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Manipulation and Analysis01:21

Manipulation and Analysis

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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...
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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...
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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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All organisms have a position within an ecosystem. The complete set of living and nonliving factors—including food resources, climate, and terrain—that define the position of a given organism are collectively referred to as the organism’s ecological niche.
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Related Experiment Video

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Exploring research on ecotechnology through artificial intelligence and bibliometric maps.

Ricardo Ruiz-Sánchez1,2, Ricardo Arencibia-Jorge2, Julia Tagüeña2,3

  • 1Unidad Profesional Interdisciplinaria de Ingeniería Palenque (UPIIP), Instituto Politécnico Nacional, Palenque, Chiapas, CP 29960, Mexico.

Environmental Science and Ecotechnology
|February 8, 2024
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Summary

Ecotechnology is key for sustainable strategies but is under-researched. This study uses machine learning and bibliometrics to map the field, identify key themes, and highlight leading nations, linking them to UN Sustainable Development Goals.

Keywords:
BibliometricsEcotechnologiesNetwork analysisSOM neural networksSustainable development goals

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Area of Science:

  • Environmental Science
  • Sustainability Studies
  • Technology and Innovation

Background:

  • Ecotechnology is crucial for sustainable socio-environmental strategies.
  • The field of ecotechnology is not yet fully explored or understood.
  • There is a need to map the current research landscape and identify key players.

Purpose of the Study:

  • To delineate the scope and landscape of ecotechnology research.
  • To elucidate pivotal research themes, challenges, and opportunities within ecotechnology.
  • To identify leading nations and connect ecotechnology advancements to the UN's 2030 Sustainable Development Goals.

Main Methods:

  • Utilized machine learning algorithms for data analysis.
  • Employed bibliometric analysis to assess research trends and impact.
  • Synthesized findings to map the ecotechnology domain and its global standing.

Main Results:

  • Identified key research themes and significant challenges in ecotechnology.
  • Highlighted the vanguard nations and institutions leading ecotechnology research.
  • Established clear links between ecotechnology advancements and specific UN Sustainable Development Goals.

Conclusions:

  • Ecotechnology research is a rapidly evolving and critical field for achieving sustainability.
  • The study provides a comprehensive overview and roadmap for future ecotechnology research.
  • Findings underscore the societal impact and global importance of advancing ecotechnology for sustainable development.