NPP estimation by fusing geodetector and deep spatio-temporal networks
In recent years, deep learning has demonstrated significant potential in net primary productivity (NPP) estimation but the existing methods fall short in fully exploiting the spatio-temporal dependencies inherent in remote sensing data for modeling NPP. To address this limitation, we propose a novel...
Saved in:
| Main Authors: | Xiaohui He, Chenqiao Yuan, Panle Li, Xijie Cheng, Mengjia Qiao, Xiaoyu He, Nan Yang, Guangsheng Zhou, Jiandong Shang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2515265 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Combining the SHAP Method and Machine Learning Algorithm for Desert Type Extraction and Change Analysis on the Qinghai–Tibetan Plateau
by: Ruijie Lu, et al.
Published: (2024-11-01) -
Characterization of spatio-temporal evolution of grain production and identification of its heterogeneity drivers in Sichuan Province based on Geodetector and GWR models
by: Huae Dang, et al.
Published: (2025-06-01) -
Climate-Driven Effects on NPP in the Tibetan Plateau Alpine Grasslands Diminish with Increasing Elevation
by: Ze Tang, et al.
Published: (2024-12-01) -
Analysis of Spatiotemporal Variation of NDVI in Pearl River Basin and Its Driving Force Based on Geodetector
by: WANG Ruiqing, et al.
Published: (2022-01-01) -
Reconstruction of Cropland for the Rikaze Area of China Since the Tubo Dynasty (AD 655)
by: Hongxia Pan, et al.
Published: (2025-05-01)