Remote Sensing - Journal - MOST Wiedzy

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Remote Sensing

ISSN:

2072-4292

Disciplines
(Field of Science):

  • Automation, electronic and electrical engineering (Engineering and Technology)
  • Information and communication technology (Engineering and Technology)
  • Civil engineering and transport (Engineering and Technology)
  • Environmental engineering, mining and energy (Engineering and Technology)
  • Forestry (Agricultural sciences)
  • Agriculture and horticulture (Agricultural sciences)
  • Social and economic geography and spatial management (Social studies)
  • Law (Social studies)
  • Earth and related environmental sciences (Natural sciences)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2021 100 Ministry Scored Journals List 2019
Ministry points - previous years
Year Points List
2021 100 Ministry Scored Journals List 2019
2020 100 Ministry Scored Journals List 2019
2019 100 Ministry Scored Journals List 2019
2018 35 A
2017 35 A
2016 35 A
2015 35 A
2014 35 A
2013 35 A

Model:

Open Access

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2019 6.1
Points CiteScore - previous years
Year Points
2019 6.1
2018 5.6
2017 5.3
2016 5.2
2015 4.3
2014 3.9
2013 3.7
2012 2.7
2011 1.1

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total: 27

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Catalog Journals

Year 2021
  • Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
    Publication
    • S. Shivappriya
    • M. Priyadarsini
    • A. Stateczny
    • C. Puttamadappa
    • B. Parameshachari

    - Remote Sensing - Year 2021

    Object detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...

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  • Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
    Publication
    • W. Wojnowski
    • S. Wei
    • W. Li
    • T. Yin
    • X. Li
    • G. Lai Fern Ow
    • M. Lokman Mohd Yusof
    • A. Whittle

    - Remote Sensing - Year 2021

    The fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...

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  • Use of Bi-Temporal ALS Point Clouds for Tree Removal Detection on Private Property in Racibórz, Poland
    Publication
    • P. Przewoźna
    • P. Hawryło
    • K. Zięba-Kulawik
    • A. Inglot
    • K. Mączka
    • P. Wężyk
    • P. Matczak

    - Remote Sensing - Year 2021

    Trees growing on private property have become an essential part of urban green policies. In many places, restrictions are imposed on tree removal on private property. However, monitoring compliance of these regulations appears difficult due to a lack of reference data and public administration capacity. We assessed the impact of the temporary suspension of mandatory permits on tree removal, which was in force in 2017 in Poland,...

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Year 2020
Year 2019
Year 2018
Year 2016

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