Estimations of Net Primary Productivity and Evapotranspiration Based on HJ-1A/B Data in Jinggangshan City, China

Net primary productivity(NPP) and evapotranspiration(ET) are two key variables in the carbon and water cycles of terrestrial ecosystems.In this study,to test a newly developed NPP algorithm designed for HJ-1 A/B data and to evaluate the usage of HJ-1 A/B data in the quantitative assessment of environments,NPP and ET in Jinggangshan city,Jiangxi province,are calculated using HJ-1 A/B data.The results illustrate the following:(1) The NPP and ET in Jinggangshan city in 2010 both show obvious seasonal variation,with the highest values in summer and the lowest values in winter,and relatively higher values were observed in autumn than in spring.(2) The spatial pattern indicates that the annual NPP is high in the southern area in Jinggangshan city and low in the northern area.Additionally,high NPP is distributed in forests located in areas with high elevation,and low NPP is found in croplands at low elevations.ET has no significant north-south difference,with high values in the southeast and northwest and low values in the southwest,and high ET is distributed in forests at low elevations in contrast to low ET in forests in high-elevation areas and in cropland and shrub grassland in low-elevation areas.(3) Compared to the MODIS product,the range of HJ-1 NPP is larger,and the spatial pattern is more coincident with the topography.The range of HJ-1 ET is smaller than that of the MODIS product,and ET is underestimated to some extent but can reflect the effect of topography.This study suggests that the algorithm can be used to estimate NPP and ET in a subtropical monsoon climate if remotely sensed images with high spatial resolution are available.

Integrating a model with remote sensing observations by a data assimilation approach to improve the model simulation accuracy of carbon flux and evapotranspiration at two flux sites

Model simulation and in situ observations are often used to research water and carbon cycles in terrestrial ecosystems, but each of these methods has its own advantages and limitations. Combining these two methods could improve the accuracy of quantifying the dynamics of the water and carbon fluxes of an ecosystem. Data assimilation is an effective means of integrating modeling with in situ observation. In this study, the ensemble Kalman filter(En KF) and the unscented Kalman filter(UKF) algorithms were used to assimilate remotely sensed leaf area index(LAI) data with the Biome-BGC model to simulate water and carbon fluxes at the Harvard Forest Environmental Monitoring Site(EMS) and the Dinghushan site. After MODIS LAI data from 2000–2004 were assimilated into the improved Biome-BGC model using the En KF algorithm at the Harvard Forest site, the R2 between the simulated and observed results for NEE and evapotranspiration increased by 7.8% and 4.7%, respectively. In addition, the sum of the absolute error(SAE) and the root mean square error(RMSE) of NEE decreased by an average of 21.9% and 26.3%, and the SAE and RMSE of evapotranspiration decreased by 24.5% and 25.5%, respectively. MODIS LAI data of 2003 were assimilated into the Biome-BGC model for the Dinghushan site, and the R2 values between the simulated and observed results for NEE and evapotranspiration were increased by 6.7% and 17.3%, respectively. In addition, the SAE values of NEE and ET were decreased by 11.3% and 30.7%, respectively, and the RMSE values of NEE and ET decreased by 10.1% and 30.9%, respectively. These results demonstrate that the accuracy of carbon and water flux simulations can be effectively improved when remotely sensed LAI data are properly integrated with ecosystem models through a data assimilation approach.

Evapotranspiration Estimation and Influence on Water Change in the Weihe River Basin,China

As the largest sub-basin of the middle reaches of the Yellow River with an obvious decreasing trend in annual runoff in recent years,the Weihe River basin is a significant region with regard to the protection and improvement of the environment in West China.Evapotranspiration(ET)is the loss of water from the Earth’s surface to the atmosphere and plays an important role in the regional water cycle,especially when considering water resource shortages.In this study,through analyzing the grid precipitation data after interpolation from 39 meteorological stations in and around the Weihe River basin from 1981 to 2011,certain periods during 1987,1993,1999,2001,2002 and 2009 with similar precipitation characteristics had been chosen for estimating the ET in the Weihe River basin.To illustrate ET’s influence on the water budget,these estimations are calculated based on an improved Penman-Monteith equation as well as remote sensing data and meteorological data.The results show that:(1)the annual ET in the Weihe River basin ranged from 350mm to 400mm in 1987,1993,1999,2001,2002 and 2009,accounting for more than 70%of the corresponding annual precipitation.There is a definite increasing trend in different decades that is primarily distributed during the summer.(2)The spatial distribution patterns of the ET in the six years mentioned area unique set,and the years are roughly identical with more than 500mm in the middle and lower reaches of the Weihe River in the southeastern region and less than 400mm in upper reaches of the Jinghe River in the northwestern area.(3)At the single-point scale,the coefficient of determination(R2)is 0.618 compared to the eddy correlation measurements in 2009 at the Changwu site,showing good agreement between the estimated ET and the observed ET.At the basin scale,the model-estimated ET is slightly lower than the actual ET with regard to the surface water budget.Additionally,the estimated ET in 2001,2002 and 2009 is close to the MODIS ET product.(4)For similar precipitation conditions,the regional amount of water shows a decreasing tendency with increasing ET,which may result from the rise in NDVI and improvements in vegetation coverage caused by human activities.This research suggests the influence of ET on water change at the basin level,which can also explain the decreasing runoff and can provide necessary information for improved water resource management.

Analysis of spatial distribution and multi-year trend of the remotely sensed soil moisture on the Tibetan Plateau

Long-term highly accurate surface soil moisture data of TP(Tibetan Plateau)are important to the research of Asian monsoon and global atmospheric circulation.However,due to the sparse in-situ networks,the lack of soil moisture observations has seriously hindered the progress of climate change researches of TP.Based on the Dual-Channel soil moisture retrieval algorithm and the satellite observation data of AMSR-E(Advanced Microwave Scanning Radiometer for EOS),we have produced the surface soil moisture data of TP from 2003 to 2010 and analyzed the seasonal characteristic of the soil moisture spatial distribution and its multi-year changing trend in area of TP.Compared to the in-situ observations,the accuracy of the soil moisture retrieved by the proposed algorithm is evaluated.The evaluation result shows that the new soil moisture product has a better accuracy in the TP region than the official product of AMSR-E.The spatial distribution of the annual mean values of soil moisture and the seasonal variations of the monthly-averaged soil moisture are analyzed.The results show that the soil moisture variations in space and time are consistent with the precipitation distribution and the water vapor transmission path in TP.Based on the new soil moisture product,we also analyzed the spatial distribution of the changing trend of multi-year soil moisture in TP.From the comparisons with the precipitation changing trend obtained from the meteorological observation sites in TP,we found that the spatial pattern of the changing trend of soil moisture coincides with the precipitation as a whole.

Effects of spatial distribution of soil parameters on soil moisture retrieval from passive microwave remote sensing

In this paper,we studied the effect of spatial distribution of soil parameters on passive soil moisture retrieval at pixel scale.First,we evaluated the forward microwave emission model and soil moisture retrieval algorithm accuracy through the observa-tion of field experiments.Then,we used soil parameters in different spatial distribution patterns,including random,normal,and uniform distribution,to determine the different levels of heterogeneity on soil moisture retrieval,in order to seek the rela-tionship between heterogeneity and soil moisture retrieval error.Finally,we conducted a controlled heterogeneity effect ex-periment measurements using a Truck-mounted Multi-frequency Radiometer(TMMR) to validate our simulation results.This work has proved that the soil moisture retrieval algorithm had a high accuracy(RMSE=0.049 cm3 cm 3) and can satisfy the need of this research.The simulation brightness temperatures match well with observations,with RMSE=9.89 K.At passive microwave remote sensing pixel scale,soil parameters with different spatial distribution patterns could have different levels of error on soil moisture estimation.Overall,we found that soil moisture with a random distribution in a satellite pixel scale can cause the largest error,with a normal distribution being the second,and a uniform distribution the least due to the smallest het-erogeneity.

Re-understanding of land surface albedo and related terms in satellite-based retrievals

Land surface albedo is a critical variable in determining surface energy balance,and regulating climate and ecosystem processes through feedback mechanisms.Therefore,climatic modelers and radiative monitoring require accurate estimates of land surface albedo.With the instrument development,algorithm upgrade,spectral-band-adjustment in wavelength center or band width,and the increasing distinct requirement from diversified communities,various albedo terms have been generated in related satellite-based products.The lack of understanding on the divergence of these terminologies can introduce potential considerable errors in the subsequent applications,or an elevated probability to invert the deduced conclusion.We surveyed the basic concepts of reflectance quantities,retrieval strategies,and models developed since the 1970s,and discuss both strength and opportunity for improvements on land surface albedo extraction,and product generation.In addition,we exemplified the difference of albedo terms using the daily MODIS product(MCD43A)to emphasize the potential risk of the ambiguous usage,over typical IGBP land covers in Northern Kazakhstan.Our investigation shows that relative differences among various albedo terms can reach up to 181%and 50%,while 0.266 and 0.118 of absolute variance respectively in the narrow and broad-band surface albedo,which illuminated cautions against the ambiguous understanding of albedo terminologies or erroneous usage of albedo products.

Using eye tracking to evaluate the usability of animated maps

Cartographic animation has been developed and widely used in geo-visualisation and many other areas in recent years.The usability of animated maps is a key characteristic affecting map users’effectiveness and efficiency in accomplishing tasks.In this paper,an eye tracking approach was proposed as a visual analytics method to evaluate the usability of animated maps by capturing participants’eye movement data and quantitatively analysing the accuracy(effectiveness)and response time(efficiency)of users’task completion.In the study,a set of animated traffic maps represented by three important visual variables(colour hue,size and frequency)was used for the usability evaluation.The experimental results showed that the usability of these three visual variables for cartographic animation affects the usability of animated maps.Red,yellow,and aqua were found to convey map information more effectively than other colour hues.Size was found to be more usable than colour hues for both animated maps and static maps.Usability was not found to be proportional to the playback rate of animated maps.Furthermore,the usability of the frequency,colour hue,and size was found to be related to the display’s size.We hope that the analysis approach presented in this paper and the results of this study will be of help in the design of cartographic animation displays with better usability.

Study on the spectral response of Brassica Campestris L. leaf to the copper pollution

Brassica Campestis L. was cultivated in the soil at the laboratory. The red edge,the visual spectrum and the near-infrared spectrum of Brassica Campestis L. leaf were used to explore the spectral response of Brassica Campestis L. leaf to the copper stress. As the Cu content in the soil gets increased,the copper level in Brassica Campestris L. leaf would be increased,and the chlorophyll level in Brassica Campestris L. leaf would be decreased. As a result,the visual spectral reflectance (A1) of Brassica Campestris L. leaf is increased,and the blue-shift (moving towards the shorter waveband) degree (S) of the red edge (the ascending region of the re-flectivity at 680―740 nm) gets increased. However,the near-infrared spectral re-flectance (A2) decreases. With the correlation coefficient R2 more than 0.95,these parameters of A1,A2 and S can be perfectly used to simulate and predict the copper level in Brassica Campestris L. leaf.

Drought Risk Assessment of China’s Mid-Season Paddy

China has the world’s largest population and a large and critically important agricultural sector. Sixty-five percent of the Chinese population lives on paddy rice. However, drought disasters frequently afflict China’s rural population and threate n its food security. It is therefore of paramount importance to assess the drought risk of paddy in China. We establish a quantitative risk assessment model for the drought risk of mid-season paddy and regional-specific vulnerability curves, evaluate the drought risk of mid-season paddy, and compile a series of risk maps. The drought disaster risk rating results indicate that risk is highest in Northeast China, followed by Northwest China, North China, and South China, showing a decreasing trend from north to south. The mid-season paddy area of Northeast China has the highest mean risk index(0.58–0.71), followed by northwestern provinces such as Inner Mongolia and Xinjiang(0.5–0.6), while risk indices in provinces of North China such as Hebei and Shandong range from 0.3–0.5, and the southern provinces show a relatively low level of risk. This article presents the preliminary results of a scientific inquiry on where the high drought risk areas of mid-season paddy are and how high the risk is. These results provide a regional-specific basis for drought risk governance of paddy in China.

Comprehensive assessment for removing multiple pollutants by plants in bioretention systems

Bioretention is a best management practice which uses vegetation to improve the pollutant removal rates in the rain water management.To select the best plant species to remove multiple pollutants in a bioretention system,we tested thirty species of plants in a laboratory in Beijing,China.We found that the ability of the plants to reduce concentrations of heavy metals including cadmium(Cd),lead(Pb),zinc(Zn),and ammonium(NH4?–N)is more than90%.The removal efficiencies for NH4?–N,nitrate(NO3-–N),total phosphorus,and copper(Cu)varied markedly among plant species.The single overall best plant was not easy to be determined.To select the best plant species,we used a dynamic neural network to establish an assessment index system,assessment criteria,and an assessment model that is used here for the first time for multiple pollutants’removal.Applying the theory and model,we discovered that Plantago asiatica L.and Digitaria sanguinalis(L.)Scop.are the overall best plants for removing the seven typicalpollutants.This paper will provide a simple and useful guide for the comprehensive assessment of multiple pollutant removal by plants in complex ecological systems.