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Continuous land-surface temperature (LST) observations from ground-based stations are an important reference dataset for validating remote-sensing LST products. However, a lack of evaluations of the representativeness of station observations limits the reliability of validation results. In this study, a new practical validation scheme is presented for validating remote-sensing LST products that includes a key step: assessing the spatial representativeness of ground-based LST measurements. Three indicators, namely, the dominant land-cover type (DLCT), relative bias (RB), and average structure scale (ASS), are established to quantify the representative levels of station observations based on the land-cover type (LCT) and LST reference maps with high spatial resolution. We validated MODIS LSTs using station observations from the Heihe River Basin (HRB) in China. The spatial representative evaluation steps show that the representativeness of observations greatly differs among stations and varies with different vegetation growth and other factors. Large differences in the validation results occur when using different representative level observations, which indicates a large potential for large error during the traditional T-based validation scheme. Comparisons show that the new validation scheme greatly improves the reliability of LST product validation through high-level representative observations. [ABSTRACT FROM AUTHOR]

Spatial identification of the urban-rural fringes is very significant for deeply understanding the development processes and regulations of urban space and guiding urban spatial development in the future. Traditionally, urban-rural fringe areas are identified using statistical analysis methods that consider indexes from single or multiple factors, such as population densities, the ratio of building land, the proportion of the non-agricultural population, and economic levels. However, these methods have limitations, for example, the statistical data are not continuous, the statistical standards are not uniform, the data is seldom available in real time, and it is difficult to avoid issues on the statistical effects from edges of administrative regions or express the internal differences of these areas. This paper proposes a convenient approach to identify the urban-rural fringe using nighttime light data of DMSP/OLS images. First, a light characteristics-combined value model was built in ArcGIS 10.3, and the combined characteristics of light intensity and the degree of light intensity fluctuation are analyzed in the urban, urban-rural fringe, and rural areas. Then, the Python programming language was used to extract the breakpoints of the characteristic combination values of the nighttime light data in 360 directions taking Tian An Men as the center. Finally, the range of the urban-rural fringe area is identified. The results show that the urban-rural fringe of Beijing is mainly located in the annular band around Tian An Men. The average inner radius is 19 km, and the outer radius is 26 km. The urban-rural fringe includes the outer portions of the four city center districts, which are the Chaoyang District, Haidian District, Fengtai District, and Shijingshan District and the part area border with Daxing District, Tongzhou District, Changping District, Mentougou District, Shunyi District, and Fangshan District. The area of the urban-rural fringe is approximately 765 km². This paper provides a convenient, feasible, and real-time approach for the identification of the urban-rural fringe areas. It is very significant to extract the urban-rural fringes. [ABSTRACT FROM AUTHOR]

Nighttime light data derived from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) in conjunction with the Soumi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) possess great potential for measuring the dynamics of Gross Domestic Product (GDP) at large scales. The temporal coverage of the DMSP-OLS data spans between 1992 and 2013, while the NPP-VIIRS data are available from 2012. Integrating the two datasets to produce a time series of continuous and consistently monitored data since the 1990s is of great significance for the understanding of the dynamics of long-term economic development. In addition, since economic developmental patterns vary with physical environment and geographical location, the quantitative relationship between nighttime lights and GDP should be designed for individual regions. Through a case study in China, this study made an attempt to integrate the DMSP-OLS and NPP-VIIRS datasets, as well as to identify an optimal model for long-term spatiotemporal GDP dynamics in different regions of China. Based on constructed regression relationships between total nighttime lights (TNL) data from the DMSP-OLS and NPP-VIIRS data in provincial units (R2 = 0.9648, P < 0.001), the temporal coverage of nighttime light data was extended from 1992 to the present day. Furthermore, three models (the linear model, quadratic polynomial model and power function model) were applied to model the spatiotemporal dynamics of GDP in China from 1992 to 2015 at both the country level and provincial level using the extended temporal coverage data. Our results show that the linear model is optimal at the country level with a mean absolute relative error (MARE) of 11.96%. The power function model is optimal in 22 of the 31 provinces and the quadratic polynomial model is optimal in 7 provinces, whereas the linear model is optimal only in two provinces. Thus, our approach demonstrates the potential to accurately and timely model long-term spatiotemporal GDP dynamics using an integration of DMSP-OLS and NPP-VIIRS data. [ABSTRACT FROM AUTHOR]

Scarce water resources are available in the arid and semi-arid areas of Northwest China, where significant water-related challenges will be faced in the coming decades. Quantitative evaluations of the spatio-temporal dynamics in ecosystem water use efficiency (WUE), as well as the underlying environmental controls, are crucial for predicting future climate change impacts on ecosystem carbon-water interactions and agricultural production. However, these questions remain poorly understood in this typical region. By means of continuous eddy covariance (EC) measurements and time-series MODIS data, this study revealed the distinct seasonal cycles in gross primary productivity (GPP), evapotranspiration (ET), and WUE for both grassland and cropland ecosystems, and the dominant climate factors performed jointly by temperature and precipitation. The MODIS WUE estimates from GPP and ET products can capture the broad trend in WUE variability of grassland, but with large biases for maize cropland, which was mainly ascribed to large uncertainties resulting from both GPP and ET algorithms. Given the excellent biophysical performance of the MODIS-derived enhanced vegetation index (EVI), a new greenness model (GR) was proposed to track the eight-day changes in ecosystem WUE. Seasonal variations and the scatterplots between EC-based WUE and the estimates from time-series EVI data (WUEGR) also certified its prediction accuracy with R2 and RMSE of both grassland and cropland ecosystems over 0.90 and less than 0.30 g kg-1, respectively. The application of the GR model to regional scales in the near future will provide accurate WUE information to support water resource management in dry regions around the world. [ABSTRACT FROM AUTHOR]

In this study, using the common classification systems of IGBP-17, IGBP-9, IPCC-5 and TC (vegetation, wetlands and others only), we studied spatial and areal inconsistencies in the three most recent multi-resource land cover products in a complex mountain-oasis-desert system and quantitatively discussed the uncertainties in classification system conversion. This is the first study to compare these products based on terrain and to quantitatively study the uncertainties in classification system conversion. The inconsistencies and uncertainties decreased from high to low levels of aggregation (IGBP-17 to TC) and from mountain to desert areas, indicating that the inconsistencies are not only influenced by the level of thematic detail and landscape complexity but also related to the conversion uncertainties. The overall areal inconsistency in the comparison of the FROM-GLC and GlobCover 2009 datasets is the smallest among the three pairs, but the smallest overall spatial inconsistency was observed between the FROM-GLC and MODISLC. The GlobCover 2009 had the largest conversion uncertainties due to mosaic land cover definition, with values up to 23.9%, 9.68% and 0.11% in mountainous, oasis and desert areas, respectively. The FROM-GLC had the smallest inconsistency, with values less than 4.58%, 1.89% and 1.2% in corresponding areas. Because the FROM-GLC dataset uses a hierarchical classification scheme with explicit attribution from the second level to the first, this system is suggested for producers of map land cover products in the future. [ABSTRACT FROM AUTHOR]

As one of the most important geographical units affected by global climate change, lakes are sensitive to climatic changes and are considered "indicators" of climate and the environment. In this study, changes in the spatial-temporal characteristics of the water levels of 204 global major lakes are systematically analyzed using satellite altimetry data (Hydroweb product) from 2002 to 2010. Additionally, the responses of the major global lake levels to climatic fluctuations are analyzed using Global Land Surface Assimilation System (GLDAS) data (temperature and precipitation). The results show that the change rates of most global lakes exceed 0, which means that the lake levels of these lakes are rising. The change rates of the lake levels are between -0.3~0.3 m/a, which indicates that the rate of change in the water-level of most lakes is not obvious. A few lakes have a particularly sharp change rate, between -5.84~-2 m/a or 0.7~1.87 m/a. Lakes with increasing levels are mainly located in the mountain and plateau regions, and the change rates in the coastal highlands are more evident. The global temperatures rise by a change rate of 0.0058 °C/a, while the global precipitation decreases by a change rate of -0.6697 mm/a. However, there are significant regional differences in both temperature and precipitation. In addition, the impact of precipitation on the water level of lakes is significant and straightforward, while the impact of temperature is more complex. A study of lake levels on a global scale would be quite useful for a better understanding of the impact which climate change has on surface water resources. [ABSTRACT FROM AUTHOR]

Interpenetrating polymer network (IPN) hydrogels were developed by engineering ionic bridges between carboxylated cellulose nanofibrils (CNFs) and amine-terminated poly(ethylene glycol) (PEG) into a covalent poly(acrylamide) architecture network, and the role of precoordinated CNF-PEG dynamic complexes in the IPN hydrogels viscoelastic dynamics was explored. The results shown that the ionic complexes significantly improved the IPN hydrogels energy dissipation and elastic recovery properties, leading to strain-rate dependent mechanics and notable enhancement in tensile toughness. The uniaxial deformation over a range of strain rates demonstrated that fracture energy peaked at 0.05 s-1 before decreased with further increasing strain rate, consistent with the crack propagation rate result. This straightforward sacrificial bonding strategy validates the hypothesis that elastomers with high toughness and excellent recovery can be achieved by incorporating precoordinated supramolecular associating motifs, which confers control over mechanical properties in a reversible, dynamic, and modular fashion. [ABSTRACT FROM AUTHOR]

As an important part of the global ecosystem, wetlands and their dynamics greatly influence regional eco-environment systems. To understand the distributions, change processes and temporal-spatial characteristics of the wetlands of the inland river basin in an arid region (Heihe River Basin, HRB), this paper employed multi-source remote sensing data to facilitate multi-temporal monitoring of the HRB wetland using a wetland information extraction method. First, we performed monitoring of these wetlands for the years 2000, 2007, 2011 and 2014; then, we analyzed the variation characteristics of the spatial-temporal dynamics of the wetlands in the HRB over the last 15 years via the landscape dynamic change model and the transformation matrix. In addition, we studied the possible driving mechanisms of these changes. The research results showed that the total area of the HRB wetlands had decreased by 2959.13 hectares in the last 15 years (Since 2000), and the annual average loss was 1.09%. The dynamics characterizing the HRB wetlands generally presented a trend of slow increase after an initial decrease, which can be classified into three stages. From 2000 to 2007, the total wetland area rapidly decreased; from 2007 to 2011, the area slowly decreased; and from 2011 to 2014, the area gradually increased. The dynamic changing processes characterizing the wetland resources were ascribed to a combination of natural processes and human activities. The main driving mechanisms of wetland dynamic changes include climatic conditions, upper reach water inflows, population, water resources, cultivated area, and policy. The findings of this study can served as reference and support for the conservation and management of wetland resources in the HRB. [ABSTRACT FROM AUTHOR]

This study presents a revised temporal scaling method based on a detection algorithm for the temporal stability of the evaporative fraction (EF) to estimate total daytime evapotranspiration (ET) at a regional scale. The study area is located in the Heihe River Basin, which is the second largest inland river basin in China. The remote sensing data and field observations used in this study were obtained from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project. The half-hourly EF values (EFEC) calculated using meteorological observations from an eddy covariance (EC) system and an automatic meteorological station (AMS) represented the diurnal pattern of the EF across the majority of the study area. The remotely sensed instantaneous midday EF (EFASTER), which indicates the spatial distribution of the midday EF over the entire study area, was calculated from an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image. The temporal stability of EFEC was examined using a detection algorithm. Intervals with inconsistent EFEC values were distinguished from those with consistent EFEC values; the total daytime ET (from 9:00 to 19:00) within these interval types was integrated separately. Validation of the total daytime ET at the satellite pixel scale was conducted using measurements from17 EC towers. Using the detection algorithm for the temporal stability of the EF and dynamic adjustment, the revised temporal scaling method resulted in a root-mean-square error (RMSE) of 0.54 (mm·d-1), a mean relative error (MRE) of 7.26% and a correlation coefficient (Corr.) of 0.81; all of these values were superior to those of the two other methods (i.e., the constant EF and variable EF methods). The revised method easily extends to other areas and exhibits a superior performance in flat and regularly-irrigated farmlands at the regional scale. [ABSTRACT FROM AUTHOR]

Validation is an essential and important step before the application of remote sensing products. This paper introduces a prototype of the validation network for remote sensing products in China (VRPC). The VRPC aims to improve remote sensing products at a regional scale in China. These improvements will enhance the applicability of the key remote sensing products in understanding and interpretation of typical land surface processes in China. The framework of the VRPC is introduced first, including its four basic components. Then, the basic selection principles of the observation sites are described, and the principles for the validation of the remote sensing products are established. The VRPC will be realized in stages. In the first stage, four stations that have improved remote sensing observation facilities have been incorporated according to the selection principles. Certain core observation sites have been constructed at these stations. Next the Heihe Station is introduced in detail as an example. The three levels of observation (the research base, pixel-scale validation sites, and regional coverage) adopted by the Heihe Station are carefully explained. The pixel-scale validation sites with nested multi-scale observation systems in this station are the most unique feature, and these sites aim to solve some key scientific problems associated with remote sensing product validation (e.g., the scale effect and scale transformation). Multi-year of in situ measurements will ensure the high accuracy and inter-annual validity of the land products, which will provide dynamic regional monitoring and simulation capabilities in China. The observation sites of the VRPC are open, with the goal of increasing cooperation and exchange with global programs. [ABSTRACT FROM AUTHOR]

The Heihe River Basin (HRB) is the second largest inland river basin in the northwestern arid and semi-arid regions of China. Recent Comprehensive Control Projects in the HRB were implemented beginning in 2001. The ecological and hydrological benefits of this effort were evaluated by analyzing the resulting changes in the vegetation cover and groundwater levels. Ten-year time series VEGETATION data were used to monitor the changes in vegetation cover in the HRB. The driving factors were analyzed for different regions with increasing or decreasing vegetation cover. Increases in mountainous precipitation and runoff resulted in increasing vegetation cover. In some regions in the middle and downstream portions of the HRB, decreases in vegetation cover exhibited a strong relationship with changes in groundwater levels. Constructive suggestions are provided for local governments based on the analysis results. [ABSTRACT FROM AUTHOR]

This study presents preliminary results of the validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) daily LST products (MOD/MYD11A1, Version 5) using longwave radiation ground measurements obtained at 12 stations in the North Arid and Semi-Arid Area Cooperative Experimental Observation Integrated Research program. In this evaluation process, the broadband emissivity at each station was obtained from the ASTER Spectral Library or estimated from the MODIS narrowband emissivity Collection 5. A comparison of the validation results based on those two methods shows that no significant differences occur in the short-term validation, and a sensitivity analysis of the broadband emissivity demonstrates that it has a limited effect on the evaluation results. In general, the results at the 12 stations indicate that the LST products have a lower accuracy in China's arid and semi-arid areas than in other areas, with a mean absolute error of 2-3 K. Compared with the temporal mismatch, the spatial mismatch has a stronger effect on the validation results in this study, and the stations with homogeneous land cover have more comparable MODIS LST accuracies. Comparisons between the stations indicate that the spatial mismatch can increase the influence of the temporal mismatch. [ABSTRACT FROM AUTHOR]

Although the research and application of a geographic information system (GIS) in bibliometrics remains in its initial stage, several valuable attempts have been made in recent years. This paper provides our overview regarding this area. We first reviewed the spatial information mining derived from literature, including structured and unstructured data. The spatial display and the basic spatial operations for the geographic information derived from literature were then introduced, demonstrating that GIS can be directly used to construct digital libraries. Some literature database websites have begun to utilize WEBGIS to display the spatial distribution of an author's location. Additionally, the spatial distribution information can be displayed in various modes with other specialized tools. Potential spatial analyses in bibliometrics were then discussed, introducing geostatistical and buffer analyses as case studies. Finally, several bibliometric indicators attached with research units were investigated. When the quantitative research index units are linked with the research spatial position, they can be displayed, queried and retrieved spatially. Future work to advance the application and research of GIS in bibliometrics is still warranted. [ABSTRACT FROM AUTHOR]

More than 20 techniques have been developed to de-noise time-series vegetation index data from different satellite sensors to reconstruct long time-series data sets. Although many studies have compared Normalized Difference Vegetation Index (NDVI) noise-reduction techniques, few studies have compared these techniques systematically and comprehensively. This study tested eight techniques for smoothing different vegetation types using different types of multi-temporal NDVI data (Advanced Very High Resolution Radiometer (AVHRR) (Global Inventory Modeling and Map Studies (GIMMS) and Pathfinder AVHRR Land (PAL), Satellite Pour l' Observation de la Terre (SPOT) VEGETATION (VGT), and Moderate Resolution Imaging Spectroradiometer (MODIS) (Terra)) with the ultimate purpose of determining the best reconstruction technique for each type of vegetation captured with four satellite sensors. These techniques include the modified best index slope extraction (M-BISE) technique, the Savitzky-Golay (S-G) technique, the mean value iteration filter (MVI) technique, the asymmetric Gaussian (A-G) technique, the double logistic (D-L) technique, the changing-weight filter (CW) technique, the interpolation for data reconstruction (IDR) technique, and the Whittaker smoother (WS) technique. These techniques were evaluated by calculating the root mean square error (RMSE), the Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC). The results indicate that the S-G, CW, and WS techniques perform better than the other tested techniques, while the IDR, M-BISE, and MVI techniques performed worse than the other techniques. The best de-noise technique varies with different vegetation types and NDVI data sources. The S-G performs best in most situations. In addition, the CW and WS are effective techniques that were exceeded only by the S-G technique. The assessment results are consistent in terms of the three evaluation indexes for GIMMS, PAL, and SPOT data in the study area, but not for the MODIS data. The study will be very helpful for choosing reconstruction techniques for long time-series data sets. [ABSTRACT FROM AUTHOR]

Cited information is an important pathway of scientific influence. It can reflect the knowledge flows among research units. This study develops two new bibliometric indices—the Citation Flow Index (CFI) and the Normalized Citation Flow Index (NCFI)—to measure knowledge flows based on scientific literature citations. The CFI measures the interactions of knowledge flows among different research units. The NCFI measures the number of papers that a research unit cited and the number of papers by a research unit that are cited. The newly developed indices were tested on a country-wide scale using the literature on the Qinghai-Tibet Plateau (QTP) as an example. The results indicate that the worldwide flow of knowledge on the QTP can be quantitatively measured and spatially displayed. Additionally, the annual NCFI change trend is analyzed for each research unit. [ABSTRACT FROM AUTHOR]

This paper aims to retrieve temporal high-resolution LAI derived by fusing MOD15 products (1 km resolution), field-measured LAI and ASTER reflectance (15-m resolution). Though the inversion of a physically based canopy reflectance model using high-resolution satellite data can produce high-resolution LAI products, the obstacle to producing temporal products is obvious due to the low temporal resolution of high resolution satellite data. A feasible method is to combine different source data, taking advantage of the spatial and temporal resolution of different sensors. In this paper, a high-resolution LAI retrieval method was implemented using a dynamic Bayesian network (DBN) inversion framework. MODIS LAI data with higher temporal resolution were used to fit the temporal background information, which is then updated by new, higher resolution data, herein ASTER data. The interactions between the different resolution data were analyzed from a Bayesian perspective. The proposed method was evaluated using a dataset collected in the HiWater (Heihe Watershed Allied Telemetry Experimental Research) experiment. The determination coefficient and RMSE between the estimated and measured LAI are 0.80 and 0.43, respectively. The research results suggest that even though the coarse-resolution background information differs from the high-resolution satellite observations, a satisfactory estimation result for the temporal high-resolution LAI can be produced using the accumulated information from both the new observations and background information. [ABSTRACT FROM AUTHOR]

Karst trough valleys are prone to flooding, primarily because of the unique hydrogeological features of karst landform, which are conducive to the spread of rapid runoff. Hydrological models that represent the complicated hydrological processes in karst regions are effective for predicting karst flooding, but their application has been hampered by their complex model structures and associated parameter set, especially so for distributed hydrological models, which require large amounts of hydrogeological data. Distributed hydrological models for predicting the Karst flooding is highly dependent on distributed structrues modeling, complicated boundary parameters setting, and tremendous hydrogeological data processing that is both time and computational power consuming. Proposed here is a distributed physically-based karst hydrological model, known as the QMG (Qingmuguan) model. The structural design of this model is relatively simple, and it is generally divided into surface and underground double-layered structures. The parameters that represent the structural functions of each layer have clear physical meanings, and the parameters are less than those of the current distributed models. This allows modeling in karst areas with only a small amount of necessary hydrogeological data. 18 flood processes across the karst underground river in the Qingmuguan karst trough valley are simulated by the QMG model, and the simulated values agree well with observations, for which the average value of Nash-Sutcliffe coefficient was 0.92. A sensitivity analysis shows that the infiltration coefficient, permeability coefficient, and rock porosity are the parameters that require the most attention in model calibration and optimization. The improved predictability of karst flooding by the proposed QMG model promotes a better mechanistic depicting of runoff generation and confluence in karst trough valleys. [ABSTRACT FROM AUTHOR]

The alpine region is important in riverine and watershed ecosystems as a contributor of freshwater, providing and stimulating specific habitats for biodiversity. In parallel, recent climate change, human activities and other perturbations may disturb hydrological processes and eco-functions, creating the need for next-generation observational and modeling approaches to advance a predictive understanding of such processes in the alpine region. However, several formidable challenges, including the cold and harsh climate, high altitude and complex topography, inhibit complete and consistent data collection where/when needed, which hinders the development of remote sensing technologies and alpine hydrological models. The current study presents a suite of datasets consisting of long-term hydrometeorological, snow cover and frozen ground data for investigating watershed science and functions from an integrated, distributed and multiscale observation network in the upper reaches of the Heihe River Basin (HRB) in China. Gap-free meteorological and hydrological data were monitored from an observation network connecting a group of automatic meteorological stations (AMSs). In addition, to capture snow accumulation and ablation processes, snow cover properties were collected from a snow observation superstation using state-of-the-art techniques and instruments. High-resolution soil physics datasets were also obtained to capture the freeze-thaw processes from a frozen ground observation superstation. The updated datasets were released to scientists with multidisciplinary backgrounds (i.e., cryosphere science, hydrology, and meteorology), and they are expected to serve as a testing platform to provide accurate forcing data and validate and evaluate remote sensing products and hydrological models for a broader community. The datasets are available from the Cold and Arid Regions Science Data Center at Lanzhou https://doi.org/10.3972/hiwater.001.2019.db. [ABSTRACT FROM AUTHOR]

Validation is mandatory to quantify the reliability of remote sensing products (RSPs). However, this process is not straightforward and usually presents formidable challenges in terms of both theory and real-world operations. In this context, a dedicated validation initiative was launched in China, and we identified a validation strategy (VS). This overall VS focuses on validating regional-scale RSPs with a systematic site-to-network concept, consisting of four main components: (1) general guidelines and technical specifications to guide users in validating various land RSPs, particularly aiming to further develop in situ sampling schemes and scaling approaches to acquire ground truth at the pixel scale over heterogeneous surfaces; (2) sound site-based validation activities, conducted through multi-scale, multi-platform, and multi-source observations to experimentally examine and improve the first component; (3) a national validation network to allow for comprehensive assessment of RSPs from site or regional scales to the national scale across various zones; and (4) an operational RSP evaluation system to implement operational validation applications. Research progress on the development of these four components is described in this paper. Some representative research results, with respect to the development of sampling methods and site-based validation activities, are also highlighted. The development of this VS improves our understanding of validation issues, especially to facilitate validating RSPs over heterogeneous land surfaces both at the pixel scale level and the product level. [ABSTRACT FROM AUTHOR]

The fabrication of reusable and biodegradation materials from renewable resources such as cellulose is essential for a sustainable world. The core-shell structured CdS-decorated TiO2/Carbon microspheres (CdS/TiO2/Carbon MS) photocatalyst was synthesized with controlled hydrolysis and a novel sonochemical method. It was prepared by using crosslinked microcrystalline cellulose as the core, tetrabutyl titanate as the titania source and CdS as the photosensitizer. The morphology, chemical structure and properties of the obtained material were characterized by many means. Additionally, the photocatalytic activity of the CdS/TiO2/Carbon MS was evaluated by the photodegradation efficiency of Rhodamine B solution, which reached 95.24% under visible light irradiation. This study demonstrated the excellent photocatalytic performance of CdS/TiO2/Carbon MS, which might have promising applications in environmental treatments. [ABSTRACT FROM AUTHOR]

An accurate estimation of carbon fluxes is very important in carbon cycle studies. A remote sensing based gross primary production (GPP) and net ecosystem production (NEP) algorithm, RS-CFLUX, was presented in this work. The algorithm was calibrated with Markov Chain Monte Carlo (MCMC) method at Daman superstation and Zhangye wetland station in the midstream of the Heihe River Basin. Results indicated that both of the stations present high GPP (1442.04 g C/m2/year at Daman superstation and 928.89 g C/m2/year at Zhangye wetland station) and NEP (409.38 g C/m2/year at Daman superstation and 422.60 g C/m2/year at Zhangye wetland station). The RS-CFLUX model can correctly simulate the seasonal dynamics and quantities of carbon fluxes at both stations, using photosynthetically active radiation (PAR), land surface temperature (LST), normalized difference water index (NDWI) and enhanced vegetation index (EVI) as input. RS-CFLUX model were sensitive to maximum light use efficiency, respiration at reference temperature, activation energy parameter of respiration. [ABSTRACT FROM AUTHOR]

A major research plan entitled "Integrated research on the eco-hydrological process of the Heihe River Basin" was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of inter-disciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated eco-hydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses. [ABSTRACT FROM AUTHOR]

As an alternative to TiO2 photocatalysts, ZnO exhibits a large potential for photocatalytic (PC) applications in environmental treatments, such as degradation of wastewater, sterilization of drinking water, and air cleaning. However, the efficiency achieved with ZnO to date is far from that expected for commercialization, due to rapid charge recombination, photo-corrosion as well as poor utilization of solar energy. Fortunately, in recent years, a great number of breakthroughs have been achieved in PC performance (including activity and stability) of micro-/nano- structured ZnO by forming heterojunctions (HJs) with metal nanoparticles (NPs), carbon nanostructures and other semiconductors. In most cases, the improvement of PC performance was ascribed to the better charge separation at the interfaces between ZnO and the other components. Sometimes, the formation of hybrids is also in favor of visible light harvesting. This review summarizes recent advances in the fields of environmental photocatalysis by ZnO based HJs, and especially emphasizes their abilities in degradation of organic pollutants or harmful substances in water. We aim to reveal the mechanism underlying the enhanced PC performance by constructing HJs, and extend the potential of ZnO HJ photocatalysts for future trends, and practical, large-scale applications in environment-related fields. [ABSTRACT FROM AUTHOR]