DKNN: deep kriging neural network for interpretable geospatial interpolation

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-05-06 DOI:10.1080/13658816.2024.2347316

Kaiqi Chen, Enbo Liu, Min Deng, Xiaoyong Tan, Jiaoju Wang, Yan Shi, Zhizhong Wang

引用次数: 0

Abstract

Geospatial interpolation plays a pivotal role in spatial analysis because it provides high-quality data support for various spatiotemporal data mining (STDM) tasks. However, statistical methods, su...

查看原文本刊更多论文

DKNN：用于可解释地理空间插值的深度克里金神经网络

地理空间插值在空间分析中起着举足轻重的作用，因为它能为各种时空数据挖掘（STDM）任务提供高质量的数据支持。然而，统计方法、...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.