ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Scope & Guideline

Elevating Knowledge in Photogrammetry and Remote Sensing

Introduction

Welcome to your portal for understanding ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageMulti-Language
ISSN0924-2716
PublisherELSEVIER
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 1989 to 2024
AbbreviationISPRS J PHOTOGRAMM / ISPRS-J. Photogramm. Remote Sens.
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

The ISPRS Journal of Photogrammetry and Remote Sensing focuses on advancing the theory and application of photogrammetry and remote sensing technologies. It aims to publish high-quality research articles that contribute to the understanding and development of methods for the acquisition, analysis, and interpretation of geospatial data.
  1. Remote Sensing Techniques and Applications:
    The journal covers a wide range of remote sensing techniques, including satellite, aerial, and UAV-based methods, focusing on their applications in environmental monitoring, urban planning, agriculture, and disaster management.
  2. Photogrammetry Innovations:
    Research related to photogrammetry, including 3D modeling, structure from motion, and image processing techniques, is a key focus area, emphasizing advancements in methodology and technology.
  3. Data Fusion and Integration:
    The journal emphasizes the integration of various data sources, such as combining optical, radar, and LiDAR data, to enhance the accuracy and richness of geospatial information.
  4. Machine Learning and AI Applications:
    There is a strong emphasis on the application of machine learning and artificial intelligence techniques in remote sensing, particularly for classification, change detection, and object recognition.
  5. Environmental and Agricultural Monitoring:
    Research focusing on the use of remote sensing for monitoring environmental changes, agricultural practices, and land use dynamics is a significant part of the journal's scope.
  6. Urban Remote Sensing:
    The journal addresses urban studies through remote sensing, including urban heat islands, land cover classification, and infrastructure monitoring.
The ISPRS Journal is witnessing a dynamic evolution in its thematic focus, with several emerging trends reflecting the latest advancements in technology and changing research needs.
  1. AI and Machine Learning in Remote Sensing:
    There is a significant increase in research focusing on the application of AI and machine learning in remote sensing, particularly for tasks like image classification, change detection, and data fusion.
  2. Multi-Source Data Fusion:
    Emerging studies increasingly emphasize the integration of data from multiple sources, such as combining satellite, UAV, and ground-based sensors, to enhance analysis and improve accuracy.
  3. Real-Time Remote Sensing Applications:
    Research is trending towards real-time applications of remote sensing data, particularly in environmental monitoring and disaster response, highlighting the need for rapid data processing and analysis.
  4. Urban Remote Sensing and Smart Cities:
    The focus on urban applications of remote sensing is growing, with increased interest in monitoring urban dynamics, infrastructure, and environmental impacts in the context of smart city initiatives.
  5. Phenological Studies and Climate Monitoring:
    An emerging trend is the use of remote sensing for detailed studies of phenology and climate change impacts, contributing to a better understanding of ecosystem dynamics.

Declining or Waning

While the ISPRS Journal maintains a broad focus, certain themes have shown a decline in prominence over recent years, reflecting shifts in research priorities and advancements in technology.
  1. Traditional Photogrammetry:
    As new technologies and methodologies emerge, traditional photogrammetry techniques are becoming less emphasized in favor of more advanced methods such as machine learning and AI-driven approaches.
  2. Basic Remote Sensing Algorithms:
    The focus on basic algorithms for remote sensing data processing is waning as researchers increasingly adopt complex, data-driven models that leverage deep learning and other advanced techniques.
  3. Single-Sensor Studies:
    Research that focuses solely on single-sensor studies is declining, with a growing preference for multi-sensor approaches that provide more comprehensive insights.
  4. Manual Data Processing Techniques:
    There is a noticeable reduction in publications discussing manual or semi-automated data processing techniques, as the field moves towards fully automated and AI-driven solutions.

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