bluuebunny/crossref_metadata_2025 huggingface dataset:
A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring
Authors: Xiao F.
Published: May 2018

Abstract. In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.
FOREST COVER CHANGE ANALYSIS IN INNER MONGOLIA USING REMOTE SENSING DATA
Authors: Xie S. , Gong J. , Huang X.
Published: May 2018

Abstract. Forest is the lung of the earth, and it has important effect on maintaining the ecological balance of the whole earth. This study was conducted in Inner Mongolia during the year 1990–2015. Land use and land cover data were used to obtain forest cover change of Inner Mongolia. In addition, protected area data, road data, ASTER GDEM data were combined with forest cover change data to analyze the relationship between them. Moreover, patch density and landscape shape index were calculated to analyze forest change in perspective of landscape aspect. The results indicated that forest area increased overall during the study period. However, a few cities still had a phenomenon of reduced forest area. Results also demonstrated that the construction of protected area had positive effect on protecting forest while roads may disturbed forest due to human activities. In addition, forest patches in most of cities of Inner Mongolia tended to be larger and less fragmented. This paper reflected forest change in Inner Mongolia objectively, which is helpful for policy making by government.
MAPPING WETLANDS OF DONGTING LAKE IN CHINA USING LANDSAT AND SENTINEL-1 TIME SERIES AT 30M
Authors: Xing L. , Tang X. , Wang H. , Fan W. , Gao X.
Published: May 2018

Abstract. Mapping and monitoring wetlands of Dongting lake using optical sensor data has been limited by cloud cover, and open access Sentinal-1 C-band data could provide cloud-free SAR images with both have high spatial and temporal resolution, which offer new opportunities for monitoring wetlands. In this study, we combined optical data and SAR data to map wetland of Dongting Lake reserves in 2016. Firstly, we generated two monthly composited Landsat land surface reflectance, NDVI, NDWI, TC-Wetness time series and Sentinel-1 (backscattering coefficient for VH and VV) time series. Secondly, we derived surface water body with two monthly frequencies based on the threshold method using the Sentinel-1 time series. Then the permanent water and seasonal water were separated by the submergence ratio. Other land cover types were identified based on SVM classifier using Landsat time series. Results showed that (1) the overall accuracies and kappa coefficients were above 86.6 % and 0.8. (3) Natural wetlands including permanent water body (14.8 %), seasonal water body (34.6 %), and permanent marshes (10.9 %) were the main land cover types, accounting for 60.3 % of the three wetland reserves. Human-made wetlands, such as rice fields, accounted 34.3 % of the total area. Generally, this study proposed a new flowchart for wetlands mapping in Dongting lake by combining multi-source remote sensing data, and the use of the two-monthly composited optical time series effectively made up the missing data due to the clouds and increased the possibility of precise wetlands classification.
INVESTIGATION ON INSAR TIME SERIES DEFORMATION MODEL CONSIDERING RHEOLOGICAL PARAMETERS FOR SOFT CLAY SUBGRADE MONITORING
Authors: Xing X. , Yuan Z. , Chen L. F. , Yu X. Y. , Xiao L.
Published: May 2018

Abstract. The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.
TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS
Authors: Xiong X. , Jin G. , Xu Q. , Zhang H.
Published: May 2018

Abstract. Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.
RESEARCH ON HORIZONTAL ACCURACY METHOD OF HIGH SPATIAL RESOLUTION REMOTELY SENSED ORTHOPHOTO IMAGE
Authors: Xu Y. M. , Zhang J. X. , Yu F. , Dong S.
Published: May 2018

Abstract. At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostly based on a set of testing points with the same accuracy and reliability. However, it is difficult to get a set of testing points with the same accuracy and reliability in the areas where the field measurement is difficult and the reference data with high accuracy is not enough. So it is difficult to test and evaluate the horizontal accuracy of the orthophoto image. The uncertainty of the horizontal accuracy has become a bottleneck for the application of satellite borne high-resolution remote sensing image and the scope of service expansion. Therefore, this paper proposes a new method to test the horizontal accuracy of orthophoto image. This method using the testing points with different accuracy and reliability. These points’ source is high accuracy reference data and field measurement. The new method solves the horizontal accuracy detection of the orthophoto image in the difficult areas and provides the basis for providing reliable orthophoto images to the users.
EIGENENTROPY BASED CONVOLUTIONAL NEURAL NETWORK BASED ALS POINT CLOUDS CLASSIFICATION METHOD
Authors: Xu Z. , Yang Z.
Published: May 2018

Abstract. The classification of point clouds is the first step in the extraction of various types of geo-information form point clouds. Recently the ISPRS WG II/4 provides a benchmark on 3D semantic labelling, a convolutional neural network based method achieves the best overall accuracy performance in all participants who only use the geometrical and waveform based features extracted from the ALS data. Features of the point are calculated in different scales to achieve the best performance. It is not efficiency for the future use. In this paper, we use an eigenentropy based scale selection strategy to improve this method. The scale selection strategy improves the average F1 score and makes the classification method more simple and efficient.
SEMANTIC SEGMENTATION OF CONVOLUTIONAL NEURAL NETWORK FOR SUPERVISED CLASSIFICATION OF MULTISPECTRAL REMOTE SENSING
Authors: Xue L. , Liu C. , Wu Y. , Li H.
Published: May 2018

Abstract. Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.
INFLUENCE OF SKY CONDITIONS ON ESTIMATION OF PHOTOSYNTHETIC PHOTON FLUX DENSITY FOR AGRICULTURAL ECOSYSTEM
Authors: Yamashita M. , Yoshimura M.
Published: May 2018

Abstract. Photosynthetic photon flux density (PPFD: µmol m−2 s−1) is indispensable for plant physiology processes in photosynthesis. However, PPFD is seldom measured, so that PPFD has been estimated by using solar radiation (SR: W m−2) measured in world wide. In method using SR, there are two steps: first to estimate photosynthetically active radiation (PAR: W m−2) by the fraction of PAR to SR (PF) and second: to convert PAR to PPFD using the ratio of quanta to energy (Q / E: µmol J−1). PF and Q/E usually have been used as the constant values, however, recent studies point out that PF and Q / E would not be constants under various sky conditions. In this study, we use the numeric data of sky-conditions factors such cloud cover, sun appearance/hiding and relative sky brightness derived from whole-sky image processing and examine the influences of sky-conditions factors on PF and Q / E of global and diffuse PAR. Furthermore, we discuss our results by comparing with the existing methods.
THE IMPACTS OF TYPICAL DROUGHT EVENTS ON TERRESTRIAL VEGETATION IN CHINA
Authors: Yang J. , Wu J. , Zhou H. , Han X.
Published: May 2018

Abstract. In our study, according to the statistical results of standardized precipitation evapotranspiration index (SPEI), we chose two drought events which occurred in the North China during 2001 and in the Southwest China from 2009 to 2010. And two of the Global Land Surface Satellite (GLASS) products had been used to evaluate the impacts of drought on vegetation, including the leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR). The results show that: (1) In the development process of a drought event, the anomaly of remote sensing parameters (LAI and FAPAR) usually falls firstly and then rises as the drought changes from moderate to severe and then to moderate. This indicates that the effects of drought on vegetation remote sensing parameters are closely related to the severity of drought disaster. (2) The response of different vegetation types to the drought disaster is different. Compared with the forests, the response of grasslands to drought disaster is earlier. For example, the duration affected by drought disaster in grassland is longer 1/3 than the forests in the Southwest China. (3) Irrigation is an effective measure to mitigate the effects of drought. Irrigated croplands are less affected by drought than non-irrigated croplands and grasslands. In the North China, the decrease amplitude of irrigated croplands’ remote sensing parameters is about half of non-irrigated croplands’.
THE LOW BACKSCATTERING OBJECTS CLASSIFICATION IN POLSAR IMAGE BASED ON BAG OF WORDS MODEL USING SUPPORT VECTOR MACHINE
Authors: Yang L. , Shi L. , Li P. , Yang J. , Zhao L. , Zhao B.
Published: May 2018

Abstract. Due to the forward scattering and block of radar signal, the water, bare soil, shadow, named low backscattering objects (LBOs), often present low backscattering intensity in polarimetric synthetic aperture radar (PolSAR) image. Because the LBOs rise similar backscattering intensity and polarimetric responses, the spectral-based classifiers are inefficient to deal with LBO classification, such as Wishart method. Although some polarimetric features had been exploited to relieve the confusion phenomenon, the backscattering features are still found unstable when the system noise floor varies in the range direction. This paper will introduce a simple but effective scene classification method based on Bag of Words (BoW) model using Support Vector Machine (SVM) to discriminate the LBOs, without relying on any polarimetric features. In the proposed approach, square windows are firstly opened around the LBOs adaptively to determine the scene images, and then the Scale-Invariant Feature Transform (SIFT) points are detected in training and test scenes. The several SIFT features detected are clustered using K-means to obtain certain cluster centers as the visual word lists and scene images are represented using word frequency. At last, the SVM is selected for training and predicting new scenes as some kind of LBOs. The proposed method is executed over two AIRSAR data sets at C band and L band, including water, bare soil and shadow scenes. The experimental results illustrate the effectiveness of the scene method in distinguishing LBOs.
RESERCH ON SPATIAL AND TEMPORAL DISTRIBUTION OF COLOR STEEL BUILDING BASED ON MULTI-SOURCE HIGH-RESOLUTION SATELLITE IMAGERY
Authors: Yang S. W. , Ma J. J. , Wang J. M.
Published: May 2018

Abstract. As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city’s image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building’s special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.
AUTOMATIC EXTRACTION OF ROAD MARKINGS FROM MOBILE LASER-POINT CLOUD USING INTENSITY DATA
Authors: Yao L. , Chen Q. , Qin C. , Wu H. , Zhang S.
Published: May 2018

Abstract. With the development of intelligent transportation, road’s high precision information data has been widely applied in many fields. This paper proposes a concise and practical way to extract road marking information from point cloud data collected by mobile mapping system (MMS). The method contains three steps. Firstly, road surface is segmented through edge detection from scan lines. Then the intensity image is generated by inverse distance weighted (IDW) interpolation and the road marking is extracted by using adaptive threshold segmentation based on integral image without intensity calibration. Moreover, the noise is reduced by removing a small number of plaque pixels from binary image. Finally, point cloud mapped from binary image is clustered into marking objects according to Euclidean distance, and using a series of algorithms including template matching and feature attribute filtering for the classification of linear markings, arrow markings and guidelines. Through processing the point cloud data collected by RIEGL VUX-1 in case area, the results show that the F-score of marking extraction is 0.83, and the average classification rate is 0.9.
A STUDY OF CO-PLANING TECHNOLOGY OF SPACEBORNE, AIRBORNE AND GROUND REMOTE SENSING DETECTING RESOURCE, DRIVEN BY DISASTER EMERGENCY TASK
Authors: Yu F. , Chen H. , Tu K. , Wen Q. , He J. , Gu X. , Wang Z.
Published: May 2018

Abstract. Facing the monitoring needs of emergency responses to major disasters, combining the disaster information acquired at the first time after the disaster and the dynamic simulation result of the disaster chain evolution process, the overall plan for coordinated planning of spaceborne, airborne and ground observation resources have been designed. Based on the analysis of the characteristics of major disaster observation tasks, the key technologies of spaceborne, airborne and ground collaborative observation project are studied. For different disaster response levels, the corresponding workflow tasks are designed. On the basis of satisfying different types of disaster monitoring demands, the existing multi-satellite collaborative observation planning algorithms are compared, analyzed, and optimized.
WATER LEAKAGE DIAGNOSIS IN METRO TUNNELS BY INTERGRATION OF LASER POINT CLOUD AND INFRARED THERMAL IMAGING
Authors: Yu P. , Wu H. , Liu C. , Xu Z.
Published: May 2018

Abstract. Diagnosis of water leakage in metro tunnels is of great significance to the metro tunnel construction and the safety of metro operation. A method that integrates laser scanning and infrared thermal imaging is proposed for the diagnosis of water leakage. The diagnosis of water leakage in this paper is mainly divided into two parts: extraction of water leakage geometry information and extraction of water leakage attribute information. Firstly, the suspected water leakage is obtained by threshold segmentation based on the point cloud of tunnel. And the real water leakage is obtained by the auxiliary interpretation of infrared thermal images. Then, the characteristic of isotherm outline is expressed by solving Centroid Distance Function to determine the type of water leakage. Similarly, the location of leakage silt and the direction of crack are calculated by finding coordinates of feature points on Centroid Distance Function. Finally, a metro tunnel part in Shanghai was selected as the case area to make experiment and the result shown that the proposed method in this paper can be used to diagnosis water leakage disease completely and accurately.
RESEARCH ON REMOTE SENSING IMAGE CLASSIFICATION BASED ON FEATURE LEVEL FUSION
Authors: Yuan L. , Zhu G.
Published: May 2018

Abstract. Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.
PRELIMINARY STUDY ON EARTHQUAKE SURFACE RUPTURE EXTRACTION FROM UAV IMAGES
Authors: Yuan X. , Wang X. , Ding X. , Wu X. , Dou A. , Wang S.
Published: May 2018

Abstract. Because of the advantages of low-cost, lightweight and photography under the cloud, UAVs have been widely used in the field of seismic geomorphology research in recent years. Earthquake surface rupture is a typical seismic tectonic geomorphology that reflects the dynamic and kinematic characteristics of crustal movement. The quick identification of earthquake surface rupture is of great significance for understanding the mechanism of earthquake occurrence, disasters distribution and scale. Using integrated differential UAV platform, series images were acquired with accuracy POS around the former urban area (Qushan town) of Beichuan County as the area stricken seriously by the 2008 Wenchuan Ms8.0 earthquake. Based on the multi-view 3D reconstruction technique, the high resolution DSM and DOM are obtained from differential UAV images. Through the shade-relief map and aspect map derived from DSM, the earthquake surface rupture is extracted and analyzed. The results show that the surface rupture can still be identified by using the UAV images although the time of earthquake elapse is longer, whose middle segment is characterized by vertical movement caused by compression deformation from fault planes.
ANALYSIS OF DYNAMIC CHANGEOF HONG JIANNAO LAKE BASED ON SCALED SOIL MOISTURE MONITORING INDEX
Authors: Yue H. , Liu Y.
Published: May 2018

Abstract. to climate change and human activities, Hong Jiannao Lake located in the arid and semi-arid area of China, it played a very important role in the regulation of the local climate, the balance of water resources and the maintenance of biological diversity. Hongjiannao Lake area in recent years continues to shrink, it was urgent to get the Hongjiannao Lake area change trend. This article take Hongjiannao Lake as study object using MODIS image of NIR and Red wavelength reflectivity data, selected April to October of 2000-2014,consturcted scale of SMMI (S-SMMI) based on soil moisture monitoring index (SMMI). The result indicated that lake area reduced from 46.9 km2 in 2000 to 27.8 km2 in 2014, average decay rate is 1.3 km2/a. The lake’s annual change showed a trend of periodic change. In general, the lake area began to increase slowly each year in April, and the area of the lake area reached the maximum, and then decreased gradually in June to July. Finally, we analysed the main driving factors included natural, man-made, and underground mining which lead to the lake area shrink.
OPTIMAL INFORMATION EXTRACTION OF LASER SCANNING DATASET BY SCALE-ADAPTIVE REDUCTION
Authors: Zang Y. , Yang B.
Published: May 2018

Abstract. 3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.
MONITORING OF THE GROUND FISSURE ACTIVITY WITHIN YUNCHENG BASIN BY TIME SERIES INSAR
Authors: Zhang F. , Yang C. S. , Zhao C. Y. , Liu R. C.
Published: May 2018

Abstract. Yuncheng area is one of the most extensive distributions of ground fissures in Shanxi basin, especially in Yanhu District of Yuncheng, the disaster of ground fissures and ground subsidence are the most serious. According to previous studies, the development and distribution of the ground fissures in this area are mainly controlled by the underlying active faults. In order to provide a better understanding of the formation mechanism, the deformation of ground fissures and its surrounding environment should be taken into consideration. In this paper, PS-InSAR technology was employed to assess the time-series ground deformation of Yuncheng ground fissures and its surrounding area with X-band TerraSAR images from 2013 to 2015. The interaction between ground fissures activity and land subsidence, groundwater, precipitation and surrounding faults will be discussed.
EXTRACTING 3D SEMANTIC INFORMATION FROM VIDEO SURVEILLANCE SYSTEM USING DEEP LEARNING
Authors: Zhang J. S. , Cao J. , Mao B. , Shen D. Q.
Published: May 2018

Abstract. At present, intelligent video analysis technology has been widely used in various fields. Object tracking is one of the important part of intelligent video surveillance, but the traditional target tracking technology based on the pixel coordinate system in images still exists some unavoidable problems. Target tracking based on pixel can’t reflect the real position information of targets, and it is difficult to track objects across scenes. Based on the analysis of Zhengyou Zhang's camera calibration method, this paper presents a method of target tracking based on the target's space coordinate system after converting the 2-D coordinate of the target into 3-D coordinate. It can be seen from the experimental results: Our method can restore the real position change information of targets well, and can also accurately get the trajectory of the target in space.
POSSIBILITY OF CLOUDLESS OPTICAL REMOTE SENSING IMAGES ACQUISITION STUDY BY USING METEOROLOGICAL SATELLITE OBSERVATIONS
Authors: Zhang T. , Lei B. , Hu Y. , Liu K. , Gan Y.
Published: May 2018

Abstract. Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.
RESEARCH ON THE DIRECT CARBON EMISSION FORECAST OF CHINA'S PROVINCIAL RESIDENTS BASED ON NEURAL NETWORK
Authors: Zhang T. , Zhou B. , Zhou S. , Yan W.
Published: May 2018

Abstract. Global climate change, which mainly effected by human carbon emissions, would affect the regional economic, natural ecological environment, social development and food security in the near future. It’s particularly important to make accurate predictions of carbon emissions based on current carbon emissions. This paper accounted out the direct consumption of carbon emissions data from 1995 to 2014 about 30 provinces (the data of Tibet, Hong Kong, Macao and Taiwan is missing) and the whole of China. And it selected the optimal models from BP, RBF and Elman neural network for direct carbon emission prediction, what aim was to select the optimal prediction method and explore the possibility of reaching the peak of residents direct carbon emissions of China in 2030. Research shows that: 1) Residents’ direct carbon emissions per capita of all provinces showed an upward trend in 20 years. 2) The accuracy of the prediction results by Elman neural network model is higher than others and more suitable for carbon emission data projections. 3) With the situation of residents’ direct carbon emissions free development, the direct carbon emissions will show a fast to slow upward trend in the next few years and began to flatten after 2020, and the direct carbon emissions of per capita will reach the peak in 2032. This is also confirmed that China is expected to reach its peak in carbon emissions by 2030 in theory.
A LANDMARK EXTRACTION METHOD ASSOCIATED WITH GEOMETRIC FEATURES AND LOCATION DISTRIBUTION
Authors: Zhang W. , Li J. , Wang Y. , Xiao Y. , Liu P. , Zhang S.
Published: May 2018

Abstract. Landmark plays an important role in spatial cognition and spatial knowledge organization. Significance measuring model is the main method of landmark extraction. It is difficult to take account of the spatial distribution pattern of landmarks because that the significance of landmark is built in one-dimensional space. In this paper, we start with the geometric features of the ground object, an extraction method based on the target height, target gap and field of view is proposed. According to the influence region of Voronoi Diagram, the description of target gap is established to the geometric representation of the distribution of adjacent targets. Then, segmentation process of the visual domain of Voronoi K order adjacent is given to set up target view under the multi view; finally, through three kinds of weighted geometric features, the landmarks are identified. Comparative experiments show that this method has a certain coincidence degree with the results of traditional significance measuring model, which verifies the effectiveness and reliability of the method and reduces the complexity of landmark extraction process without losing the reference value of landmark.
ERROR ANALYSIS AND VALIDATION FOR INSAR HEIGHT MEASUREMENT INDUCED BY SLANT RANGE
Authors: Zhang X. , Li T. , Fan W. , Geng X.
Published: May 2018

Abstract. InSAR technique is an important method for large area DEM extraction. Several factors have significant influence on the accuracy of height measurement. In this research, the effect of slant range measurement for InSAR height measurement was analysis and discussed. Based on the theory of InSAR height measurement, the error propagation model was derived assuming no coupling among different factors, which directly characterise the relationship between slant range error and height measurement error. Then the theoretical-based analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of slant range error to height measurement. In addition, the simulation validation of InSAR error model induced by slant range was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were further discussed and evaluated.
TWO-DIMENSIONAL LOESS LANDSLIDE DEFORMATION MONITORING WITH MULTIDIMENSIONAL SMALL BASELINE SUBSET (MSBAS) – A CASE STUDY OF XINYUAN No.2 LANDSLIDE, GANSU, CHINA
Authors: Zhao C. Y. , Liu X. J. , Zhu W. , Zhu W. F.
Published: May 2018

Abstract. The deformation monitoring of active landslides is of great importance for the safety of human lives and properties. And twodimensional deformation result can give us more thoughts on the landslide type and deformation process. In this study, multidimensional small baseline subsets (MSBAS) technique is introduced and tested to compute two-dimensional deformation rate and time series for both east-west and vertical deformation of Xinyuan No.2 landslide by simultaneously processing ascending and descending TerraSAR-X data acquired from January 2016 to November 2016. Results show not only the spatiotemporal characteristics of this landslides, but the retrogressive loess landslide failure mode is revealed for the first time with the two-dimensional deformation.
STUDY ON THE SPECTRAL MIXING MODEL FOR MINERAL PIGMENTS BASED ON DERIVATIVE OF RATIO SPECTROSCOPY-TAKE VERMILION AND STONE YELLOW FOR EXAMPLE
Authors: Zhao H. , Hao Y. , Liu X. , Hou M. , Zhao X.
Published: May 2018

Abstract. Hyperspectral remote sensing is a completely non-invasive technology for measurement of cultural relics, and has been successfully applied in identification and analysis of pigments of Chinese historical paintings. Although the phenomenon of mixing pigments is very usual in Chinese historical paintings, the quantitative analysis of the mixing pigments in the ancient paintings is still unsolved. In this research, we took two typical mineral pigments, vermilion and stone yellow as example, made precisely mixed samples using these two kinds of pigments, and measured their spectra in the laboratory. For the mixing spectra, both fully constrained least square (FCLS) method and derivative of ratio spectroscopy (DRS) were performed. Experimental results showed that the mixing spectra of vermilion and stone yellow had strong nonlinear mixing characteristics, but at some bands linear unmixing could also achieve satisfactory results. DRS using strong linear bands can reach much higher accuracy than that of FCLS using full bands.
APPLICABILITY ASSESSMENT OF UAVSAR DATA IN WETLAND MONITORING: A CASE STUDY OF LOUISIANA WETLAND
Authors: Zhao J. , Niu Y. , Lu Z. , Yang J. , Li P. , Liu W.
Published: May 2018

Abstract. Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.
DISCUSSION ON HEIGHT SYSTEMS IN STEREOSCOPIC MAPPING USING THE ZY-3 SATELLITE IMAGES
Authors: Zhao L. , Fu X. , Zhu G. , Zhang J. , Han C. , Cheng L.
Published: May 2018

Abstract. The ZY-3 is the civil high-resolution optical stereoscopic mapping satellite independently developed by China. It is mainly used for 1 : 50,000 scale topographic mapping. One of the distinguishing features of the ZY-3 is that the panchromatic triplet camera can obtain thousands of kilometers of continuous strip stereo data. The working mode is suitable for wide-range stereoscopic mapping, in particular global DEM extraction. The ZY-3 constellation is operated in a sun-synchronous at an altitude 505 km, with a 10:30 AM equator crossing time and a 29-day revisiting period. The panchromatic triplet sensors have excellent base-to-height ratio, which is advantageous for obtaining good mapping accuracy. In this paper the China quasi-geoid, EGM2008 and the height conversion method are discussed. It is pointed out that according to the current surveying and mapping specifications, almost all maps and charts use mean sea level for elevation. Experiments on bundle adjustment and DEM extraction with different height systems have been carried out in Liaoning Province of China. The results show that the similar accuracy can be obtained using different elevation system. According to the principle of geodesy and photogrammetry, it is recommended to use ellipsoidal height for satellite photogrammetric calculation and use the orthometric height in mapping production.
THE LAND-USE AND LAND-COVER CHANGE ANALYSIS IN BEIJING HUAIROU IN LAST TEN YEARS
Authors: Zhao Q. , Liu G. , Tu J. , Wang Z.
Published: May 2018

Abstract. With eCognition software, the sample-based object-oriented classification method is used. Remote sensing images in Huairou district of Beijing had been classified using remote sensing images of last ten years. According to the results of image processing, the land use types in Huairou district of Beijing were analyzed in the past ten years, and the changes of land use types in Huairou district were obtained, and the reasons for its occurrence were analyzed.
STUDY ON DESERTIFICATION MONITORING FROM 2000 TO 2014 AND ITS DRIVING FACTORS THROUGH REMOTE SENSING IN NINGXIA，CHINA
Authors: Zhao Z. , Wu Q.
Published: May 2018

Abstract. Due to the implementation of national policy, the desertification in Ningxia has been gradually reduced, but the overall situation of desertification is still serious. Rainfall Use Efficiency(RUE) can make some improvement to the problem that the precipitation has a great influence on vegetation in arid area and fully reflect the dynamic characteristics of desertification. Using the MOD13Q1 data, land use classification map, as well as non-remote sensing data such as meteorological data and social statistics data, the paper carries out the evaluation of the status of desertification based on RUE through spatial trend analysis, gravity center migration model. The driving factors of desertification are quantitatively analyzed by using grey relational analysis. Our study demonstrated that RUE in most parts of Ningxia showed a trend of improvement, mainly located in central and southern Ningxia. The area where desertification occurred from 2000 to 2014 accounted for 7.79 %, mainly distributed in Helan Mountain, Liupan Mountain, Yinchuan Central. The proportion of desertification decreased gradually from 2005 to 2014, and the center of gravity of desertification had a tendency to migrate to northern Ningxia. By analyzing the driving factors, RUE had negative correlations with precipitation and relative humidity and there was no significant correlation between RUE and average temperature and sunshine hours. RUE was positively correlated with GDP, grain yield and number of sheep. On the basis of the results of grey relational analysis, it was found that sunshine hours, average temperature, relative humidity, population were the main influencing factors of desertification.
RESEARCH ON AIRCRAFT TARGET DETECTION ALGORITHM BASED ON IMPROVED RADIAL GRADIENT TRANSFORMATION
Authors: Zhao Z. M. , Gao X. M. , Jiang D. N. , Zhang Y. Q.
Published: May 2018

Abstract. Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied，and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.
TYPICAL APPLICATIONS OF AIRBORNE LIDAR TECHNOLAGY IN GEOLOGICAL INVESTIGATION
Authors: Zheng X. , Xiao C.
Published: May 2018

Abstract. The technology of airborne light detection and ranging (LiDAR), also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover) with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.
IMPROVEMENT ON TIMING ACCURACY OF LIDAR FOR REMOTE SENSING
Authors: Zhou G. , Huang W. , Zhou X. , Huang Y. , He C. , Li X. , Zhang L.
Published: May 2018

Abstract. The traditional timing discrimination technique for laser rangefinding in remote sensing, which is lower in measurement performance and also has a larger error, has been unable to meet the high precision measurement and high definition lidar image. To solve this problem, an improvement of timing accuracy based on the improved leading-edge timing discrimination (LED) is proposed. Firstly, the method enables the corresponding timing point of the same threshold to move forward with the multiple amplifying of the received signal. Then, timing information is sampled, and fitted the timing points through algorithms in MATLAB software. Finally, the minimum timing error is calculated by the fitting function. Thereby, the timing error of the received signal from the lidar is compressed and the lidar data quality is improved. Experiments show that timing error can be significantly reduced by the multiple amplifying of the received signal and the algorithm of fitting the parameters, and a timing accuracy of 4.63 ps is achieved.
MONITORING THE DEFORMATION OF HIGH-RISE BUILDINGS IN SHANGHAI LUIJIAZUI ZONE BY TOMO-PSINSAR
Authors: Zhou L. F. , Ma P. F. , Xia Y. , Xie C. H.
Published: May 2018

Abstract. In this study, we utilize a Tomography-based Persistent Scatterers Interferometry (Tomo-PSInSAR) approach for monitoring the deformation performances of high-rise buildings, i.e. SWFC and Jin Mao Tower, in Shanghai Lujiazui Zone. For the purpose of this study, we use 31 Stripmap acquisitions from TerraSAR-X missions, spanning from December 2009 to February 2013. Considering thermal expansion, creep and shrinkage are two long-term movements that occur in high-rise buildings with concrete structures, we use an extended 4-D SAR phase model, and three parameters (height, deformation velocity, and thermal amplitude) are estimated simultaneously. Moreover, we apply a two-tier network strategy to detect single and double PSs with no need for preliminary removal of the atmospheric phase screen (APS) in the study area, avoiding possible error caused by the uncertainty in spatiotemporal filtering. Thermal expansion is illustrated in the thermal amplitude map, and deformation due to creep and shrinkage is revealed in the linear deformation velocity map. The thermal amplitude map demonstrates that the derived thermal amplitude of the two high-rise buildings both dilate and contract periodically, which is highly related to the building height due to the upward accumulative effect of thermal expansion. The linear deformation velocity map reveals that SWFC is subject to deformation during the new built period due to creep and shrinkage, which is height-dependent movements in the linear velocity map. It is worth mention that creep and shrinkage induces movements that increase with the increasing height in the downward direction. In addition, the deformation rates caused by creep and shrinkage are largest at the beginning and gradually decrease, and at last achieve a steady state as time goes infinity. On the contrary, the linear deformation velocity map shows that Jin Mao Tower is almost stable, and the reason is that it is an old built building, which is not influenced by creep and shrinkage as the load is relaxed and dehydration proceeds. This study underlines the potential of the Tomo-PSInSAR solution for the monitoring deformation performance of high-rise buildings, which offers a quantitative indicator to local authorities and planners for assessing potential damages.
THE MONITORING AND SPATIAL-TEMPORAL EVOLUTION CHARACTERISTIC ANALYSIS FOR LAND SUBSIDENCE IN BEIJING
Authors: Zhou Q. , Zhao W. , Yu J.
Published: May 2018

Abstract. At present the land subsidence has been the main geological disaster in the plain area of China, and became one of the most serious disaster that restrict the social and economic sustainable development, it also is an important content in the project of national geographic conditions monitoring. With the development of economy and society, Beijing as the capital of China has experienced significant population growth in the last few decades which led to over-exploitation of the ground water to meet the water demand of more than 20 million inhabitants, especially in the urban region with high population density. However, the rainfall and surface runoff can’t satisfy the need of aquifer recharge that product the land subsidence. As China’s political center and a metropolis, there are a lot of large constructions, underground traffic projects and complicated municipal pipeline network, and Beijing is also an important traffic hub for national railway and highway network, all of them would be threatened by the land subsidence disaster. In this article the author used twenty ENVISAT Synthetic Aperture Radar (SAR) images acquired in 2008 June–2010 August and ten TerraSAR images acquired in 2011 June–2012 September were processed with Small Baseline Subset SAR Interferometry (SBAS-InSAR) techniques, to investigate spatial and temporal patterns of land subsidence in the urban area of Beijing.