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

Ecological Disturbance02:26

Ecological Disturbance

20.3K
An ecological disturbance is a temporary disruption in the environment resulting from abiotic, biotic, or anthropogenic factors, causing a pronounced change in an ecosystem. The impact of an ecological disturbance, which can depend on its intensity, frequency, and spatial distribution, plays a significant role in shaping the species diversity within the ecosystem.
20.3K
Global Climate Change01:50

Global Climate Change

28.2K
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
28.2K
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

326
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
326
Manipulation and Analysis01:21

Manipulation and Analysis

205
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...
205
Levels of Use of a GIS01:29

Levels of Use of a GIS

235
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
235
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

524
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
524

You might also read

Related Articles

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

Sort by
Same author

Correction: Costache et al. Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors. <i>Sensors</i> 2021, <i>21</i>, 280.

Sensors (Basel, Switzerland)·2026
Same author

CloudSEN12, a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2.

Scientific data·2022
Same author

QADI as a New Method and Alternative to Kappa for Accuracy Assessment of Remote Sensing-Based Image Classification.

Sensors (Basel, Switzerland)·2022
Same author

Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan.

Sensors (Basel, Switzerland)·2022
Same author

Mask R-CNN-based building extraction from VHR satellite data in operational humanitarian action: An example related to Covid-19 response in Khartoum, Sudan.

Transactions in GIS : TG·2021
Same author

Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors.

Sensors (Basel, Switzerland)·2021

Related Experiment Video

Updated: Dec 8, 2025

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

4.2K

Big Earth data: disruptive changes in Earth observation data management and analysis?

Martin Sudmanns1, Dirk Tiede1, Stefan Lang1

  • 1Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.

International Journal of Digital Earth
|September 17, 2020
PubMed
Summary

The growing volume of Earth observation (EO) data, termed big Earth data, requires evolving traditional workflows. Web-based systems are key to revolutionizing EO applications and addressing these challenges.

Keywords:
Digital earthdata accessobject-based image analysis (OBIA)remote sensing workflowsatellite data portals

More Related Videos

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.2K
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

7.1K

Related Experiment Videos

Last Updated: Dec 8, 2025

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

4.2K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.2K
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

7.1K

Area of Science:

  • Earth Science
  • Geospatial Information Science
  • Data Science

Background:

  • Consistent transformation of Earth observation (EO) data into global information layers presents a persistent challenge.
  • The emergence of 'big Earth data' introduces significant challenges to traditional analytical workflows.

Purpose of the Study:

  • To investigate the impact of big Earth data on EO workflows.
  • To explore the evolution of EO systems in response to big data.
  • To identify challenges and opportunities in adopting big Earth data.

Main Methods:

  • Analysis of existing EO systems and portals.
  • Contextualization of these systems within big data challenges.
  • Identification of shortcomings and future development needs.

Main Results:

  • Traditional EO workflows face significant challenges with big Earth data.
  • Web-based workflows are increasingly relied upon by analysts and end-users.
  • Selected systems and portals show varying degrees of readiness for big Earth data.

Conclusions:

  • An evolution of Earth observation is necessary to revolutionize its applications.
  • Addressing the challenges of big Earth data requires advancements in EO systems and workflows.
  • Future developments should focus on enhancing Web-based platforms for big Earth data utilization.