Introducing Variations of Predictors as Optional Predictors Offers the Potential to Improve the Downscaling Performance of Geographically Weighted Regression Model-Reference-Cited by-同舟云学术

Introducing Variations of Predictors as Optional Predictors Offers the Potential to Improve the Downscaling Performance of Geographically Weighted Regression Model

Published:2023 Issue: Volume:11 Page:25203-25216
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhang Haijun¹^ORCID,Bai Jingfeng¹,Dai Sha²,Qi Pengcheng¹^ORCID,Wang Shuzhuan¹^ORCID,Fan Hongyan¹^ORCID

Affiliation:

1. Henan Province Engineering Research Center of Environmental Laser Remote Sensing Technology and Application, Nanyang Normal University, Nanyang, China

2. Department of College English Teaching and Studies, Nanyang Normal University, Nanyang, China

Funder

National Natural Science Foundation of China

Henan Province Soft Science Research Program

Higher Discipline Innovation and Talent Introduction Base of Henan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10064290.pdf?arnumber=10064290

Reference67 articles.

1. Station‐based non‐linear regression downscaling approach: A new monthly precipitation downscaling technique

2. MODIS vegetation index user’s guide (MOD13 series);didan,2015

3. Deep Learning for Daily Precipitation and Temperature Downscaling

4. Comparison of Different Methods for Spatial Downscaling of GPM IMERG V06B Satellite Precipitation Product Over a Typical Arid to Semi-Arid Area

5. A Neural-Network Based Spatial Resolution Downscaling Method for Soil Moisture: Case Study of Qinghai Province

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing drought monitoring through spatial downscaling: A geographically weighted regression approach using TRMM 3B43 precipitation in the Urmia Lake Basin;Earth Science Informatics;2024-05-15