Urban land surface temperature forecasting: a data-driven approach using regression and neural network models

IF 3.3 4区地球科学 Q2 ENVIRONMENTAL SCIENCES

Geocarto International Pub Date : 2024-01-25 DOI:10.1080/10106049.2023.2299145

Nimish Gupta, Bharath Haridas Aithal

引用次数: 0

Abstract

The insinuations of the ailments associated with the unrestrained and disorganized proliferation of artificial impervious materials over natural surfaces are prevalent among city dwellers. These im...

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城市地表温度预报：利用回归和神经网络模型的数据驱动方法

城市居民普遍认为，人工不透水材料在自然地表上无节制、无组织地扩散会带来各种疾病。这些影...

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来源期刊

Geocarto International ENVIRONMENTAL SCIENCES-GEOSCIENCES, MULTIDISCIPLINARY

CiteScore

6.30

自引率

13.20%

发文量

407

审稿时长

>12 weeks

期刊介绍： Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community. The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines; Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.