The Information System of Water Conservancy Project Statues for Zhangye City (ISWCPZY) was developed based on the remotely sensed image interpretation and in\|situ Global Position System (GPS) measurement,which were used to collect the geographic spatial data of the water conservancy project statues.The linked attribute data were provided and collected by the Zhangye Water Conservancy Bureau and its subordinate water management stations.The correlative thematic and background information were also collected.The data of the water conservancy project include 159 main canals,782 branch canals,5 315 lateral canals,6 228 pumping wells and 43 reservoirs.The total length of the canals is 8 745.0km.The data collection procedure is introduced in detail and the data quality of the water conservancy project is evaluated preliminarily in this paper,which would afford important reference for the data users.The ISWCPZY was developed by using Components GIS technologies and based on these data resources.The ISWCPZY,as one of the most integrated information management platforms of water conservancy project,has been widely used in the thematic atlas compilation,decision\|making supporting system development,social and economical module development,hydrological model construction,and so on.The canal,as the key information in the ISWCPZY,was analysed on the length ratio of different classes of canals,density,and direction.The results elicit obvious scale effects among the Zhangye City level,county or district level,and water management station level.
ystematical study on scaling and scaling effects and comprehensive utilization of an increasing number of different resolution remote sensing image data is one of the trends of scientific development on geo-spatial information. In order to provided the background knowledge to the further multi-scaling transformation study, this paper, as a preliminary work in the major topic of multi-scaling transformation, tried to verify the validation of the products from different scaling, to found the potential problems in the process of the multi-scaling transformation, and to explore some feasible methods for scaling transformation through the comparison and analysis. In this paper, the multi-scaling snow cover area acquisition mainly included: ① the field measurements in sub-pixels plot with 1m resolution, ② the resampled sub-pixel plot with 30 m resolution, the satellite inversion from Hyperion and TM with 30 m resolution, and the MODIS daily snow cover product MOD10A1 with 500 m resolution. Through the comparison of the several types of Snow Cover Area (SCA), it has been found that: ① the SCA of sub-pixel plot with the 1m resolution > the SCA of the resampled sub-pixel plot with 30 m resolution > the inversion of SCA from Hyperion and TM with 30 m resolution | ② If the plot with 1m resolution was used as the single point test which aimed at the image with 500 m spatial resolution, the characterization of the single point can not completely indicated the feature in the same geographical location on images with low resolution | ③ A methods of snow cover synthesis was used to help determine and resume the type of surface under the clouds at the region covered with clouds in the MOD10A1 SCA daily product. At the same time, through the validation of SCA test on the pixel level scale, nine potential and the key issues of the scaling transformation has also been found: ① Accurate position against the pixel matching | ② Resampling methods | ③ Data acquisition time and time series of the products | ④ multi-sensor image processing | ⑤ the impact of product algorithm | ⑥ the impact of mixed-pixel | ⑦ the size and design about the insitu plots | ⑧ the synchronous ground measurements of multi-physical-parameter | ⑨ the quantitative expression of the Spatial heterogeneity.
aken the eastern section of Qilian Mountains,Shiyanghe Basin as the study area,the land use and land coverage was classified using TM data in the typical mountainous system.The study area is located in 37°5′37″N\|37°6′30″N,102°3′37.2″E\|102°6′E with elevation 2 016~4 318 m.Firstly,the retrieved data from TM image such as principal components,vegetation indexes,image textural feature by using gray co\|occurrence matrix, the topographical data from DEM (elevation,aspect) were obtained in this study.The optimal bands combination was acquired using optimal band index method.The optimal bands combinations was used to classify the land use and coverage based on non\|supervised classification,maximum likelihood method,support vector machine and the decision tree classification method.The conclusion can be drawn from the approach:① the multi\|scale data mining is useful to improve the accuracy of classification | ② by comparing the four methods,the decision tree classification method had been selected due to its high accuracy which depended on the appropriate criteria selected.
Soil moisture is a key variable for the cycling of water and energy in the soil-atmosphere intreface.Active microwave remote sensing,especially radar remote sensing has shown its potential for retrieving soil moisture from soil surfaces.Since the backscattering process is very complicated and also influenced by soil roughness,the characterization of this roughness is crucial for an accurate estimation.The algorithm proposed in this investigation aiming to obtain the roughness parameters and soil moisture in SAR pixel scale simultaneously without the ancillary roughness ground measurements in virtue of 3 scenes ASAR images.An evaluation was performed in the middle stream of Heihe river basin and achieved reliable results (RMSE less than 6 vol %).
In this paper,a method to normalize the multi-temporal remote sensing images using pseudo-invariant feature was developed. The main processes include the selecting of reference image, correction of atmospheric radiation, the selecting of Pseudo-invariant feature points, establishing the regression model and estimating the result. The operating procedure was introduced in detail. The pseudo-invariant feature points chosen with artificial method were used in practice. The results were evaluated with principal component analysis. The result of evaluation indicated that the artificial method for choosing Pseudo-invariant feature points is feasible in the normalization process of the Multi-Temporal Remote Sensing Images | The method reduced the influences of some factors such as the seasonal variety of surface radiation, the difference of lighting condition and the great fluctuation of meteorology condition (atmospheric scattering and assimilating, change of cloud cover). The processed images can meet the demands of the model.
NDVI time series datasets have been successfully applied to global and regional environmental change research,vegetation dynamic,land cover change and extraction of surface biophysical parameters.Due to the limitation of atmospheric conditions and sensors,although temporal NDVI dataset has been preprocessed rigorously,there is still so much noise within the NDVI time series datasets which would affect further analysis and applications.This study introduced six common methods for reconstructing high-quality NDVI time series dataset in recent years: Mean-value iteration filter,the modified best index slope extraction,Fourier Transform,Savitzky-Golay filter,Asymmetric Gaussian function fitting and Harmonic analysis of time series.Then,the six methods mentioned above were applied to reconstruct the SPOT VEGETATION 10-days-maximum-NDVI composite data in 2007 and 2008 in Zhangye.The reconstructing results are compared and evaluated separately.Finally,a temporal profile with artificial noise was also reconstructed with the six methods respectivly in order to evaluating the merits and demerits of every method.
Snow is an important component of the Earth's surface.The accuracy of satellite-derived snow cover area products is important for water management and for modeling hydrological and climatic processes.In the paper,the accuracy of MODIS snow cover products (MOD10A1 and MOD102) and VEGETATION snow cover products (VGT-S10 snow cover products) algorithm under varied terrain and land cover types were analyzed using in situ observation data at 47 climatic stations in northern Xinjiang area,China,during the five snow seasons including January 1 to March 31 of 2001 and each November 1 to March 31 of 2001 to 2005.The research result indicates that the overall accuracy of MOD10A1,MOD10A2 and VGT-S10 snow cover products in all climatic stations is high at 91.3%,90.6% and 87.9% respectively.However,the overall accuracy of the snow cover products in mountain regions is low.The snow omission of three products is 32.4,21.7% and 36.3% respectively in mountain climatic stations.The cloud limitation ratio of MOD10A1 reaches to 61.8%,but that of the MOD10A2 and VGT-S10 are only 7.6% and 1.8%.The comparison result of user-defined 10-day MODIS products and VGT-S10 products shows that the snow identification ability of MODIS is more accuracy than VGT-S10 snow cover products.However,the VGT-S10 snow cover products are little affected by cloud than MODIS snow cover products.
The objective of this paper is to analyze the forest height retrieval methods from polarimetric SAR interferometry and their validation against ground truth.Both of the methods based on coherence optimization process and that on super-resolution method such as ESPRIT are generalized,analyzed,and compared.Also in this paper hybrid methods of ESPRIT and three-stages/three-stage Sinc are proposed and validated.The DLR quad-polarimetric interferometry ESAR data is used for forest height generation.The validation with ground truth shows that the three-stage and three-stage Sinc method have a relative better performance than all other methods despite with a overestimation of height but with a very good correlation with ground truth.In contrast,as in expectation,the direct ESPRIT phase differencing methods,due to their virtual height results,severally underestimates the forest heights but also with a poor correlation with ground truth.The hybrid methods of ESPRIT and three-stages/three-stage Sinc method,even a fast processing gained,lead to no improved results.
The long time series of passive microwave satellite data (SMMR and SSM/I) have provided important information on the earth surface science and climate research in the past decades.Due to update of satellite-based radiometers and their platforms,there are biases among brightness temperature from different sensors,at the same place.In order to obtain consistent brightness temperature datasets,the relationship of the microwave brightness temperatures from similar sensors on successive satellite platforms must be understood.The brightness temperature data at 18 and 37GHz channels of Nimbus-7 and 19GHz,37GHz channels of DMSP were analyzed.The cross cabibration coefficiemts are estimated based on F13.
There are various factors that impact passive microwave responses of snow. These factors include depth, crystal size, wetness, density and temperature of snow. In this paper, a sensitivity study was carried out based on Microwave Emission Model of Layered Snowpacks (MEMLS) model. The result showed that grain size made the most effect on the output of the model, while depth, wetness, density, and snow temperature are in the next place. The relation between snow depth and the difference between 19 and 37GHz brightness temperature can be described by a linear formula when the snow depth is less than 50cm, while the range of increase will slow down and tend to a saturation when the snow depth is large than 50cm. Snow density and grain size can greatly influence the coefficient of the linear formula. The passive microwave remote sensing data could not reflect snow depth and snow water equivalent when snow is wet because liquid water significantly changes the permittivity of dry snow. The difference of snow temperature at different channels can reduce the effect of brightness temperature on the estimation of snow depth.
Height of a building is an important element in the city disaster evaluation and prediction. Up to now, several methods have been developed to estimate the height of a building using single satellite image with a high resolution. However, the accuracy and calculation speed are not ideal for application. To solve this problem, this paper developed a new fast method. In this method, the distance between a pair of matched points was used. The result showed that the accuracy of this new method was higher (less than 2.04 meters) and it could be wildly used in prediction and assessment of city disaster.
In this study, the area around Qinghai Lake was taken as the study area. According to the main reason of the formation of eco-environment and its result, eight evaluation indexes (including vegetation index, soil luminance and soil moisture, DEM and slope, temperature, precipitation and land use) were set up based on RS and GIS technology. The weight for every evaluation index was calculated with AHP method. The study area can be marked as four degree with qualitative and quantitative analysis: tiny vulnerability, little vulnerability, middle vulnerability and heavy vulnerability. The results showed that the areas in little vulnerability and middle vulnerability account for 35.2% and 40.7% respectively. It was concluded that the current status of the integral eco-environment quality of the research area are affirmative. It could provide theoretics for the governance to protect and formulate regional management by this research.
The two maps of LUCC of Songhuaba water source region in Kunming city was obtained through the interpretation of two Landsat TM Images acquired in 1992 and 2001 respectively. SWAT hydrological model was operated to simulate the yearly and monthly surface runoff during 1992 to 2001 in this area combined with the analysis of the LUCC, DEM, hydrological data, meteorological data, soil data and so on. According to model calibration, 4 kinds of LUCC cases are set to predict the Changes of runoff. The conclusions are as follows: case one: if it is a non-vegetation area, the runoff depth will increase 53.87 mm | case two: if farmlands and garden plots become woodlands, the runoff depth increase 3.62 mm | case three: if habitations, industrial and mining areas, farmlands and garden plots turn into woodlands, the runoff depth increase 13.73 mm | case four: if there are only woodlands, the runoff depth increase 6.99 mm. The case one might associate with heavy soil erosion. In the case there, runoff depth can be increased more than that in other different afforestation situations.
In the broadly northwest arid regions,frequently,same object has different spectral characters because of the special characteristics of land cover change such as complex causes of formation,sensitivity to environment change,rapid and violent change and obvious differences in landscape.The conventional methods of classification including visual interpretation,supervised classification,unsupervised classification,and artificial decision tree classification have disadvantages in the efficiency or the accuracy.In this paper,machine learning algorithm based on C5.0 decision tree was used to classify the entire study area automatically according to the sample data mining classification rules.Spectral features,NDVI,TC,texture and other informations were involved in the algorithm.More classification rules could be mined by machine learning decision tree.C5.0 algorithm handling with both continuous and discrete data is independent of the distribution of sampling sites,The classification rules mined by this algorithm were interpretable.Other superiority of this algorithm included the fast speed of training and higher accuracy than many other classifiers.Thus,it is able to be used in the mapping of land use/cover change in a large scale in northwest arid regions.
order to extract the urban residential areas automatically, this paper chose one of metropolis, small cities and towns respectively to carry out research experiment based on the calculation models built using the spatial modeler of Erdas Imagine. The results showed that the traditional extraction methods based on Landsat TM had disadvantages. This study established a comprehensive threshold method to retrieve urban residential areas automatically under the conditions of NDVI<0, TM1/TM4>T and TM2+TM3<TM4+TM5.T took values in the interval of 1.5 to 1.9 at different acquisition date of TM images. For example, T took values about 1.5 in spring and summer but 1.9 in autumn and winter. Of course, the value could also be adjusted flexibly according to actual situation. This method had a better accuracy in the three study areas because it rednced the impacts of some features such as the mountain shadows, water and its boundary, urban grass land and river.
Based on light-use efficiency model,a net primary productivity model for grassland using EOS/MODIS data was proposed.This model considered the influences of temperature and the difference of surface water vapor pressure.The NPP of grassland in 2003 was calculated using MODIS data with 1km×1km resolution from April to November in 2003,the multi-year annual average value of monthly solar radiation of 73 meteorological stations in the Loess Plateau and other relevant datasets.The result showed that the estimation of maximum net primary productivity of the entire Loess Plateau is 516 gC yr-1 while the minimum is 1 gC yr-1.The spatial pattern of NPP in Loess Plateau indicated that high values of NPP distributed in the south and west corners,then rapidly decreased from the southeast and northwest corners into the center inland regions.The trend is closely related with the differences of hydro-thermal conditions and the law of zonal differentiation of grassland.
The security of Eastern Qilian Mountainous landscape was analyzed with percentage of matrix, changing rate of patch number and area, changing rate of patch density based on RS. The result showed that:① grassland which maintained in stability condition was the key composition in the stability of eastern Qilian Mountainous landscape ；② patches with little area got the highest stability condition, and played important role in maintaining the landscape heterogeneity in eastern Qilian Mountainous landscape.
As one of the important achievements of the Great Wall surveying project,thematic maps for the Great Wall are based on the aerial remote sensing images,which carry a large quantity of present fundamental geographic data and thematic information.Those maps can serve various purposes such as Great Wall reparation and protection.Generally there are two major techniques to produce imagery thematic map.The first is using a geographical information system (GIS) software,e.g.,ArcGIS and MapInfo,etc.The other is using professional mapping software such as CorelDraw,Illustrator.In this paper,we propose a novel technique which combines geographical information system software (ArcGIS) and professional mapping software (Illustrator).The combination will fully make use of advantages of each technique and avoid their weaknesses.It will use ArcGIS to manage and process spatial data,and use Illustrator to present and output spatial data.We applied this method to producing the thematic maps for the Great Wall.Overall design,data organization and processing,and map decoration design were introduced.This paper concluded that this combination technique not only improves mapping precision and map presentation,but also increases the mapping efficiency and lowers costs.Such method will have a brilliant future for map producing.
The global environment change has become one of the three global environmental issues with the greatest global impact.Lake is of great ecological significance in regional ecosystem study.Dynamic change as one of three main lake environmental problems of lakes has became the key point of the research area.Remote sensing techniques,as scientific tools of rapid investigation and monitoring,have been widely applied in the research of dynamic change in lakes.Main progress around of the world in areas of lake dynamic change research by means of remote sensing techniques are introduced in the aspects of basic principles and remote sensing data sources,remote sensing classification and dynamic change monitoring methods of lake information | especially,the advantages and disadvantages of remote sensing data source and dynamic analysis methods are analyzed deeply.In addition,some existing problems and the development trends of the recent lake dynamic change research are discussed.
The rapid spread of poisonous weeds often causes serious damage to grassland habitats,and limits the development of animal husbandry.Remote sensing technology offers the advantage of efficient natural resource investigation than ground survey,and it has become one of important techniques in pasture management.The spatial resolution and spectral resolution of the sensors are the key factors which will determine the ability of detecting poisonous weeds.Acquiring imagery data at proper phenological stage will help to improve the accuracy of discrimination.This paper reviewed three types of remote sensing technology in detecting poisonous weeds.Aerial photography has not been widely used because of its high cost and complex data processing.Most current multispectral satellite sensors have relatively coarse spatial resolution and only show some potential in detecting dense and large areas of poisonous weeds.The emergence of hyperspectral remote sensing has improved the accuracy of vegetation classification and identification,and it will be the main basis for high accuracy poisonous weed detecting and mapping in the future.By reason of the redundancy and complexity of the hyperspectral remote sensing data,the methods of data handling and classification will be challenges which will influence the accuracy of detecting poisonous weeds.
The application of Digital Elevation Model (DEM) had instructional significance in the second terrain investigation in Gansu Province.This work took Yuzhong County as study area.An algorithm using DEM to classify agrarian slope was employed in this study.The feasibility of this algorithm was analyzed soon.The comparisons in three aspects including the difference of the slope calculations for farmland,the difference between agrarian slope and topographical slope,and the accuracy of the results calculated with different models or using the DEM datasets in different scales(or spatial resolution)were operated in this study.From this paper,two points have been observed.Firstly,topographical slope could instead of agrarian slope in gullied regions in the Loess Plateau | additionally,the DEM with the interval of 20 meters is the best choice for slope calculations for farmland.Secondly,to overlay probabilistic slope model with database was more feasible in the slope calculations for farmland.
Combined with the Scalable Vector Graphics (SVG) technology,some basic WebGIS functions are achieved in this paper based on Asp.net,Script language (JavaScript) and DOM Techniques.Requirements and solving themes of general WebGIS functions were considered during this process.In this paper,three technology problems were solved.Firstly,the Internet transmission speed of mass geographical spatial information was improved.Secondly,the limit of map data formats for publication required by GIS software platform (spatial data format was mostly required) was released.Thirdly,data security problems in the process of spatial data publication were improved.To solve all these problems,mapping data was conversed into SVG data which was published on WEB later.WebGIS system developed in this paper receives a good result in practices.
The full-color LISS-4MN images with 5.8m spatial resolution obtained by Indian IRS-P6 satellite were used in this study.The technologies of band composition under MN mode,image calibration and data fusion of LISS-4MN and ETM+ were researched in the preliminary plan on soil and water conservation.Land use type,vegetation cover type,soil erosion and soil and water conservation in Xianzigou watershed of Liujiaxia reservoir were surveyed using IRS-P6 images based on artificial patches drawing,the features of watershed soil erosion,was learned comprehensively.A reasonable and effective soil erosion prevention system was established to improve the efficiency of soil and water conservation in ecological engineering.
