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

Precipitation Gravimetry01:03

Precipitation Gravimetry

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...

You might also read

Related Articles

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

Sort by
Same author

Deep Learning Meets InSAR for Infrastructure Monitoring: A Systematic Review of Models, Applications, and Challenges.

Sensors (Basel, Switzerland)·2025
Same author

Spatial-Temporal Dynamics of Vegetation Indices in Response to Drought Across Two Traditional Olive Orchard Regions in the Iberian Peninsula.

Sensors (Basel, Switzerland)·2025
Same author

A Systematic Review on the Advancements in Remote Sensing and Proximity Tools for Grapevine Disease Detection.

Sensors (Basel, Switzerland)·2025
Same author

Comparative Analysis of TLS and UAV Sensors for Estimation of Grapevine Geometric Parameters.

Sensors (Basel, Switzerland)·2024
Same author

Plastic debris in lakes and reservoirs.

Nature·2023
Same author

Social Vulnerability of Brazilian Metropolitan Schools and Teachers' Absence from Work Due to Vocal and Psychological Symptoms: A Multilevel Analysis.

International journal of environmental research and public health·2023

Related Experiment Video

Updated: Jul 3, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

Spatio-Temporal Water Hyacinth Monitoring in the Lower Mondego (Portugal) Using Remote Sensing Data.

Luís Pádua1,2, Lia Duarte3,4, Ana M Antão-Geraldes5,6

  • 1Centre for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal.

Plants (Basel, Switzerland)
|December 23, 2022
PubMed
Summary

Monitoring invasive water hyacinth using Sentinel-2 satellite data proved effective. The normalized difference vegetation index (NDVI) approach accurately estimated coverage, showing a decrease in 2021 potentially due to mitigation efforts.

Keywords:
geographical information systemsinvasive speciesnormalized difference vegetation indexremote sensingsatellite

More Related Videos

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

11.3K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.9K

Related Experiment Videos

Last Updated: Jul 3, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K
Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
12:50

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

11.3K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.9K

Area of Science:

  • Ecology and Environmental Science
  • Remote Sensing and Geospatial Analysis
  • Invasive Species Management

Background:

  • Invasive plant species monitoring is vital for ecosystem health but is labor-intensive and logistically challenging.
  • Remotely sensed data offers a promising solution for surveying large and inaccessible areas, particularly for conspicuous species.
  • Water hyacinth (Eichhornia crassipes) is a significant invasive aquatic plant impacting ecosystems globally.

Purpose of the Study:

  • To monitor the spatial distribution and area occupied by water hyacinth in the Lower Mondego region, Portugal.
  • To assess the effectiveness of Sentinel-2 satellite data and the normalized difference vegetation index (NDVI) for invasive species tracking.
  • To develop a semi-automatic geographic information system (GIS) application for ongoing monitoring of invasive plants.

Main Methods:

  • Utilized Sentinel-2 satellite imagery from 2018 to 2021 to analyze water hyacinth presence in three water channels.
  • Applied the normalized difference vegetation index (NDVI) to estimate the surface area occupied by the invasive species.
  • Developed a semi-automatic GIS application to implement the methodology for researchers and ecologists.

Main Results:

  • The study identified an exponential increase in water hyacinth coverage from May to October annually.
  • A significant deviation from this trend was observed in 2021, suggesting the potential impact of mitigation measures.
  • The NDVI-based methodology achieved over 97% accuracy, outperforming machine learning approaches (93%) for multispectral UAV data.

Conclusions:

  • Sentinel-2 data combined with NDVI is a robust and accurate method for monitoring water hyacinth infestations.
  • The developed GIS tool provides a practical and transferable approach for invasive plant species management.
  • The observed reduction in 2021 highlights the importance of and potential success of targeted mitigation strategies.