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- Sun, Bin; Wang, Yan; Li, Zengyuan; Gao, Wentao; Wu, Junjun; Li, Changlong; Song, Zhangliang; Gao, Zhihai
- Catena 2019 v.179 pp. 85-97
- agricultural land; arid lands; carbon cycle; climate; data collection; desertification; deserts; forest land; grasslands; land degradation; land use; moderate resolution imaging spectroradiometer; population characteristics; remote sensing; satellites; shrublands; simulation models; soil organic carbon; soil respiration; spatial variation; temporal variation; time series analysis; China
- ... Accurate quantitative estimates of Soil Organic Carbon Density (SOCD) can effectively represent regional carbon cycle processes and regulation mechanisms, and can serve as reference data when making land management decisions. Limited research, however, has been carried out in arid or desert zones covered with sparse vegetation, despite the fact that these cover wide areas of the earth and play a s ...
- Liu, Q.J.; Zhang, H.Y.; Gao, K.T.; Xu, B.; Wu, J.Z.; Fang, N.F.
- Catena 2019 v.179 pp. 107-118
- case studies; land use; mixing; neural networks; normalized difference vegetation index; prediction; rain; regression analysis; rivers; runoff; sediments; soil erosion; suspended sediment; time series analysis; topography; variance; watersheds; China
- ... Suspended sediment concentration (SSC) time series are highly nonlinear and nonstationary due to numerous influencing factors that can be characterized by specific time scales, thereby increasing the difficulty of performing SSC simulations. Analyzing the spectral and temporal information of the SSC and its contributing factors can improve the resulting simulation efforts. In this study, the Hilbe ...