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International Journal Of Applied Earth Observation and Geoinformation
H-index 65

International Journal Of Applied Earth Observation and Geoinformation

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Environmental Sciences 55 315 463 55
Earth Science 83 90 117 30

Additional Metrics

Number of Best Scientists*: 744
Documents by Best Scientists*: 1015
Top 100 Ranked Scientists*: 15
SCIMAGO H-index: 144
SCIMAGO SJR: 2.241
Impact Factor: 8.6

Overview

Top Research Topics at International Journal of Applied Earth Observation and Geoinformation?

The journal mostly deals with topics like Remote sensing, Vegetation, Land cover, Normalized Difference Vegetation Index and Satellite imagery. The concepts on Remote sensing presented in the journal can also apply to other research fields, including Pixel and Scale (map). International Journal of Applied Earth Observation and Geoinformation focuses on Pixel research as part of the broader topic of Artificial intelligence.

In addition to Vegetation research, International Journal of Applied Earth Observation and Geoinformation aims to explore topics under Hydrology, Canopy and Physical geography. International Journal of Applied Earth Observation and Geoinformation connects research in Land cover with the related topic of Cartography. The study on Normalized Difference Vegetation Index presented is investigated in conjunction with research in Moderate-resolution imaging spectroradiometer.

  • Remote sensing (43.79%)
  • Vegetation (16.99%)
  • Land cover (13.46%)

What are the most cited papers published in the journal?

  • Multi- and hyperspectral geologic remote sensing: A review (595 citations)
  • Assessment with satellite data of the urban heat island effects in Asian mega cities (560 citations)
  • Urban sprawl: metrics, dynamics and modelling using GIS (493 citations)

Research areas of the most cited articles at International Journal of Applied Earth Observation and Geoinformation:

The most cited articles are mainly concerned with subjects like Remote sensing, Vegetation, Land cover, Normalized Difference Vegetation Index and Cartography. The published papers focus on Remote sensing but the discussions also offer insight into other areas such as Pixel and Canopy. The journal papers address concerns in the field of Vegetation by exploring it in line with topics in Hydrology which intersect with Soil water subjects.

What topics the last edition of the journal is best known for?

  • Ecology
  • Statistics
  • Artificial intelligence

The previous edition focused in particular on these issues:

The journal focuses on Remote sensing, Vegetation, Artificial intelligence, Mean squared error and Hyperspectral imaging. The Remote sensing works featured in it incorporate elements from Image resolution, Pixel and Land cover. The journal centers on topics in Vegetation, with a focus on Normalized Difference Vegetation Index.

The journal addresses concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning and Pattern recognition. The journal features Mean squared error research that overlaps with concepts in Coefficient of determination. Topics in Physical geography were tackled in line with various other fields like Climate change and China.

The most cited articles from the last journal are:

  • Fusion of Sentinel-2 and PlanetScope time-series data into daily 3 m surface reflectance and wheat LAI monitoring (15 citations)
  • Automated mapping of cultural heritage in Norway from airborne lidar data using faster R-CNN (12 citations)
  • An updated MODIS global urban extent product (MGUP) from 2001 to 2018 based on an automated mapping approach (10 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in International Journal of Applied Earth Observation and Geoinformation (based on the number of publications) are:

  • Andrew K. Skidmore (56 papers) published 4 papers at the last edition the same number as at the previous edition,
  • Freek D. van der Meer (31 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Alfred Stein (27 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • Roshanak Darvishzadeh (20 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • Jonathan Li (18 papers) published 11 papers at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in International Journal of Applied Earth Observation and Geoinformation (based on the number of publications) are:

  • Chinese Academy of Sciences (225 papers) published 53 papers at the last edition, 32 more than at the previous edition,
  • University of Twente (124 papers) published 16 papers at the last edition, 1 more than at the previous edition,
  • Wageningen University and Research Centre (85 papers) published 4 papers at the last edition the same number as at the previous edition,
  • International Institute of Minnesota (65 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Wuhan University (64 papers) published 17 papers at the last edition, 13 more than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 10.29% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 32.48% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.46% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.20% of all publications and 45.86% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data

    Wang Li;Wang Li;Zheng Niu;Rong Shang;Yuchu Qin

    (2020)
    247 Citations
  • Retrieval of aboveground crop nitrogen content with a hybrid machine learning method

    Katja Berger;Jochem Verrelst;Jean-Baptiste Féret;Tobias Hank

    (2020)
    178 Citations
  • Knowledge generation using satellite Earth Observations to support Sustainable Development Goals (SDG): a use case on Land Degradation

    Gregory Giuliani;Paolo Mazzetti;Mattia Santoro;Stefano Nativi

    (2020)
    145 Citations
  • Assessing the benefit of satellite-based Solar-Induced Chlorophyll Fluorescence in crop yield prediction

    Bin Peng;Kaiyu Guan;Wang Zhou;Chongya Jiang

    (2020)
    120 Citations
  • Demystifying LandTrendr and CCDC temporal segmentation

    (2022)
    118 Citations
  • Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery

    Dezhi Wang;Bo Wan;Jing Liu;Jing Liu;Yanjun Su

    (2020)
    115 Citations
  • Integrating remote sensing and geospatial big data for urban land use mapping: a review

    Jiadi Yin;Jiadi Yin;Jinwei Dong;Nicholas A.S. Hamm;Zhichao Li

    (2021)
    113 Citations
  • Fine-scale prediction of biomass and leaf nitrogen content in sugarcane using UAV LiDAR and multispectral imaging

    Yuri Shendryk;Jeremy Sofonia;Robert Garrard;Yannik Rist

    (2020)
    104 Citations
  • 10 m crop type mapping using Sentinel-2 reflectance and 30 m cropland data layer product

    (2022)
    102 Citations

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