Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Statgraphics01:10

Statgraphics

356
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
356
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

394
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
394
Methods of Obtaining Topography01:25

Methods of Obtaining Topography

237
Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
237
The Distance Formula01:20

The Distance Formula

513
In geometry, measuring the direct distance between two points on a plane is essential in various practical and theoretical applications. Whether in navigation, engineering, or computer graphics, determining the shortest path between two locations involves using the distance formula. This formula is derived from the Pythagorean Theorem, which relates the lengths of the sides of a right triangle. On a coordinate plane, the horizontal and vertical distances between two points serve as the legs of...
513
Precipitation Gravimetry01:03

Precipitation Gravimetry

12.8K
Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
12.8K
Manipulation and Analysis01:21

Manipulation and Analysis

253
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
253

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d'Ivoire.

International journal of environmental research and public health·2022
Same author

Evaluating urban greening scenarios for urban heat mitigation: a spatially explicit approach.

Royal Society open science·2021
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Jan 2, 2026

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
09:44

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

10.6K

PyLandStats: An open-source Pythonic library to compute landscape metrics.

Martí Bosch1

  • 1Urban and Regional Planning Community (CEAT), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Plos One
|December 6, 2019
PubMed
Summary
This summary is machine-generated.

PyLandStats is a new open-source Python library for calculating landscape metrics. It integrates seamlessly into scientific workflows and offers flexible options for spatial pattern analysis.

More Related Videos

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
06:48

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

Published on: May 10, 2020

3.9K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.2K

Related Experiment Videos

Last Updated: Jan 2, 2026

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
09:44

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

10.6K
Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
06:48

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

Published on: May 10, 2020

3.9K
Automatic Identification of Dendritic Branches and their Orientation
06:08

Automatic Identification of Dendritic Branches and their Orientation

Published on: September 17, 2021

2.2K

Area of Science:

  • Landscape ecology
  • Geospatial analysis
  • Spatial pattern quantification

Background:

  • Quantifying landscape spatial patterns is crucial in landscape ecology.
  • Existing software often lacks integration with interactive environments like Jupyter notebooks or automated workflows.
  • There is a need for accessible tools within the scientific Python stack.

Purpose of the Study:

  • Introduce PyLandStats, an open-source Python library for computing landscape metrics.
  • Facilitate the integration of landscape pattern analysis into complex computational workflows.
  • Provide flexible methods for quantifying spatial and spatiotemporal landscape patterns.

Main Methods:

  • Developed as a Pythonic library leveraging existing geospatial data analysis tools.
  • Offers a set of methods for landscape pattern quantification, including spatiotemporal and zonal analysis.
  • Designed for seamless integration within the scientific Python ecosystem.

Main Results:

  • PyLandStats enables efficient computation of landscape metrics within Python.
  • The library supports analysis of land use/land cover change and zonal statistics.
  • Its modular, object-oriented structure ensures maintainability and extensibility.

Conclusions:

  • PyLandStats provides a powerful and flexible solution for landscape pattern analysis in Python.
  • The library enhances the usability of landscape metrics in scientific research and automated workflows.
  • Its open-source nature promotes community contribution and further development.