Estimation of All-Sky High-Resolution Gross Primary Production Across Different Biome Types Using Active Microwave Satellite Images and Environmental Data

被引:0
|
作者
Chen, Jiang [1 ]
Zhang, Zhou [1 ]
机构
[1] Univ Wisconsin, Dept Biol Syst Engn, Madison, WI 53706 USA
基金
美国农业部; 美国食品与农业研究所;
关键词
Optical sensors; Optical imaging; Biomedical optical imaging; Adaptive optics; Remote sensing; Microwave imaging; Radar polarimetry; Climate change; Satellites; Spatial resolution; Carbon; Sentinel-1; Integrated optics; Data models; Active microwave satellite; all-sky conditions; gross primary production (GPP); high spatial resolution; LIGHT-USE EFFICIENCY; MACHINE LEARNING-METHODS; CHLOROPHYLL CONTENT; LANDSAT; 8; REMOTE; SENTINEL-1; MODIS; WHEAT; PHENOLOGY; FOREST;
D O I
10.1109/JSTARS.2024.3422795
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Gross primary production (GPP) measures the amount of carbon fixed by plants and, thus, plays a significant role in the terrestrial carbon cycle and global food security, especially in the context of climate change and carbon neutrality. Currently, all-sky high-resolution (<100 m) GPP is increasingly needed for a better understanding of the food-carbon-water-energy nexus. However, previous studies usually used optical satellites to estimate clear-sky GPP at kilometer-scale resolution. Due to missing estimates under cloudy-sky conditions, monitoring spatio-temporal changes in GPP from optical satellites would suffer from some uncertainties. Moreover, one issue of some previous studies is that they only used optical satellite images or environmental data to estimate GPP rather than jointly integrating them and biome types. To address these challenges, this study attempts to use active microwave Sentinel-1 synthetic aperture radar (SAR) images at 10 m resolution to estimate all-sky GPP. GPP measurements across nine biome types in North America and Sentinel-1 images were employed to develop the SAR-based all-sky model. Meanwhile, an optical-based clear-sky model with Landsat-8 images was also proposed for comparison. The results revealed that, first, Sentinel-1 SAR images can be utilized to estimate all-sky GPP. By integrating Sentinel-1 SAR images, environmental data, and biome types, the optimal SAR-based model showed high accuracy in estimating all-sky daily GPP that is coefficient of determination (R-2) = 0.764, root-mean-square error (RMSE) = 1.976 gC/m(2)/d, and mean absolute error (MAE) = 1.308 gC/m(2)/d. Second, the optimal optical-based model had reasonable validation results in estimating clear-sky daily GPP (R-2 = 0.809, RMSE = 1.762 gC/m(2)/d, and MAE = 1.165 gC/m(2)/d). Third, Landsat-8 optical images contributed more than environmental data in the optical-based model, while the contribution of environmental data was higher than Sentinel-1 SAR images in the SAR-based model. Fourth, the optical-based model had better performance than the SAR-based model in estimating clear-sky daily GPP, and these two models showed reasonable consistency (R-2 = 0.730 and RMSE = 1.858 gC/m(2)/d) and can be utilized together. Therefore, this study demonstrated that active microwave provides an important data source to estimate all-sky high-resolution GPP, advancing our understanding of the carbon cycle, food security, and environmental change.
引用
收藏
页码:12969 / 12982
页数:14
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