Different application conditions applied for different models used in satellite-based terrestrial latent heat estimation. Therefore, great uncertainties exist in large-scale application of such methods. BMA fusion algorithm, which has combined three commonly used models (including Penman Monteith LE algorithm, Priestly-Taylor LE algorithm and Semi-empirical Penman LE algorithm), is then carried out in this study. It can effectively reduce the uncertainty and improve the accuracy of terrestrial latent heat estimation comparing with single algorithm itself after testing with 190 eddy covariance tower site data (Fluxnet site data). The error of mean square root (RMSE) has decreased by 5W/m 2 and the value of average correlation coefficient (R 2 ) has increased by 0.05 for most of observation points in this test. The fusion model has applied in China to carry out a monthly-based latent heat estimation and mapping for data achieved from 1989 to 2006. The estimation result, after analyzed quantitatively, returns sound precision and stability, which can make up the shortage of current latent heat products. Meanwhile, the spatial distribution analysis shows that: latent heat spatial distribution is the combined contribution of temperature, precipitation and vegetation together. The temporal distribution of latent heat has obvious seasonal characteristic, which is low in winter and high in summer. The latent heat value is declined by 0.07 W/m 2 per year for past 18 years.
This work was to give an identification mode of ChemicaL Oxygen Demand (COD) within water body using remotely sensing technique. For this purpose the field data, including the spectral data of water body and the concentration of COD within water ,were collected at Huanjiang river, Rouyuan river and Malian river in Qingyang city , Gansu province of China on 6–7 April and 13–15 October,2006. The 90% samples were employed to establish the identification mode of COD according to Fisher multiclass discriminant rule. By the actual status and the national standard, the concentration of COD were classed three levels. The field spectral data were processed as corresponding bands of Landsat/ TM.. The accuracy reaches 83% with the validation of the rest 10% samples. Further, the model was applied to the two Landsat/ TM images captured on Oct. 16, 2005 and Apr. 10, 2006 in order to obtain the distributing image of COD in the rivers. By mean of the image the temporal change and spatial distribute of the concentration of COD within the three rivers were analyzed. The result shows that the establishment of identification mode based on remotely sensing provides an effective means to obtain rapidly and low-cost the concentration of COD in water environment.
DBMS (data base management system) plays an important role in administrating remote sensing data, and a lot of work has done. Today, building a spectrum database becomes easy through DBMS. Then, in Web-based spectrum database, how to access and display the data turns into the issue. A new way of Web-based model simulation is addressed in this paper. It provides three ways as parameters input, parameters filling in through Web, parameters upload from local and parameters extracting from the database. It also makes it easy to execute the model and to view the simulated results. A Web service is an interface that describes a collection of operations that are network accessible through standardized XML messaging. Based on Web services, we can integrate our model simulation with partners and clients in a fashion that is loosely coupled, simple, and platform independent.
In accordance with the data which were experiment of mixing-ratio in water tank and collecting water samples in situ from natural seawater and urban sewage discharged into the sea along Dalian coast of the northern Yellow Sea in February and April 2012, with quinine sulfate and sodium humate as a reference, the calibration curve was established among CDOM (Chromophoric dissolved organic matter) concentration and fluorescence intensity and reference wave absorption coefficient. To calibration curve as the foundation, the CDOM samples concentration of various sources was determined after analyzing CDOM sample from Dalian coast of the northern Yellow Sea sewage into the sea and natural sea. Based on the comparative analysis on CDOM fluorescence fingerprint, the main component of water CDOM were determined. The results showed that in Dalian coastal waters of the northern Yellow Sea, the main component of CDOM in natural seawater is tryptophan and in urban sewage discharged into the sea are tryptophan, tyrosine, and humic acid. On the basis of comprehensive analysis of CDOM fluorescence and absorption spectral, the thinking of synergy inversion of CDOM absorption spectral slope S by connecting fluorescence and ocean color remote sensing is put forward.
An experimental study was carried out in order to prove the feasibility of monitoring petroluem-polluted waters with remote sensing technology. The field data was collected in the rivers threatened by petroleum pollution. The measured items mainly included (1) the absorption coefficients of yellow substance, de-pigmented particles and phytoplankton pigments; (2) the backscattering coefficients data of water; (3) water quality parameters; (4) in-situ fine water spectral data. First, absorption spectral features and backscattering coefficients of petroleum-polluted water were analyzed. Secondly, the field spectral data were processed as corresponding bands of ENVISAT/MERIS using the spectral respond function of ENVISAT/MERIS in order to probe into the contribution of the various constituent concentrations in waters on the leaving-water radiation and remote sensing reflectance. The results showed that (1) with the increase of the petroleum pollution concentration, the absorption coefficients of petroleum-polluted water are also increased; (2) the spectra slope of exponential function of petroleum-polluted water is larger than that of petroleum-unpolluted water; (3) Emulsificated oil and decomposed oil in water can be absorbed by suspended particles and influence the scattering properties of the particles. Moreover it will change the spectral model of the inorganic particles backscattering coefficient with petroleum-polluted water; (4) the correlation between petroleum pollution concentration and remote sensing reflectance based on ENVISAT/MERIS is negative. These features of inherent optical parameters and apparent optical parameters obtained from the experiment provide the feasibility for monitoring petroleum-polluted waters with remote sensing technology.
Effectively monitoring the real-time position and status of oil facilities (mainly well-site) in oil field is very important for the safety production. Considering the low efficiency of traditional visual interpretation method and the high demands of preset feature for machine learning method, one of the object detection methods in Deep learning (YOLOv2) was introduced to recognize oil industry facilities automatically. After establishing the dataset of oil facility samples, 90 percent of samples are used for model training while 10 percent are for validating. Comparing with the results extracted by machine learning (Adaboost model based on Haar-like), YOLOv2 recognition results of oil facilities indicated that: Deep learning improve the recognition efficiency and accuracy of oil facilities. The accuracy can be as high as 92% while the error rate and omission rate can be maintained in a low level. At the same time, the constructed model was applied in an oilfield in eastern part of China, and the result shows that the model can identify most of the oilfield facilities correctly with only 4% omission rate, which is much lower comparing with manual interpretation. However, the 11% error rate, caused by insufficient sample types and sample quantities, is relatively high especially in city area.
It becomes difficult to study the remote sensing quantificationally in the domain of geology and geography nowadays.As one of the important contents in studying the interaction between the land surface and the atmosphere,the determination and retrieval of the surface temperature and the surface net radiation fluxes will be directly impacted by the downward atmospheric radiation in terms of the precision of the retrieval.In this paper a new model describes the retrieval of the downward atmospheric radiation based on the thermal inertia of the pixel and the surface radiometric temperature which resolved the errors introduced by the unequally distribution of the atmosphere temperature and water vapor, and the replacement of the region with point.The correlation expression has been established between surface radiometric temperature(T) at the time of Landsat/TM passing by the study area and atmosphere temperature(T_0),which has made full use of the observation datum acquired from the experiments of the agriculture demonstration field in Xiaotangshan,Beijing.The datum includes those recoeded by automatic weather stations and thermal infrared thermometers(80 samples).The expression is,T_0=0.5087*T+9.5414(R~2=0.78). Through analyzing the datum from 21 regular weather stations in Beijing and 5 scenes TM TM images in 2004,beijing,the experience expression between the thermal inertia(P) and air vapor pressure(e_0) was created(105 samples),namely e_0=10.395*P+14.09(R~2=0.78). Furthermore,the model of Izionmon(2003) was used based on the two expressions,and the spatial model was given that retrieve the pixel downward atmospheric radiation(R_(ld)) under clear day using the remote sensing factors,such as thermal inertia and surface net radiation fluxes,namely R_(ld)=1-0.35exp-10~((10.395P+14.09)/(0.5087T+9.5414))σ(0.5087T+9.5414)~4 The retrieval results were validated using experiment-measuring data in practice.The retrieval precision is better than the one with traditional model in which only one downward atmospheric radiation value is correlated to one scene of the whole image.The improvement on the precision rather than 9.5% of estimating the surface net radiation fluxes by using the calculated downward atmospheric radiation on the pixel basis illustrated.It is feasible to estimate the downward atmospheric radiation by making use of the thermal inertia and the surface radiometric temperature.Thus the application of this method would have a bright future.
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