Remote Sensing Applications-Society and Environment

Scope & Guideline

Pioneering insights from remote sensing for global sustainability.

Introduction

Delve into the academic richness of Remote Sensing Applications-Society and Environment with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN2352-9385
PublisherELSEVIER
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 2015 to 2024
AbbreviationREMOTE SENS APPL / Remote Sens. Appl.-Soc. Environ.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

The journal 'Remote Sensing Applications: Society and Environment' focuses on the application of remote sensing technologies to address environmental and socio-economic challenges. The journal encourages interdisciplinary approaches, integrating remote sensing with geographical information systems (GIS), machine learning, and ecological modeling.
  1. Remote Sensing Methodologies:
    The journal emphasizes various remote sensing methodologies, including satellite imagery, UAV (drone) data, and LiDAR, to assess land cover, vegetation health, and environmental changes.
  2. Environmental Monitoring and Assessment:
    A core focus of the journal is environmental monitoring, including the assessment of climate change impacts, deforestation, urbanization, and habitat loss through remote sensing techniques.
  3. Socio-economic Applications:
    The journal explores the socio-economic implications of environmental changes, including urban heat island effects, land use changes, and their impacts on local communities and economies.
  4. Machine Learning and Data Analysis:
    The integration of machine learning techniques for analyzing remote sensing data is a significant area of interest, enhancing the accuracy and efficiency of environmental assessments.
  5. Ecosystem Services and Management:
    Research on ecosystem services, including the quantification and management of natural resources, is a key theme, highlighting the importance of remote sensing in sustainable environmental practices.
The journal has witnessed a shift towards emerging themes that reflect current environmental concerns and technological advancements. These trends indicate the evolving landscape of remote sensing applications in addressing critical issues.
  1. Machine Learning Applications:
    There is a growing trend towards employing machine learning algorithms to enhance the analysis of remote sensing data, particularly in areas like crop monitoring, land cover classification, and ecological modeling.
  2. Climate Change Impact Studies:
    Research focusing on the impacts of climate change on ecosystems and human activities is increasingly prevalent, reflecting the urgent need to understand and mitigate climate-related challenges.
  3. Urbanization and Heat Island Effects:
    As urban areas expand, studies addressing urbanization effects, particularly urban heat islands and their socio-economic impacts, have gained significant traction.
  4. Water Quality and Resource Management:
    Emerging themes include the assessment of water quality using remote sensing technologies, reflecting global concerns over freshwater resources and pollution.
  5. Biodiversity and Habitat Conservation:
    Research on biodiversity monitoring and habitat conservation using remote sensing tools is trending, highlighting the role of these technologies in protecting ecosystems.

Declining or Waning

While the journal continues to thrive in various domains, certain themes have shown a decline in prominence over recent years. These waning scopes indicate a shift in research focus and priorities within the journal's publications.
  1. Traditional Land Cover Mapping:
    There has been a noticeable decline in papers focusing on traditional land cover mapping techniques, as researchers increasingly adopt more advanced methodologies such as machine learning and hybrid approaches.
  2. Basic Environmental Monitoring:
    Basic environmental monitoring studies, which do not integrate advanced technologies or interdisciplinary approaches, appear to be less frequent. This reflects a trend towards more complex and comprehensive assessments.
  3. Single Data Source Studies:
    Papers relying solely on single data sources for analysis are becoming less common, as the integration of multi-source data is now favored for more robust conclusions.

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