Journal of Spatial Science

Journal of Spatial Science
期刊缩写:
J. Spatial Sci.
影响因子:
1
ISSN:
print: 1449-8596
on-line: 1836-5655
研究领域:
地学-地质学
h-index:
21
自引率:
5.30%
Gold OA文章占比:
9.82%
原创研究文献占比:
100.00%
SCI收录类型:
Science Citation Index Expanded (SCIE) || Scopus (CiteScore)
期刊介绍英文:
The Journal of Spatial Science publishes papers broadly across the spatial sciences including such areas as cartography, geodesy, geographic information science, hydrography, digital image analysis and photogrammetry, remote sensing, surveying and related areas. Two types of papers are published by he journal: Research Papers and Professional Papers. Research Papers (including reviews) are peer-reviewed and must meet a minimum standard of making a contribution to the knowledge base of an area of the spatial sciences. This can be achieved through the empirical or theoretical contribution to knowledge that produces significant new outcomes. It is anticipated that Professional Papers will be written by industry practitioners. Professional Papers describe innovative aspects of professional practise and applications that advance the development of the spatial industry.
CiteScore:
CiteScoreSJRSNIPCiteScore排名
5.00.4600.910
学科
排名
百分位
大类:Social Sciences
小类:Geography, Planning and Development
170 / 821
79%
大类:Earth and Planetary Sciences
小类:Atmospheric Science
60 / 148
59%
大类:Energy
小类:General Energy
30 / 73
59%
发文信息
中科院SCI期刊分区
大类 小类 TOP期刊 综述期刊
4区 地球科学
4区 自然地理 GEOGRAPHY, PHYSICAL
4区 遥感 REMOTE SENSING
WOS期刊分区
学科分类
Q4GEOGRAPHY, PHYSICAL
Q4REMOTE SENSING
历年影响因子
2015年1.0950
2016年0.7350
2017年1.0780
2018年1.7110
2019年1.4050
2020年1.9810
2021年1.8400
2022年1.9000
2023年1.0000
历年发表
2012年21
2013年31
2014年37
2015年32
2016年40
2017年29
2018年52
2019年49
2020年39
2021年31
2022年25
投稿信息
出版周期:
Semiannual
出版语言:
English
出版国家(地区):
AUSTRALIA
审稿时长:
>12 weeks
出版商:
Taylor and Francis Ltd.
编辑部地址:
SPATIAL SCIENCES INST, GPO BOX 6836, EAST PERTH, AUSTRALIA, WA 6892

Journal of Spatial Science - 最新文献

Analysis of vegetation influence on building shadow extraction in remote sensing imagery using deep convolutional neural networks

Pub Date : 2024-09-03 DOI: 10.1080/14498596.2024.2394439 Shuangquan Ge, Zihou Xu, Shaohan Cao, Dejun Feng, Wang Junfan

A novel approach to coral species classification using deep learning and unsupervised feature extraction

Pub Date : 2024-08-14 DOI: 10.1080/14498596.2024.2383881 R. Jannathul Firdous, S. Sabena

Land cover classification in high-resolution remote sensing: using Swin Transformer deep learning with texture features

Pub Date : 2024-08-07 DOI: 10.1080/14498596.2024.2386317 Yongle Zhang, Min Huang, Yanxi Chen, Xingzhu Xiao, Hao Li
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