Adjusting the Main Cropping Types in Mollisol Regions Could Improve the Net Primary Productivity of Low‐Producing Areas by 20%–30% Under Future Climate Change

Adjusting the Main Cropping Types in Mollisol Regions Could Improve the Net Primary Productivity of Low‐Producing Areas by 20%–30% Under Future Climate Change

Abstract Rationalizing site‐specific crop types is an effective strategy for ensuring food security under climate change. This study employed environmental covariates representing climate, soil, and vegetation, combined with a hybrid convolutional neural network ‐ Long Short‐term Memory‐self‐attenti...

Full description

Saved in:
Bibliographic Details
Main Authors: Yilin Bao, Xiangtian Meng, Huanjun Liu, Mingchang Wang, Fengmei Yao, Abdul Mounem Mouazen
Format: Article
Language:English
Published: Wiley 2025-07-01
Series:Earth's Future
Subjects:
net primary productivity
convolutional neural network‐long short‐term memory‐self‐attention model
interrelationships
crop adjustment
Mollisol regions
Online Access:https://doi.org/10.1029/2025EF006074
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items