Redirigiendo al acceso original de articulo en 15 segundos...
Inicio  /  Applied Sciences  /  Vol: 13 Par: 10 (2023)  /  Artículo
ARTÍCULO
TITULO

Spatial?Temporal Correlation Considering Environmental Factor Fusion for Estimating Gross Primary Productivity in Tibetan Grasslands

Qinmeng Yang    
Ningming Nie    
Yangang Wang    
Xiaojing Wu    
Weihua Liu    
Xiaoli Ren    
Zijian Wang    
Meng Wan and Rongqiang Cao    

Resumen

Gross primary productivity (GPP) is an important indicator in research on carbon cycling in terrestrial ecosystems. High-accuracy GPP prediction is crucial for ecosystem health and climate change assessments. We developed a site-level GPP prediction method based on the GeoMAN model, which was able to extract spatiotemporal features and fuse external environmental factors to predict GPP on the Tibetan Plateau. We evaluated four models? behavior?Random Forest (RF), Support Vector Machine (SVM), Deep Belief Network (DBN), and GeoMAN?in predicting GPP at nine flux observation sites on the Tibetan Plateau. The GeoMAN model achieved the best results (R2 = 0.870, RMSE = 0.788 g Cm-2 d-1, MAE = 0.440 g Cm-2 d-1). Distance and vegetation type of the flux sites influenced GPP prediction, with the latter being more significant. The different grassland vegetation types exhibited different sensitivity to environmental factors (Ta, PAR, EVI, NDVI, and LSWI) for GPP prediction. Among them, the site located in the alpine swamp meadow was insensitive to changes in environmental factors; the GPP prediction accuracy of the site located in the alpine meadow steppe decreased significantly with the changes in environmental factors; and the GPP prediction accuracy of the site located in the alpine Kobresia meadow also varied with environmental factor changes, but to a lesser extent than the former. This study provides a good reference that deep learning model is able to achieve good accuracy in GPP simulation when considers spatial, temporal, and environmental factors, and the judgement made by deep learning model conforms to basic knowledge in the relevant field.

 Artículos similares

       
 
Hongming Li, Lilai Zhang, Hao Cao and Yirui Wu    
Deoxyribonucleic Acid (DNA) computing has demonstrated great potential in data encryption due to its capability of parallel computation, minimal storage requirement, and unbreakable cryptography. Focusing on high-dimensional image data for encryption wit... ver más
Revista: Applied Sciences

 
Loris Belcastro, Domenico Carbone, Cristian Cosentino, Fabrizio Marozzo and Paolo Trunfio    
Since the advent of Bitcoin, the cryptocurrency landscape has seen the emergence of several virtual currencies that have quickly established their presence in the global market. The dynamics of this market, influenced by a multitude of factors that are d... ver más
Revista: Algorithms

 
Lorenzo De Carlo, Mohammad Farzamian, Antonietta Celeste Turturro and Maria Clementina Caputo    
In recent years, geophysical techniques have been increasingly used to monitor flow and transport processes in the Earth critical zone (ECZ). Among these, electrical resistivity tomography (ERT) is a powerful tool used to predict hydrological parameters ... ver más
Revista: Water

 
Jinrong Bao, Chenzhen Ji, Deng Pan, Chao Zong, Ziyang Zhang and Tong Zhu    
The propagation mechanism of flow disturbance under acoustic excitations plays a crucial role in thermoacoustic instability, especially when considering the effect of non-premixed combustion on heat release due to reactant mixing and diffusion. This rela... ver más
Revista: Aerospace

 
Guo Li, Yida Teng and Huimin Zhou    
Aero engine compressor disks are typically life-limited parts and it is necessary to secure them through the implementation of an engineering plan and a manufacturing plan. Specifically, the engineering plan recommends the quantification of the safety of... ver más
Revista: Aerospace