmatically with the Allen Coral Atlas and is not based on any official API so expect features to break once in a while.
Disclaimer: This is an unofficial tool. Is not licensed or endorsed by Allen Coral Atlas. It is created and maintained by Samapriya Roy.
usage: pycoral [-h]
{readme,auth,aoi-find,aoi-create,aoi-stat,aoi-delete,aoi-download}
...
Simple CLI for Allen Coral Atlas
positional arguments:
{readme,auth,aoi-find,aoi-create,aoi-stat,aoi-delete,aoi-download}
readme Go to the web based pycoral readme page
auth Saves your username and password
aoi-find Find AOI name and ID or list all
aoi-create Use a GeoJSON geometry file to create My Area AOI
aoi-stat Print summary statistics for AOI using geoemtry file,
name or ID
aoi-delete Delete AOI from My Areas list
aoi-download Download files using name or ID
optional arguments:
-h, --help show this help message and exit
Changelog
v0.0.7
Uses requests head to estimate zip completion for download.
Added option to download data in specific format kml,geojson,shp or gpkg.
Improved notification for download tool
v0.0.6
Added auto version check to the tool.
Added a web based readme site for the tool for ease of use.
v0.0.5
Captures products available for download for parsing product type.
For now chooses default product type only.
Product download is more graceful since it checks product UUID and type before download per AOI.
v0.0.4
Added aoi-delete capability along with create using GeoJSON and unique name check.
Added local timestamp based unique name generator to AOI stats tool and checks to see if mapped area.
Stability test across python3.6 to 3.9 and for all OS types built into CI
Updated docs and code cleanup
open-oceans/pyaqua: Simple CLI for Aqualink Org
No full text<p>Aqualink.org is a philanthropic engineering organization working on building ocean conservation technology. Read more about their <a href="https://aqualink.org/about">inspiration, smart buoy, and web application</a>. This tool is designed to help interact programmatically with the Aqualink.org map and is not based on any official API so expect features to break once in a while. This tool is designed for only those sites associated with a spotter or hobo sensor.</p>
<p>Disclaimer: This is an unofficial tool. Is not licensed or endorsed by Aqualink org. It is created and maintained by Samapriya Roy.</p>
<pre><code>usage: pyaqua [-h] {site-list,site-info,site-live,site-daily,site-timeseries} ...
Simple CLI for Aqualink API
positional arguments:
{readme,site-list,site-alert,site-info,site-live,site-daily,site-timeseries,site-argo}
readme Go to the web based pyaqua readme page
site-list Print lists of Site Name and ID with spotters
site-alert Print site alerts for sites with spotters
site-info Print detailed information for a site
site-live Get most recent/live info from a site
site-daily Print daily data info for a site
site-timeseries Exports timeseries data for a site
optional arguments:
-h, --help show this help message and exit
</code></pre>
<h2>Changelog</h2>
<h4>v0.2.0</h4>
<ul>
<li>Fixed major issues with data parsing and fetching custom timeseries exports</li>
<li>Better metadata parsing and handling of time series fields</li>
<li>Added support for cleaner logging</li>
<li>Fixed alert tooling issues and removed argofloats export tool</li>
</ul>
<h4>v0.1.0</h4>
<ul>
<li>Fixed issue with Boolean value for payload</li>
<li>Fixed metadata parsing and improved logic for time series export</li>
<li>Both time series and daily data now support export</li>
<li>Both time series and daily data now support custom date ranges</li>
<li></li>
</ul>
<h4>v0.0.9</h4>
<ul>
<li>now includes support for hobo sensors</li>
<li>added site list filter for device type breakdown</li>
<li>modified site alert tool to pull from all sites and by device type</li>
<li>general improvements</li>
</ul>
<h4>v0.0.8</h4>
<ul>
<li>added site-argo tool for argofloat exports for sites</li>
</ul>
<h4>v0.0.7</h4>
<ul>
<li>added readme tool to CLI for browser redirect</li>
</ul>
<h4>v0.0.6</h4>
<ul>
<li>added site alert tool</li>
</ul>
<h4>v0.0.5</h4>
<ul>
<li>added status filter to site-list tool</li>
<li>added lat long for site-timeseries export</li>
</ul>
<h4>v0.0.4</h4>
<ul>
<li>Fixed tool descriptor for timeseries tool.</li>
</ul>
<h4>v0.0.3</h4>
<ul>
<li>Added site info tool for detailed information on site.</li>
</ul>
<h4>v0.0.2</h4>
<ul>
<li>added readme page to docs</li>
</ul>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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