No abstract

No abstract

As the biggest carbon flux of terrestrial ecosystems from photosynthesis, gross primary productivity (GPP) is an important indicator in understanding the carbon cycle and biogeochemical process of terrestrial ecosystems. Despite advances in remote sensing-based GPP modeling, spatial and temporal variations of GPP are still uncertain especially under extreme climate conditions such as droughts. As the only official products of global spatially explicit GPP, MOD17A2H (GPPMOD) has been widely used to assess the variations of carbon uptake of terrestrial ecosystems. However, systematic assessment of its performance has rarely been conducted especially for the grassland ecosystems where inter-annual variability is high. Based on a collection of GPP datasets (GPPEC) from a global network of eddy covariance towers (FluxNet), we compared GPPMOD and GPPEC at all FluxNet grassland sites with more than five years of observations. We evaluated the performance and robustness of GPPMOD in different grassland biomes (tropical, temperate, and alpine) by using a bootstrapping method for calculating 95% confident intervals (CI) for the linear regression slope, coefficients of determination (R2), and root mean square errors (RMSE). We found that GPPMOD generally underestimated GPP by about 34% across all biomes despite a significant relationship (R2 = 0.66 (CI, 0.63–0.69), RMSE = 2.46 (2.33–2.58) g Cm−2 day−1) for the three grassland biomes. GPPMOD had varied performances with R2 values of 0.72 (0.68–0.75) (temperate), 0.64 (0.59–0.68) (alpine), and 0.40 (0.27–0.52) (tropical). Thus, GPPMOD performed better in low GPP situations (e.g., temperate grassland type), which further indicated that GPPMOD underestimated GPP. The underestimation of GPP could be partly attributed to the biased maximum light use efficiency (εmax) values of different grassland biomes. The uncertainty of the fraction of absorbed photosynthetically active radiation (FPAR) and the water scalar based on the vapor pressure deficit (VPD) could have other reasons for the underestimation. Therefore, more accurate estimates of GPP for different grassland biomes should consider improvements in εmax, FPAR, and the VPD scalar. Our results suggest that the community should be cautious when using MODIS GPP products to examine spatial and temporal variations of carbon fluxes.

In the past three decades, breakthroughs in satellites and remote sensing have highly demonstrated their potential to characterize and model the various components of the hydrological cycle. A wealth of satellite missions are launched and some of the missions are specifically designed for hydrological research. Given the massive big data for hydrology, it is time for hydrology to embrace the fourth paradigm, data intensive science. This paper aims to highlight available and emergent technologies and missions in the field of Earth observation that have contributed greatly to hydrological science, the current status of those technologies and their improvements in our understanding of hydrological components, and to identify the important and emerging issues in Earth observation data applications in hydrology. This review will provide the readers with detail of Earth observation progress applications in hydrology.

In the context of global change exacerbating the water crisis, it is difficult to solve the new problems of water resource management based on traditional hydrology without considering other aspects of water circulation, such as biotic dynamics. Vegetation, which once was thought to play only a relatively minor role and was ignored or treated as a static component in models, has now been recognized as one of the most important factors in water circulation. Ecohydrology has been promoted as a concept that links ecological and hydrological processes and considers interactions between water resources and ecosystems. Ecohydrological models are not only important tools for studying the mechanisms of ecological patterns and processes but also essential tools to assess the effects of environmental change on hydrological and ecological processes, providing solutions to issues of water management. This paper: 1) analyzes the characteristics of the interactions between terrestrial vegetation and hydrological processes; 2) summarizes the categories of existing watershed ecohydrological models for analysis and discusses the advantages and disadvantages of different kinds of ecohydrological models; 3) reviews the typical achievements of the application of ecohydrological models; and 4) illustrates the key issues of ecohydrological models at the watershed scale.

No abstract

No abstract

This paper conducts a novel study in China’s Jing-Jin-Ji region to investigate the determinants of population distribution and short-term migration based on a comprehensive dataset including traditional census data, earth observation data, and emerging Internet data. Our results show that due to the high level of urbanization in this region, natural conditions are no longer the strongest determinants of population distribution. New transportation modes, such as high-speed rail, have arisen as a significant determinant of population distribution and short-term migration, particularly in large cities. Socio-economic factors such as GDP, investment, urbanization level, and technology, which are traditionally assumed to govern population distribution and short-term migration, have less influence although education still remains an important factor affecting population distribution. These findings will contribute valuable information to regional planning decision-making in the Jing-Jin-Ji region.