This paper analyzes the key factors that result in the estimation errors of the MODIS land surface temperature products.Then the principle methods of validating the MODIS LST was discussed and compared.Normally there are bigger uncertainties of MODIS LST products in the semi\|arid and arid regions.As a case study,the Heihe river basin was selected to estimate the accuracy of MODIS LST products in Chinese arid and semi-arid regions.The two kinds of ground-measured observation data were obtained from the automatic meteorological stations:Infrared Radiation Thermometer data and longwave radiation data.The comparisons were performed for the validation based on these two types of observation data over three typical land cover types.The result demonstrates that:it is more reasonable to use long\|term nighttime surface longwave radiation data to validate the MODIS LST products.The validation results indicate that mean absolute error is less than 2.2 ℃ in the selected stations.
The research object of this paper is Tamarix ramosissima,which are the vegetation dominant species in lower reaches of Heihe river basin.Ecology,Geobotany,Statistics theories and remote sense technology were applied.The spatial distributions of Tamarix ramosissima was obtained from high resolution satellite imagery GeoEye-1.Biological characteristics of typical samples survey and biomass test of Tamarix ramosissima were made.Then the model of Tamarix ramosissima canopy area with biomass was built.The over ground part biomass of Tamarix ramosissima was estimated.Finally,the spatial distribution patterns of biomass in the different buffer zones of 0~2,2~5,5~10 and 10~15 km was analyzed.The results showed:The total biomass of Tamarix ramosissima is 4.10×105 t.The biomass of 0~2,2~5,5~10 and 10~15 km buffer zones were 2.34×105,1.07×105,6.35×104and 5.17×103 t separately.The distance to river has significant effect on biomass of Tamarix ramosissima.The biomass of unit area increases with the distance reduced.The correlation coefficient of them is -0.97.
Using the latest data of GRACE gravity satellites—RL04,published by the CSR,we got the trend of water storage in the Heihe River Basin(HRB) through 2002~2008.In order to improve the inversion accuracy,errors were removed from the data by decorrelation and Fan Filter.Then we analyzed temporal and spatial distribution of water storage variations in the HRB.Results revealed that water storage of HRB features with obviously seasonal characteristic.The amplitude peak of increasing is in summer and declining in winter.Inter\|annual analysis showed HRB water storage appears an increasing trend,which is consistent with that of precipitation variations in HRB.Spatially,water storage is greatly influenced by the terrain in HRB,resulting in an increasing trend in the upstream and midstream areas,while a decreasing trend in a part of the downstream area,increasing in other parts.
In this paper,a new satellite\|derived approach for instantaneous SSI by combining Moderate Resolution Imaging Spectrometer (MODIS) and Multi\|Functional Transport Satellite (MTSAT) data is presented and validated with one year pyranometer measurements from three stations in Heihe river basin.The approach is based on a Look-Up Table (LUT) created via comprehensive radiative transfer modeling,to expect attaining equal results as directly using a complicated Radiative Transfer Model (RTM) but without that heavy computing loads.Synergy of the multispectral sensor MODIS and high temporal resolution geostationary satellite MTSAT enables the use of late remote sensing information on atmosphere/surface state and complements each own shortcoming.Meanwhile based on the instantaneous retrieval results,the calculation of hourly average SSI is also explored.The preliminary validation demonstrates that the high accuracy instantaneous SSI can be produced over in Heihe river basin using this approach.
We utilized the synchronous observation of MODIS and AMSR-E on Aqua satellite to retrieve the microwave surface emissivity of Tibetan Plateau.Combining with the data of land surface types derived from MODIS observations,we further analyzed the variations of microwave emissivity with frequency,different time scales,and land types over Tibetan Plateau.The results show that among the three main land types in Tibetan Plateau,the emissivity over grass land is higher than that over barren and shrub land,and the two latter have very similar trend and close value.The land surface emissivity decrease with increasing frequency,and the variation range at vertical polarization is more remarkable than that at horizontal polarization with increasing frequency.For different time scale,the annual variation is small,and the seasonal variation is a little bit,and the diurnal one is quite obvious.The differences of horizontal polarized emissivity over different land types are more obvious than those of vertical one so that the former emissivity could be more useful to classify land surface types.
Temperature Vegetation Dryness Index (TVDI) is an extensively used method for land surface soil moisture retrieval from optical and thermal\|infrared remote sensing data.This study adapts the typical TVDI model that was proposed by Sandholt (2002),to retrieve soil moisture information from TERRA/MODIS data in Xinjiang,west China.Improvements mainly include:① cloud\|mask correction and 16\|day averaged temperature composition approaches are used to reduce the impacts of clouds in TVDI\|based soil moisture inversion;② the problems caused by the topographic,thermal radiation and land\|cover differences over a large area are also addressed in the adjusted TVDI model;③ the modeling of TVDI dry edge is also adjusted to reduce the errors in soil moisture retrieval from MODIS data.In\|situ measurements in the study area were collected with the soil sampling instrument,and used to derive the model parameters and verify the adjusted model outputs.The result shows that the modified TVDI model can give better estimation of land surface soil moisture from MODIS data in a typical arid area,Xinjiang.
DEM is the basis of geographic information system data,associated with the terrain in all areas has a very broad application prospects,in the production and applications of DEM,has an important significance.Wenchuan earthquake changed the existing landscape of disaster area,lead to the original DEM data and Topographic Map no longer have timeliness,the effective DEM data for earthquake relief at the time and reconstruction accuracy orthophoto imagery map production,3D roaming,road transport and geological disaster forecast and warning information extraction,etc.is extremely important.Therefore,the technical methods adopted quickly after the earthquake disaster obtain DEM data was a serious problem.In this context,this paper use ENVI platform,selected for the study area in Sichuan Province Pingwu country,select IRS\|P5 stereo pair as the main source of the data,in the emergency case of cannot be collected in high\|precision ground control points,try to get the study area 1∶50 000 DEM data after the earthquake quickly.Experimental results and the accuracy assessment show that,the experimental area for post\|earthquake DEM accuracy,reaching 1∶50 000 scale accuracy or higher standard.This research method and process in similar regions of emergency conditions to extract up to a certain precision of the DEM has practical reference value.
A method for urban major road information extraction from QuickBird imagery is proposed.First,the use of histogram equalization for the enhancement of the original remote sensing image processing,outstanding image edge information.With the Otsu automatic thresholding method for image enhancement processing after the initial split,extract urban roads and houses and other buildings.According to the image difference between the morphological characteristics of various elements to build a different tag images with different structural elements to build the road model,with the model of thresholding the image after morphological reconstruction,were extracted from the city roads and buildings.Generated reconstruction of the road shape optimization module,extract the contours of urban roads.Experimental results show that the method can effectively extract images from high resolution remote sensing of urban road network.
Traditional spatial data system always can not offer data product to meet final customer needs.Scientists in earth observation field often spend a lot of time on data preprocessing,in order to adapter specific sub\|area,image band or file format for application request,even if the final calculation and analysis is very simple.The on\|demand spatial data services technology,aims to integrate distributed computing resources and data resources together,perform various geospatial process functions for user demands.In this paper we propose an on\|demand oriented spatial data service model,which integrate a large number of fundamental pre-processing tasks into data access procedure,and minimize the time cost.In order to build proper mechanism for data service,we have a close examination of the basic operation involve with data source,and classify these operations into some service module,combined with functions described in OGC service specifications.Thus,the model based on OGC WCS standards can provide high level spatial data products to meet applications requests.We use this on\|demand data service model in Spatial Information Grid platform for case study,and conducted close examination of comparison study with traditional methods.Through the experiment we can concluded:for traditional spatial data service,results returned by the query identifiers.Users retrieve data items and copy the data to local storage by the physical file names.Two parts greatly impacted process performance,which is time for data transmission to local side,and time for local preprocessing in client side.As to the system build with on demand data service model,data acquisition is customizable.The on\|demand operations are done on the server side.The data has been manipulated according to specific operation requirements before transmitting to the user.This method better improves geo-information processing efficiency,and reduces additional time waste on preprocessing.
Aiming at the question of shape and scale parameters estimations of K-distribution,a method combing fractional order moments with NM simplex algorithms is presented.Initial values of shape and scale parameters are calculated via fractional order moments,and then the estimated values are obtainded by numerical searching algorithms of NM simplex.We have analyzed measurement data of X-band sea clutter.The results are shown that the K-distribution is superior to Gamma and Weibull distribution.The probability density function of K-distribution is consistent with the measurement data,and it has the lowest RMSE.As far as one dimension sea clutter is concerned,the method has moderate computation efficiency.
To extract quantitative information from HJ-1B imagery data accurately,atmospheric correction is a necessary step.We present a new algorithm that based on stratified elevation and using the spectral correlation between red and 1.6 μm channel to drive atmospheric properties and execute atmospheric correction process for HJ-1B Data.Since our study area in mountainous region,we separate the whole area into 17 different elevation zones by step of 0.1 km and simulating aerosol optical depth in 0.55 μm within each elevation zone using radiative transfer model,then the atmospheric correction procedure in different elevation zone of each visible,infrared and short wave infrared spectral channel is performed.Through the comparative analysis of spectral curve of dense mature forest,bare soil and water contained sediment before and after atmospheric correction at different sites,the result indicating this approach is promising in atmospheric correction for HJ\|1B imagery data.
Remote sensing plays an important role in regional vegetation change research and provides new technical possibilities for global vegetation temporal and spatial variation.NDVI is supersaturated in regions with good vegetation,but is so sensitive in areas with sparse vegetation cover.We selected Songmuxicuo basin with sparse vegetation in the south of Guliya Ice Cap as our research region,and used NDVI dataset derived from imagery obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) to build the time series of vegetation change in recent 10 years based on RS and GIS technology.Then we analysed the relationship between vegetation change and climatic factors.① The change demonstrated that the area of vegetation covers increase in recent 10 years in south of Guliya Ice Cap in Tibet an Plateau.② NDVI character showed that the grow season is short,and the NDVI floating interval is 0.11～0.13,lower than nationwide level(0.3～0.35),also lower than global open shrublands mean NDVI(0.2～0.4).③ The correlation analysis between NDVI with the temperature and precipitation in the south of Guliya Ice Cap was carried out.There was significant positive correlation between NDVI and temperature and precipitation was not strong correlation relatively with NDVI in the region.It implied that the increasing temperature recent years is the mean factor to make vegetation covers increase in the region.
Meteorological observations environments and their representatives play important roles in weather forecast and climate change research.Based on high-resolution multi\|temporal Landsat satellite data with land\|based GIS technology,four Landsat\|based land use/land cover types were identified and used around the meteorological station,including:construction land (urban and built\|up),water,cultivated land and vegetation (forest and grass).The method that using satellite remote sensing survey and assessment of the environment of meteorological station was presented,and then it was applied to study the representativeness of 6 meteorological stations environment in Anhui province.The results showed that temporal and spatial variations of land use types from satellite-based remote sensing could be well applied to surveying and assessing the variations of meteorological stations environment in the meteorological stations buffer zones.The above survey and assessment had good effects with the facts.The effects show that the representativeness of national climatic stations environments in Anhui province were better,while the representativeness of national basic station environment in Hefei city was not good due to the impact of itself urbanization.This work provided convincing evidences that a remote\|sensing method for analyzing the representativeness of meteorological stations was proven to be robust and applicable.In addition,it was very useful to identify the reference and urban stations locations that using the landsat images when we evaluated urbanization effect on surface air temperature trends.
The study chooses the Landsat MSS remote sensing images in 1970s,TM images both in 1993 and 2009 to extract information of the Fen river basin by using several methods,such as the normalized difference vegetation index,normalized difference water index,threshold method,spectral relations act method,and the combination methods of supervised and unsupervised classification.Referencing the “ecological environment evaluation of technical specifications” issued by Environmental Protection Administration,we conduct quality evaluation and time sequential analysis to eco-environment by selecting biological abundance index,water network density index,vegetation cover,soil degradation index and the environmental quality index for the Fen river basin at three different scales-the upper,middle down streams of the river,administrative regions and small drainages.The results show that:the eco-environmental quality is fair or poor in the Fen river basin at any scales;the eco-environment quality reduced from 1970s to 1993,which began to become better from 1993 to 2009;the eco-environment quality varies at different scales,but the change trends are similar.This research has some scientific significance in the eco\|environment protection and management of Fen river basin.
Environmental remote sensing is an important area of application of remote sensing technology.With the development of the hyperspectral remote sensing technology and the quantitative remote sensing theory,it is paid attention to which carries out the distribution of atmospheric SO2 using OMI and MODIS data.OMI is a new generation of atmospheric composition detection sensor.OMSO2,one of the OMI Level-2 trace data products,owns perfect sensitivity in SO2 value inversion.Based on the daily OMI Level-2 trace data in February during 2005~2008 and in May,August,November in 2005,the study,using remote sensing and GIS methods,analyzes spatial distribution,seasonal variations and inter-annual variations in the winter of SO2 at the atmospheric boundary layer in Lanzhou and surrounding areas.The results show that SO2 values had a discrete planar distribution,and Lanzhou-Baiyin and Jinchang are two evident high\|value areas.SO2 value in winter was significantly higher than that in other seasons,meanwhile inter-annual fluctuates obviously.The study shows that using the OMI Level-2 trace data products can detect and assess the situation of SO2 under the condition of larger human activities scales.
Taking the Regiment 121 of the 8th Agricultural Division,located in the manasi oasis in the north slope of Tianshan mountain,in Xinjiang,as the study area,the paper analyzed the spatio\|temporal variability of soil nutrients by the combining method of geostatistics,traditional statistics analysis and GIS technique.The results showed that:the contents of soil organic matter decreased significantly from 1982 to 2004,whereas the total N,total P,available N,available P and available K increased obviously,which suggesting,after twenty\|two years of cultivation and fertilization,N and P contents in soils has significantly increased.
The Nugget/Sill ratios revealed that spatial correlation of the available K belongs to a strong class,suggesting that spatial distribution was mainly affected by soil parent material,while available N and total N has a moderate spatial correlation,indicating theirs spatial distribution was jointly affected by soil parent materialand fertilizer,cultivation etc.The Nugget/Sill ratios of total P and OM was increased to 39.11% and 45.51% in 2004 from 15.74% and 17.57% in 1982 respectively.The changes in the Nugget/Sill ratios indicated that the strong spatial correlation of the total P and OM has changed into a moderate spatial correlation,suggesting that the stochastic factors such as fertilizer,cultivation,irrigation and crop structure during the 22 years have affected,and the soil nutrients were gradually jointly affected by the structural factors and stochastic factors.The contents of soil organic matter,total N,total P,available N and available P in Manasi river oasis were lower than those in Sangong river watershed oasis,but the content of available K,was higher than that of Sangong river watershed in 1982,and lower than that in 2004. Spatial variability of soil nutrients and soil organic matter in Manasi river oasis was lower than that of Sangong river watershed oasis,which was probably related to high fertilization in long\|term cultivation and crop in Sangong river watershed.
This paper selected the north part of Shenzha in Northern Tibet as study area.The author collected and processed 23 times MODIS NDVI data of 2009 in order to get the time-series NDVI data of study area.Then reconstruct the NDVI time-series data to improve the data quality by the Savitzky-Golay filter.After that,this paper analyzed the time-series curves of six types to get the different characteristics and extract the best bands for classification.Based on the work before,the author divvied the study area to six types by ISODATA method in ENVI.They are swamp meadow,alpine meadow,middle coverage grassland,low coverage grassland,bare land and water.The author analyzed the spatial distribution characteristics of four grassland types combine with the terrain data.Series of processing results and analysis proved that using the MODIS NDVI time-series data to identify the grassland type in Northern Tibet is feasibility and applicability.
Qerqan Oasis—a typical Oasis in arid area was chosen as an example,the remote sensing images of MSS in 1973,TM in 1991,ETM+ in 2001 and 2008 were used as major data sources,be combined with fieldwork data,the appropriate disaggregated indicators system was selected to classify the images,and classified the images,and then obtained the different types of land use/cover transition matrix.The results showed that the cultivated area had been showing an increasing trend in the last 35 years,it was increased 105.32 km2,the increase of the cultivated land is mainly from the conversion of grassland and woodland,the cultivated land is the fastest growing land use type.Woodland and grassland had been gradually decreasing trend,and most reduced land type was the forest land,it was decreased 69.459 km2.This was mainly caused by the conversion proportion area of woodland to the grassland、water land and cultivated land was much faster than grass land conversion to the forestland. Grass land decreased 63.093 km2,and it was mainly from the conversion of grass land to the cultivated land and rare land. The water area had been showing an increasing trend, it is increased 22.073 km2,and the increase of water land was mainly from the conversion of grass land and rare land to the water land. Rare land had a little increasing trend, and it was increased 5.093 km2.
We classified the data of Heihe e-Science ecological\|hydrological data sharing center into six sorts:raster data,vector data,AWS data,FLUX data,ordinary document data and image data,aiming at realizing visualization by their characteristic.Moreover,by researching the methods and tools for data visualization on Web,we selected open source Web mapping tool MapServer,flash based Web charting tool—Amcharts,OpenOffice/unoconv and SWFTools to make the corresponding visualization module for achieving data visualization for single data and datasets,and we finished an application system at last.
For fragile geological environment and the frequent occurrence of landslides in Lanzhou city,in this paper,based on Logistic regression model and adopted ArcGIS and SPSS softwares,selected elevation,slope,average precipitation from July to September,vegetation cover,roads,railways,lithology,faults as impacted factors of Lanzhou landslide disaster.First of all,impacted factors were classificated and calculated index values of every class at the same time,and then overlapped all impacted factors in ArcMap of ArcGIS software.The end,use of Logistic multiple non\|linear statistical methods to calculate the coefficient of each impacted factor in SPSS software,according to the statistical results,Logistic regression model was gained.Drawed the Lanzhou landslide susceptibility zoning map based on Logistic regression model in ArcMap,zoning map of landslides accord with the actual distribution of landslides.Kappa value and AUC value of the model were 0.623 and 0.709 respectively,the tested results of the two methods showed that the model is good and can be applied to the Lanzhou landslide susceptibility zoning studies.
Water quality remote sensing monitoring system of large and medium\|sized reservoirs in Guangdong province can meet the need of widely,dynamically,quickly monitoring water environment of reservoirs and provide water environment protect information.The system overall structure and technical workflow are introduced,and the key techniques are expounded.The system combines GIS and RS functions,based on ArcEngine and PCI-EASI component secondary development and water quality remote sensing physical analysis model,with the structure of configuration files,menu driving and public data pool.The system functions contain image pretreatment,water quality remote sensing automatic retrieval,water quality classifying,statistic analysis and so on.The system brings good effect to operational monitoring water quality of large and medium-sized reservoirs in Guangdong province.
In order to give full play of application value of Google Maps in the region of GIS,regard integration of Google Maps and vector data as the starting point,developed a vectorization web platform by the use of Ajax and GDAL on the basis of Google Maps API.Through this platform,users can implement Google raster maps vectorization,save the results as ESRI Shape files and display user Shape data in vectorial mode on Google Maps.
This paper introduces the concepts of ontology,geographic ontology and toponym ontology,discusses some key issues on recognition and disambiguation Chinese toponyms from Web texts based on natural language processing using toponym ontology under GATE (General Architecture for Text Engineering) framework,designs and implements a prototype system.By eliminating the geo/non-geo and geo/geo ambiguities,rich semantics and precise geographical coordinates are given to the extracted toponyms which correspond to the locations on the earths surface.At last,an experiment is made and the result is analyzed.
This paper introduces the method and process of 3D GIS system creation in skyline software environment.The data source of the 3D GIS system includes aerial and satellite images,digital elevation model data and related thematic data.All these data come from Gansu Political GIS platform; meanwhile,the 3D system is an indispensable part of this platform.Because 3D terrain model is the foundation of 3D GIS system,also,3D terrain model uses mass data,which leads to many problems,so,some important issues and experiential parameters during 3D terrain model creation based on mass data is presented in this paper.Multi-computer cooperating calculating is used in the procedure.Last but not the least,application instances of the 3D GIS system in Gansu province is illustrated.
