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SCIESCOPUSQ3

Spatial Information Research

SPRINGER SINGAPORE PTE LTD, South Korea

Spatial Information Research is an academic journal published by SPRINGER SINGAPORE PTE LTD (South Korea). Identifiers: ISSN 2366-3286, eISSN 2366-3294. Indexed in SCIE, SCOPUS. Metrics: JIF 2.0, CiteScore 5.5, SJR 0.465, SNIP 0.83. Subject areas: REMOTE SENSING. tlooto lists 2,515 papers from this journal.

CiteScore

5.50

Scopus citation metric

SJR

0.465

SCImago rank

SNIP

0.83

Source normalized impact

Percentage rank

-

JIF percentile rank

Journal profile

ISSN
2366-3286
eISSN
2366-3294
Abbreviation
SPAT INF RES
Publisher
SPRINGER SINGAPORE PTE LTD
Country
South Korea

Web of Science categories

No Web of Science category data available.

Scopus ASJC categories

170217061903 Computers in Earth Sciences3305 Geography

Papers in this journal

Recent papers

  1. A multimodal 15-minute city index for South Asian cities: integrating informal transport modes in accessibility framework for Varanasi, India

    2026

  2. Precision mapping using a UAV mounted 3DT Scanfly LiDAR system

    2026

  3. Exploratory spatial co-patterns of VIIRS nighttime radiance and land cover compositional evenness at 10-km resolution in Java, Indonesia

    2026

  4. Geo-enabled large language models for landslide risk assessment in Kishtwar, India

    2026

  5. PCA-WSA based hybrid modeling approach for sub-watershed prioritization of Phalgu River Basin, Middle Ganga Plain, India

    2026

Most cited papers

  1. The role of artificial neural network and machine learning in utilizing spatial information

    2022 · 221 citations

  2. Exploring groundwater potential zones using MIF technique in semi-arid region: a case study of Hingoli district, Maharashtra

    2017 · 127 citations

  3. Groundwater potential mapping using analytical hierarchical process: a study on Md. Bazar Block of Birbhum District, West Bengal

    2017 · 125 citations

  4. Crop yield prediction in cotton for regional level using random forest approach

    2020 · 124 citations

  5. Machine learning based aspect level sentiment analysis for Amazon products

    2020 · 79 citations