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| 1 | Crop area and leaf area index simultaneous retrieval based on spatial scaling transformation显示文摘Accurate estimation of crop yields is crucial for ensuring food security. However, crops are distributed so fragmentally in China that mixed pixels account for a large proportion in moderate and coarse resolution remote sensing images. As a result, unmixing of mixed pixel becomes a major problem to estimate crop yield by means of remote sensing method. Aimed at mixed pixels, we developed a new method to introduce additional information contained in the spatial scaling transformation equation to the canopy reflectance model. The crop area and LAI can be retrieved simultaneously. On the basis of a precise and simple canopy reflectance model, directional second derivative method was chosen to retrieve LAI from optimal bands of hyper-spectral data; this method can reduce the impact of the canopy non-isotropic features and soil background. To evaluate the performance of the method, Yingke Oasis, Zhangye City, Gansu Province, was chosen as the validation area. This area was covered mainly by maize and wheat. A Hyperion/EO-1 image with the 30 m spatial resolution was acquired on July 15, 2008. Images of 180 m and 1080 m resolutions were generated by linearly interpolating the original Hyperion image to coarser resolutions. Then a multi-scale image serial was obtained. Using the proposed method, we calculated crop area and the average LAI of every 1080 m pixel. A SPOT-5 classification figure serves as the validation data of crop area proportion. Results show that the pattern of crop distribution accords with the classification figure. The errors are restrained mainly to -0.1-0.1, and approximate a Normal Distribution. Meanwhile, 85 LAI values obtained using LAI-2000 Plant Canopy Analyzer, equipped with GPS, were taken as the ground reference. Results show that the standard deviation of the errors is 0.340. The method proposed in the paper is reliable. | Fan WenJie Yan BinYan Xu XiRu | 2010 | Science China Earth Sciences2010，53，11： | 6 |
| 2 | Evaluating Common Land Model Energy Fluxes Using FLUXNET Data显示文摘Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model(Co LM) over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise(30 min) to monthly. A comparison between the simulations and observations indicated that Co LM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes. A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas Co LM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. Co LM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why Co LM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, Co LM performs best for evergreen broadleaf forests and worst for croplands and wetlands. | Xiangxiang ZHANG Yongjiu DAI Hongzhi CUI Robert E.DICKINSON Siguang ZHU Nan WEI Binyan YAN Hua YUAN Wei SHANGGUAN Lili WANG Wenting FU | 2017 | Advances in Atmospheric Sciences2017，34，9： | 4 |
| 3 | The spatial scaling effect of the discrete-canopy effective leaf area index retrieved by remote sensing显示文摘The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery. | FAN WenJie GAI YingYing XU XiRu YAN BinYan | 2013 | Science China Earth Sciences2013，56，9： | 4 |
| 4 | A unified canopy bidirectional reflectance (BRDF) model for row ceops显示文摘Row sowing is a basic crop sowing method in China,and thus an accurate Bidirectional Reflectance Distribution Function (BRDF) model of row crops is the foundation for describing the canopy bidirectional reflectance characteristics and estimating crop ecological parameters.Because of the macroscopically geometric difference,the row crop is usually regarded as a transition between continuous and discrete vegetation in previous studies.Were row treated as the unit for calculating the four components in the Geometric Optical model (GO model),the formula would be too complex and difficult to retrieve.This study focuses on the microscopic structure of row crops.Regarding the row crop as a result of leaves clumped at canopy scale,we apply clumping index to link continuous vegetation and row crops.Meanwhile,the formula of clumping index is deduced theoretically.Then taking leaf as the basic unit,we calculate the four components of the GO model and develop a BRDF model for continuous vegetation,which is gradually extended to the unified BRDF model for row crops.It is of great importance to introduce clumping index into BRDF model.In order to evaluate the performance of the unified BRDF model,the canopy BRDF data collected in field experiment,'Watershed Allied Telemetry Experiment Research (WATER)',from May 30th to July 1st,2008 are used as the validation dataset for the simulated values.The results show that the unified model proposed in this paper is able to accurately describe the non-isotropic characteristics of canopy reflectance for row crops.In addition,the model is simple and easy to retrieve.In general,there is no irreconcilable conflict between continuous and discrete vegetation,so understanding their common and individual characteristics is advantageous for simulating canopy BRDF.It is proven that the four components of the GO model is the basic motivational factor for bidirectional reflectance of all vegetation types. | YAN BinYan XU XiRu FAN WenJie | 2012 | Science China Earth Sciences2012，55，5： | 3 |
| 5 | The receptor-like cytosolic kinase RIPK activates NADP-malic enzyme 2 to generate NADPH for fueling ROS production显示文摘Reactive oxygen species(ROS)production is a conserved immune response in Arabidopsis primarily medi-ated by respiratory burst oxidase homolog D(RBOHD),a nicotinamide adenine dinucleotide phosphate(NADPH)oxidase associated with the plasma membrane.A rapid increase in NADPH is necessary to fuel RBOHD proteins and thus maintain ROS production.However,the molecular mechanism by which NADPH is generated to fuel RBOHD remains unclear.In this study,we isolated a new mutant allele of FLAGELLIN-INSENSITIVE 4(FIN4),which encodes the first enzyme in de novo NAD biosynthesis.fin4 mu-tants show reduced NADPH levels and impaired ROS production.However,FIN4 and other genes involved in NAD-and NADPH-generating pathways are not highly upregulated upon elicitor treatment,raising a pos-sibility that a cytosolic NADP-linked dehydrogenase might be post-transcriptionally activated to maintain the NADPH supply close to RBOHD.To verify this possibility,we isolated the proteins associated with RPM1-INDUCED PROTEIN KINASE(RIPK),a receptor-like cytoplasmic kinase that regulates broad-spectrum ROS signaling in plant immunity,and identified NADP-malic enzyme 2(NADP-ME2),an NADPH-generating enzyme.Compared with wild-type plants,nadp-me2 mutants display decreased NADP-ME activity,lower NADPH levels,and reduced ROS production in response to immune elicitors.Furthermore,we found that RIPK can directly phosphorylate NADP-ME2 and enhance its activity in vitro.The phosphorylation of the NADP-ME2 S371 residue contributes to ROS production upon immune elicitor treatment and susceptibility to the necrotrophic bacterium Pectobacterium carotovorum.Collectively,our study suggests that RIPK phosphorylates and activates NADP-ME2 to rapidly increase cytosolic NADPH,thus fueling RBOHD to sustain ROS production in plant immunity. | Binyan Wu Ping Li Xiufang Hong Cuihong Xu Ran Wang Yan Liang | 2022 | Molecular Plant2022，15，5： | 2 |
| 6 | Validation methods of LAI products on the basis of scaling effect显示文摘Validation is one of the most important processes used to evaluate whether remotely sensed products can accurately reflect land surface configuration. Leaf Area Index( LAI) is a key parameter that represents vegetation canopy structures and growth conditions. Accurate evaluation of LAI products is the basis for applying them to land surface models. In this study,validation methods of coarse resolution MODIS and GLASS LAI products for heterogeneous pixels are established on the basis of the scaling effect and the scaling transformation. Considering spatial heterogeneity and growth difference,we transformed LAI from field measurements into a 1 km resolution scale with the aid of middle resolution images. We used average LAI and apparent LAI separately to validate the algorithms and products of MODIS and GLASS LAI. Two study areas,Hebi City and the Yingke Oasis,were selected for validation. Both MODIS and GLASS LAI products underestimate the true LAI in crop area. However,this result cannot be completely attributed to their algorithms. Instead,the primary reason is the heterogeneity and nonuniformity of the coarse pixels.Underestimation is evident in the Yingke Oasis,where heterogeneity is significant. Given that GLASS LAI product is the fusion of multiple LAI products,the mean value of this product is closer to the real situation,but the dynamic range is narrower than that of MODIS LAI product. | LIAO Yanran GAI Yingying YAO Yanjuan FAN Wenjie XU Xiru YAN Binyan | 2015 | 遥感学报2015，19，1： | 2 |
| 7 | Global water cycle and remote sensing big data: overview, challenge, and opportunities显示文摘The Earth’s water cycle involves energy exchange and mass move-ment in the hydrosphere and thus sustains the dynamic balance of global hydrologic cycle.All water cycle variables on the Earth are closely interconnected with each other through the process of energy and water circulation.Observing,understanding and predict-ing the storage,movement,and quality of water remains a grand challenge for contemporary water science and technology,especially for researches across different spatio-temporal scales.The remote sensing observing platform has a unique advantage in acquiring complex water information and has already greatly improved obser-ving,understanding,and predicting ability of the water cycle.Methods of obtaining comprehensive water cycle data are also expanded by new remote sensing techniques,and the vast amount of data has become increasingly available and thus accelerated a new Era:the Remote Sensing Big Data Study of Global Water Cycle.The element inversion,time and space reconstruction,and scale conver-sion are three key scientific issues for remote sensing water cycle in suchEra.Moreover,it also presents a huge opportunity of capitalizing the combinations of Remote Sensing and Big Data to advance and improve the global hydrology and water security research and devel-opment,and uncork the new bottlenecks. | Yaokui Cui Xi Chen Jinyu Gao Binyan Yan Guoqiang Tang Yang Hong | 2018 | Big Earth Data2018，2，3： | 0 |
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