Microwave remote sensing can penetrate the clouds and even to some extent the rain and can make up for the lack of thermal infrared light. In order to get land surface temperature (LST) under all weather conditions, it is essential to develop the inversion algorithm based on microwave remote sensing data. This paper reviews the former algorithms found in literature, which can be roughly categorized into the statistical-based and physical-based retrieval algorithms and neural network algorithm from a methodology perspective. The merits and disadvantages are summarized for each method. This paper also points out the direction of future development and provides a reference for future research.
Single image geo-spatial mapping is very important and the research can promote the thorough application of the single image in GIS. Firstly, the concept of single image geo-spatial mapping is briefly introduced. Then, a method is proposed. Its main steps are as follows: A large quantity of images should be collected and the principal optic axis is approximately horizontal. Then each image is divided into many super-pixels, and lots of features are selected such as color, texture and location. All super-pixels are calculated one by one and the classes include ground and no ground. Through training, a decision tree can be obtained.On the basis of the horizontal constraint as well as the center coordinate of the camera and azimuth, the image coordinate of the ground area can be transferred into the projected coordinate.Through shooting many images on a university campus, the method is verified. The mapping accuracy is analyzed. The result is good. The study is useful for single images application in GIS.
Accurately extracting the riverway information could provide the basis for dam construction, flood prevention projects and disaster reduction facilities. Taking Huayuankou section in the lower reaches of the Yellow River as the study area, the authors enhanced the remote sensing images based on an improved fusion method that combines PCA transformation with wavelet transformation. Then the riverway information of four-period images consisting of winter, spring, summer and autumn was extracted using the object-oriented method. The seasonal variations in the river area, the mean river channel width, the river island area and the amount were comparatively studied under the support of GIS. The results show that the integrated remote sensing technique and GIS could directly monitor the seasonal variation characteristics of riverbed with good precision.
Research on image characteristics and quality of ZY-3 satellite multi-spectral data was performed in comparison with SPOT5 HRG(high resolution geometric)satellite data. Subjective quality assessment was employed to compare the image quality, and the differences were analyzed by calculating data range, mean and standard deviation from gray scale statistics of the three distinct areas; on such a basis, the multi-spectral radiometric characteristics were investigated, and histograms of typical ground objects in these areas were selected for comparison. By calculating the correlation index between different bands of ZY-3 and SPOT5 images, the band correlation assessment was made. Through refining texture characteristics, such as homogeneity, contrast, entropy and angular second moment of these two images, their textural qualities were assessed. The results show that, though the high correlation between ZY-3's bands in vegetation makes its vegetation extraction capability lower than that of SPOT5, ZY-3 multi-spectral image, it still has a better performance in the aspect of water and building extraction potential and it has advantage in image quality and texture characteristics, so it can be used as base map for different applications in different fields.
At present, high temperature target recognition mainly uses thermal infrared remote sensing data. In this study, the authors have found that shortwave infrared band has better recognition capability than thermal infrared band. In the mixed pixel of high temperature targets,temperature and area of high temperature objects are unknown. They are the key parameters that can determine the spectral character of mixed pixels. Based on the constant energy principle,the authors formulated the radiation energy equation for the mixed pixel of high temperature targets on the Earth's surface. The results of the sensibility analysis for the equation parameters show that the area percentage of high temperature targets and the reflection of the normal temperature targets are most sensitive to the invertion of the temperature and the area of high temperature targets. ETM+ 7 data obtained in Baode of Shanxi and Fugu of Shaanxi were used for study of high temperature target recognition. The radiation flux density of the recognized fire is about 1.36 to 4.76 times that of the background value. Field verification shows that Mahalanobis method has the precision of 88%,suggesting that shortwave infrared band can be used to recognize high temperature targets.
Seeking for the optimal seam-line is an important part in remote sensing image mosaic. Most algorithms for finding the optimal seam-line only emphasize the minimum difference between pixels rather than the integrity of objects. Therefore, the authors put forward a new algorithm for finding the optimal seam-line based on minimum gradient point in local area in this paper. This method adopts the gradient to indicate the change of gray scale and then finds the pixel of the minimum gradient in local area progressively according to the principle that the change of gray scale is milder when the gradient is smaller. Meanwhile, an improved difference method to solve the band effect caused by the hard correction method is proposed in this paper. The experimental results show that the optimal seam-line determined in this paper can avoid the great gray scale variation area and the objects can be reserved unbroken. It avoids the band effect well and the seam-line is removed smoothly, the mosaic image also has a good sense of sight. In addition, the proposed method is very simple, effective, and easy to realize.
In order to classify the edible oil and the waste cooking oil by using their difference in spectral characteristics, the authors employed 22 samples collected from the mixture of two kinds of waste oil and four sorts of edible oil to analyze the possibility of distinguishing these two kinds of oil by clustering their hyperspectral digital number. Spectral data which lies in the range of 350~2 500 nm were utilized in this paper for clustering analysis. Digital number of hyperspectral data, first order derivation and second order derivation of the reflective data were used as the spectral information for the target. Correlation distance, Euclidean distance,standardized Euclidean distance and Minkowski distance method were used to calculate the distance between the spectral objects in the data matrix. And then, eight different kinds of distance method were employed to compute the clustering tree, which accurately classified these oils into twenty-two types. Numerical experiments demonstrate that un-weighted distance method and interior square sum distance could be utilized in the correlation clustering analysis to accurately distinguish different kinds of oils in the sample and to classify these oils into 22 types accurately.
In order to study the method for identifying the oil film using the multispectral data, the authors obtained the imagery of Zhoushan waters by using the marine aircraft-borne multi-spectral oil spill detector, and also acquired the reflectance spectra of the water and oil film by means of FieldSpec spectroradiometer.The image characteristics and spectral response characteristics were analyzed so as to detect the distribution of the relative thickness using the decision tree classifier. The overall accuracy is 93.7%, which shows that the classification method based on the spectral characteristics could effectively recognize the thick thin sheen oil film and extract the information of marine oil pollution, thus sufficiently satisfying the requirements for monitoring marine oil spill.
A method of segmentation and semi-automated modeling for vehicle-borne light detection and ranging(LiDAR) point cloud data is presented in this paper. Firstly,the LiDAR point cloud data are converted into standard format and sampled sparsely. Then the geometric features of different objects are used to govern the data and model of 3D roads,buildings,trees,power poles and facilities. In view of the imperfection of vehicle-borne LiDAR point cloud data,the vehicle-borne and texture information of aerial image auxiliary is used to build the facade and the top surface of the three-dimensional modeling. Finally,a streetscape is reconstructed by using IP-S2 vehicle-borne LiDAR point cloud data. The results show that the method proposed in this paper is simple and suitable for semi-automatic segmentation of roads and buildings.
The accurate synthetic aperture Radar (SAR) image registration is the prerequisite for exact analysis of mine deformation. Many image registration algorithms have been proposed, but the results are not satisfactory when these registration algorithms are directly applied to SAR image. In view of such a situation, the authors put forward an integrated registration approach in this paper. The first step of this approach is the coarse matching with Canny edge for region division; then the fine matching is performed by SIFT algorithm with improved Canny edge features; finally, the accurate registration SAR image is obtained. This approach has fewer computations than that simply using SIFT feature matching. Experimental analyses with SAR images demonstrate the efficiency and accuracy of this approach for mine SAR image registration, which provides high-quality image data for comprehensive management in mining areas.
The aim of this study is to test the feasibility of soil classification based on remote sensing in a typical area of Qinghai Lake basin. The authors employed TM image and terrain data as main data sources, and used GeoEye-1 high-resolution remote sensing images and soil map as auxiliary data sources. The TM image was processed to extract classification features by using a variety of image processing techniques, which included such means as principal component analysis, tasseled cap transformation, and band math. Supported by ArcGIS9.3 software, the authors detected several topographical features with DEM, such as elevation, slope and aspect. Then, the authors incorporated all classification features into a dataset, and used maximum likelihood classifier of supervision to classify the soil of the test area. The results suggest that the combination of remote sensing image with terrain data can distinguish nine soil subcategories and one non-soil unit. The overall classification accuracy can reach 91.76%.
In order to effectively extract land use/land cover remote sensing information in a wide range of terrain complex area,the authors, taking the transition zone between Tibetan Plateau and the Loess Plateau in eastern Qinghai as the study area,studied the intelligent remote sensing classification of land use/land cover by using ant colony intelligent optimization algorithm(ACIOA)in this paper. Firstly,TM image,digital elevation model,slope and aspect data were selected as characteristic bands for classification. Secondly,the study area was divided into two parts using the normalized difference vegetation index(NDVI)so as to reduce the influence of different objects with the same spectrum. Finally,the classification rules were excavated using ACIOA,by which regional land use/cover information was extracted. The results show that the ACIOA classification of multi-character data based on vegetation partition is superior to the traditional remote sensing classification. The overall accuracy of the classification and the Kappa coefficient of ACIOA with multi-character data based on vegetation partition is 88.85% and 0.86 respectively. Therefore,this study provides an effective way for extracting land use/land cover information in large-area complex terrain.
Modeling using empirical methods based on Hyperion is a fast and accurate way to retrieve vegetation chlorophyll content. In this paper,the measured spectra and simulated Hyperion spectra were analyzed,the correlation between chlorophyll content and reflectance with its change forms and the relation between chlorophyll content and red edge parameters as well as vegetation indexes were calculated to obtain the most accurate modeling method. The vegetation index of modified simple ratio(MSR)has a significant correlation with chlorophyll content,and its regression model can retrieve chlorophyll concentration accurately. Using MSR and measured chlorophyll content,the authors built the regression model based on Hyperion data and then established the chlorophyll concentration profile. The chlorophyll concentration profile of Zhangye City was computed and a high-accuracy was achieved,with its relative error less than 5%.
In order to study the spatial and temporal distribution and the change of soil moisture in the lower reaches of the Heihe River Basin, the authors used the MODIS data products and the soil moisture data measured from the field data and adopted the thermal inertia to calculate the apparent thermal inertia (ATI). Then ATI and soil moisture were used to build the experience model by regression analysis. At last the soil moisture in the lower reaches of Heihe River Basin was successfully retrieved by this model. The results indicate that using MODIS products provided by NASA could predigest the retrieval parameters, reduce the complexity of soil moisture retrieval and ensure the application in the large or middle-sized region. The ATI mean of sand is larger than that of loam and clay, the ATI of clay and loam is relatively large and scattered. The ATI mean of the oasis area is larger than that of the gobi and desert area. The proposed thermal inertia model can reliably monitor the soil moisture within the soil depth of 20 cm.
Acquiring urban information and dynamically monitoring urban expansion forms constitute important parts of remote sensing technique in the field of resource and environment application. As a coastal province, Zhejiang has experienced a rapid economic development in the past 20 years. At the same time, its urban expansion phenomenon is significant. With Zhejiang Province as the study area, the authors obtained the spatial distribution information of urban land from Landsat TM data by using the CART algorithm. Under the condition of getting accurate classification results, the urban expansion spatial-temporal features of Zhejiang Province from 1995 to 2010 were analyzed.Applying CART to extracting urban information from TM data and optimized with NTL is an effective and adaptable method for monitoring regional urban expansion.During the past 15 years, the expansion acceleration of most cities is greater than zero, except for Dongtou, Qingyuan, Wencheng, Yunhe, Lanxi, Longquan and Shaoxing. From 1995 to 2010, Xiaoshan, Yuhang, Ningbo remained the first three cities in this aspect.It is shown that the urbanization levels of various cities are significantly different from each other. The urbanization level of coastal cities and cities in the terrain flat area is higher than that of the non-coastal cities and cities in the complicated topography area. As a result, the first three large coastal cities, which are Hangzhou, Shaoxing and Wenzhou, and the zone of small and medium sized cities in the non-costal area around Jinhua have been developed.
In order to evaluate the white roof plan for quantitative alleviation of the urban heat island effect, the authors, adopting Shanghai as a study area and based on remote sensing, obtained the data of roof reflectance. By using Hottel model, the sun sunny hourly irradiance was simulated, and the city's rooftops in the absorption of solar radiation were employed to simulate the process under different values of reflectance. According to the "white roof plan", the authors estimated that the temperature of island intensity in the study area can reduce 1.32 ℃ during the lunch period in summer. In combination with the white roof heat transfer model, the authors also estimated that, in the house with white rooftop in summer, the air conditioning energy efficiency can be up to 12.60%.
The airborne interferometric synthetic aperture Radar (InSAR) is a new technique for generating digital elevation model (DEM) with high accuracy. To generate high precision DEMs in large areas, this paper introduces accurate parameter calibration and bundle adjustment to the pre existing data processing flow of airborne InSAR DEMs generation, and presents a novel method and procedure for massive high precision DEMs generation by using airborne dual-antenna InSAR data of hilly areas, which includes parameter calibration, interferometric processing, bundle adjustment, phase-to-height conversion, geo coding and mosaicking. The airborne InSAR for the topography mapping processing system has been exploited based on the VC++. Some experimental research is presented based on airborne dual-antenna X-band InSAR data of 4 stripes. The authors processed and generated a high precision DEM covering an area of over 500 km2. Several corner reflectors were placed in this area as reference GCPs for the assessment of the accuracy of the generated DEM. The evaluation results in terms of the mean square error (MSE) were derived by comparing the generated InSAR DEM with the reference GCPs. The MSE of the point and the height are ±1.188 m and ±0.508 m, respectively. It is concluded that the generated DEM using the proposed method meets the requirements of 1：10 000 terrain mapping. The airborne InSAR system could provide a new technique for topographic mapping in large complex areas.
Overexploitation of groundwater is the major factor responsible for ground subsidence in many areas. The development of the SAR Interferometry (InSAR) technique provides a powerful tool for revealing the detailed evolution of subsidence with the advantages of large coverage, dense spatial sampling and high temporal frequency. In this study, the authors present an example of complex deformation procedure monitoring by time series analysis of coherent point target with small baseline subsets. Taking Dezhou as the study area, the authors analyzed the subsidence evolution during the period from January 2004 to October 2010 by using the ENVISAT ASAR data. The causes of the seasonal subsidence and rebound were investigated by analyzing the groundwater pumping as well as leveling surveying and weather data. It can be concluded that the continuous overexploitation of the groundwater and the yearly rainfall changes are the major factors responsible for seasonal subsidence and rebound, which result in the close temporal relationship between subsidence and water level changes.
The study of water ice on the moon is related not only to the formation and evolution of the moon but also to the utilization of lunar resources and the problem whether human beings can go into the depth of the universe with the help of the moon. This paper reviewed the progress of lunar water ice exploration and summarized the research status both in China and abroad. The authors analyzed some impact craters in the north moon and discussed whether there exists water ice or not by means of the polarization synthetic aperture Radar,the data of miniature radio frequency(Mini-RF)and the characters of polarization SAR as well as the reflection of water ice. The Mini-RF CPR data analysis reveals that the north-pole of the moon probably contains water ice,but the water quantity and the mode of occurrence require further investigation.
Rockslide is one of the main geological disasters in China.Each rockslide disaster has different characteristics,so its emergency and rescue plans are not identical. The digital elevation model before and after rockslide and the aerial image with 0.35 m resolution were used as the data source. The digital landslide technologies were also adopted to quantitatively interpret such information of the Jiweishan rockslide as scale,topographical change,direction of movement,disaster features and affected limits. The Jiweishan rockslide is a typical multiple huge disaster that experienced a chain reaction consisting of "creep sliding along week layer-burnish surrounding rock-fragment flow-barrier lake". According to the disaster characteristics,the best location of engineering work for buried miners underground was explored by combining the collected layout of the Gonghe iron ore deposit with the results of the remote sensing interpretation for the Jiweishan rockslide. The results obtained by the authors could provide valuable references for the study of rockslide disaster characteristics and emergency rescue engineering using remote sensing technology in the future.
Radial submarine sand ridges are large-sized sandy accumulation bodies in offshore area of northern Jiangsu. Because of their complicated hydrodynamic environment and geomorphology, it is very difficult to obtain the field investigation data. This paper is based on the color and texture reflected on the remote sensing image, Geomorphologic mapping was conducted in combination with the measured terrain data and historical charts as well as the historical geomorphological map. In addition, the spatial characteristics were analyzed. The results show that the use of remote sensing images to draw the geomorphologic map of radial submarine sand ridges can provide practical and reliable scientific basis not only for the study of the geomorphologic structure but also for the development and utilization of spatial resources.
Located in the collision juncture zone between the West Kunlun compound oroganic belt on the northern margin of Tibetan Plateau and the southern margin of Tarim Basin,Kosrap area has favorable ore-forming geological conditions and thus has aroused much attention among geologists; nevertheless, owing to its poor natural conditions and poor accessibility,it is very difficult to obtain important geological and ore-prospecting information with tranditional geological investigation methods. Practice shows that the increasingly mature remote sensing technology can well make up for the shortage. With Kosrap as the study area and ETM+ image as the data source, various kinds of methods, such as ratio method,data masking,principal component analysis and density segmentation, could be utilized in an integrated way in the ENVI software environment to process the data and extract the near-ore wall rock alteration information in the study area. Then the extracted remote sensing alteration information could be analyzed by stacking the existing ore spot information and geochemical anomalies in the study area. The results show that these methods are effective in obtaining hydroxy alteration information in the study area, and the results can provide the basis for further large-scale geological prospecting work in the study area.
High spatial and temporal resolution of HJ-1B IRS4 single channel infrared data can meet the need of the sea water temperature in Daya Bay where strong variability of the temperature is obvious in time and space. Based on the common HJ-1B IRS4 sea surface temperature retrieval algorithms and numerical differential methods, the authors carried out sensitivity analysis of the influence of the temperature retrieval error, which included the total water content in the atmosphere, the observation angle and the emissivity. Combined with the actual situation of Daya Bay nuclear power plants and based on the single window algorithm for temperature retrieval model, the authors employed the HJ-1B IRS4 thermal infrared data of December 18, 2011 and December 22, 2011 around Daya Bay,the corresponding CE312 real measured infrared radiation temperature data and meteorological observation data and, through the least square method and the linear regression method, revised parameters a and b of the retrieval model, with the corresponding amendatory value being 1 163.4 and -4.013 4 respectively. Two years' HJ-1B IRS4 single channel infrared data of 2010 and 2011 were utilized to monitor thermal discharge in Daya Bay nuclear power plants. The results provide a basis for further dynamic monitoring application of thermal discharge in Daya Bay nuclear power plants by using HJ-1B IRS4 thermal infrared data.
Using IDL and based on the VIRR and MWHS instruments on the FY-3 satellite, the authors developed a software called "FY-3 microwave humidity 3D visualization display". According to different monitoring periods, the software can automatically generate a series of pictures composed by VIRR B6,B2,B1 and microwave humidity distribution at 4 different altitudes (ground, 850 hPa, 500 hPa and 300 hPa) from MWHS (day), or can generate a series of pictures from black body temperture(TBB) of VIRR B5 and microwave humidity distribution at 4 different altitudes from MWHS (night). The utilization of this software in tropical cyclone‘SOALA’and rainfall monitoring shows that the 3D visualization, which combines and strengthens the advantages from VIRR and MWHS data on FY-3, is simple and easy to understand. The software can be a useful means in monitoring and warning of severe weathers such as tropical cyclone and rainfall.
Snow depth is an important parameter to characterize snow features, and is also one of the sensitive factors of regional response to climate change. Based on snow depth daily data and monthly temperature, precipitation, wind and sunshine hours data from meteorological stations during 1979 to 2010, the authors analyzed the spatial and temporal variation of snow depth in Tibetan Plateau and its response to climatic change by using methods of anomaly analysis, mutation analysis, spatial analysis and power spectral analysis. The results showed that, in the period from 1979 to 2010, the snow depth increased obviously and significantly with linear trend rate 0.26 cm/10a, but there was a pronounced decrease phase from 1999 to 2010, thus forming the situation that the snow depth increased first and then decreased in general in Tibetan Plateau. In the four seasons, winter mean snow depth contributed most significantly to the annual situation, with the correlation coefficient between them up to 0.88. The snow depth was extremely excessive in the 1990s but with no climate mutation. An analysis of power spectrum showed that the snow depth had quasi-periodic oscillation of 6-7 years. The results indicated that there were significant spatial differences in the snow depth of Tibetan Plateau. In the peripheral high mountains, snow depth was distributed extensively and had a long duration, but in the vast interior it was rare or even thin. The snow depth was significantly affected by the altitude with a steep step effect.And most of linear trend rates of snow depth in Tibetan Plateau were between -0.08 and 0.08 cm/a, with the percentage reaching 74.6%. The results of regression analysis indicated that the increased area of snow depth accounted for 76.9%, while the decreased area accounted for 23.1%. There was obvious statistical and spatial correlation between snow depth and temperature, precipitation, wind speed and sunshine duration in general; there was negative correlation between snow depth and temperature, wind speed and sunshine duration, but positive correlation between snow depth and precipitation. The results of multiple regression analysis showed that, in spring and autumn, the correlation coefficients between simulated snow depth and observation data were both above 0.6 and passed 0.01 significance test, while they were only between 0.4 and 0.5 in summer and winter and didn't pass the 0.05 significance test.
In order to study the response relationship of the change of the Hoh Xil Lake to the climate change, the authors extracted surface area of the Ulan Ul Lake based on the remote sensing images (Landsat TM/ETM+) from 1970 to 2010, and examined the lake level elevation variations by GLAS/ICESat lase altimeter during the period of 2003-2009. On the basis of the lake area and level elevation extracted from remote sensing data, the variations of water quantity were calculated. SWAT model(soil and water assessment tool)was used to simulate the runoff in the basin of the Ulan Ul Lake from 1970 to 2012. During the simulation, DEM, land-use classification, soil classification and meteorological data served as input data, and the model was calibrated and verified by the variations of water quantity. The results showed that the lake area decreased by 70 km2 from 1970 to 1990, and increased by 129 km2 from 1990 to the present; the correlation coefficient of the simulated and measured data is R2= 0.82. These data suggest that the model is feasible, and the simulation results are in agreement with measured results from remote sensing. The average annual runoff of the Ulan Ul Lake was 103.8 mm, and the peak of runoff occurred from July to September.
Based on landscape ecology, remote sensing and geographical information system, the authors analyzed the dynamic change of landscape pattern of Jiangsu costal wetland from 1992 to 2009. Combining the remote sensing derived information with Pressure-State-Response model, the authors also assessed AHP and Delphi methods, regional ecological security states and change trends. The experimental results show that the size of natural landscape has been reduced, while the manmade landscape tends to increase, accompanied by a transfer from wetland natural landscape to human landscape. The fragmentation degree has been intensified gradually, and the average fractal dimension tends to decrease, as a result of human intervention. The increased Shannon diversity metrics indicates more richness of wetland landscape types, which has resulted from the transfer of natural landscape to manmade landscape. The results also indicate that the wetland ecological system has been in critical security state, and the percentage of ill and insecure areas has been on the increase, so more attention should be paid to the landscape pattern improvement and ecological building.
Using trend analysis and stability analysis methods, the authors studied the dynamic change characteristics of surface vegetation cover in the past 13 years in Bashang Area of Hebei Province based on MODIS data. Some conclusions have been reached: In spatial distribution, the surface vegetation cover of Bashang area became better gradually from west to east and there existed remarkable differences in the seasonal variation features of sub-regions. In time, there was an improving trend in most parts of Bashang Area in the past 13 years, with the improved area accounting for 51.35% of the total area and the basically unchanged area accounting for 25.68%. However, the vegetation growth was easily affected by natural factors and human activities, and its ecological environment was relatively fragile, so the vegetation cover was unstable in the time series, the mean value of MNDVI coefficient of variance (Cv) was 14.85%, and the proportion of the area with Cv<10% was 15.3%.
Spatial database is a spatial information infrastructure, and the efficiency and quality of its construction determine the success or failure of the geo-information project. Currently, the spatial database is mostly associated with a specific GIS platform. The database construction process is complex, inefficient and lack of versatility. In order to adapt the database construction to complex variability, the authors, through an analysis of the structural expression of the spatial database data model, studied and put forward the method for storing data model by using data dictionary and the technology for automatic construction of a spatial database. Practice of quite a few projects has proved that the method can significantly reduce the complexity of building a database and improve efficiency, together with certain extent of versatility.
In order to meet the management and service needs of China's first self-developed high-resolution satellite for earth resources investigation proposed by related land and resources department, the authors designed and developed the C/S-based data management subsystem and the B/S-based data services subsystem of ZY-1 02C, with the propose of spreading the application of ZY-1 02C data relying on the existing hardware and software environment of land and resources field. Functions such as timely storage of mass data, efficient distribution and real-time online inquiries were completed in this system. The study and development of this system can provide basic data protection for spreading utilization of ZY-1 02C data in land and resources field and also lay a theoretical and practical foundation for the subsequent earth resource satellite application system in China which integrates many functions (such as data reception, processing, interpretation, and information sharing service) into one function.