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jorsg
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Journal of Remote Sensing & GIS

E-ISSN: 2230-7990

Editor Overview

jorsg maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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Dr. Shefali Agarwal

Group Director & Scientist/Engineer – G
Indian Institute of Remote Sensing, ISRO, Dept. of Space, Uttarakhand, india
Editor in Chief
Journal of Remote Sensing & GIS
Email :

Institutional Profile Link : https://www.iirs.gov.in/shefali-agrawal

Publisher

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.

E-mail:
[email protected]
Phone:
(+91)-0120- 4781-200
Mobile:
(+91)-981-007-8958
(+91)-966-7725-932

About the Journal

Journal of Remote Sensing & GIS [2230-7990(e)] is a peer-reviewed hybrid open-access journal launched in 2011 focused on practical and theoretical issues, collection, analysis, modeling, interpretation, and display of spatial data, connections between GIS and related technologies and also new GIS applications which help to solve current issues & problems.

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Journal Particulars

Title
Journal of Remote Sensing & GIS
Journal Abbreviation
jorsg
Issues Per Year (Frequency)
3 Issues (Jan-April, May-August, Sept-Dec)
ISSN
2230-7990

Publisher
STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI
10.37591/JoRSG
Copyright
STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
Starting Year
2010
Subject
Multidisciplinary

Language
English
Publication Format
Hybrid Open Access

Copyright Licensing Policy
Type of Publication
Peer-reviewed Journal (Refereed Journal)
Website
https://journals.stmjournals.com/jorsg
Address
STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin – 201301

Principal Contact
Prashant Chauhan
[email protected]

Latest Articles

Volume: 16, Issue: 02, Year: 2025

Regular Issue  Subscription Review Article Published on :- 08/05/2025

Ritik Sahu, Vinay Lowanshi, Nitya Khare
Keywords: Soil Health, Convolutional Neural Networks, Recurrent Neural Networks

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