bluuebunny/crossref_metadata_2025 huggingface dataset:
A HYPERSPECTRAL IMAGE CLASSIFICATION METHOD USING ISOMAP AND RVM
Authors: Chang H. , Wang T. , Fang H. , Su Y.
Published: April 2018

Abstract. Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes’ ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.
POLARIMETRIC CALIBRATION AND ASSESSMENT OF GF-3 IMAGES IN STEPPE
Authors: Chang Y. , Yang J. , Li P. , Shi L. , Zhao L.
Published: April 2018

Abstract. The GaoFen-3 (GF-3) satellite is the first fully polarimetric synthetic aperture radar (PolSAR) satellite in China. It has three fully polarimetric imaging modes and is available for many applications. The system has been taken on several calibration experiments after the launch in Inner Mongolia by the Institute of Electronics, Chinese Academy of Sciences (IECAS), and the polarimetric calibration (PolCAL) strategy of GF-3 are also improved. Therefore, it is necessary to assess the image quality before any further applications. In this paper, we evaluated the polarimetric residual errors of GF-3 images that acquired in July 2017 in a steppe site. The results shows that the crosstalk of these images varies from −36 dB to −46 dB, and the channel imbalance varies from −0.43 dB to 0.55 dB with angle varying from −1.6 to 3.6 degree. We also made a PolCAL experiment to restrain the polarimetric distortion afterwards, and the polarimetric quality of the image got better after the PolCAL processing.
ANALYSIS OF THE TONLE SAP FLOOD PULSE BASED ON REMOTE SENSING: HOW MUCH DOES TONLE SAP LAKE AFFECT THE MEKONG RIVER FLOOD?
Authors: Qu W. , Hu N. , Fu J. , Lu J. , Lu H. , Lei T. , Pang Z. , Li X. , Li L.
Published: April 2018

Abstract. The economic value of the Tonle Sap Lake Floodplain to Cambodia is among the highest provided to a nation by a single ecosystem around the world. The flow of Mekong River is the primary factor affecting the Tonle Sap Lake Floodplain. The Tonle Sap Lake also plays a very important role in regulating the downstream flood of Mekong River. Hence, it is necessary to understand its temporal changes of lake surface and water storage and to analyse its relation with the flood processes of Mekong River. Monthly lake surface and water storage from July 2013 to May 2014 were first monitored based on remote sensing data. The relationship between water surface and accumulative water storage change was then established. In combination with hydrological modelling results of Mekong River Basin, the relation between the lake’s water storage and the runoff of Mekong River was analysed. It is found that the water storage has a sharp increase from September to December and, after reaching its maximum in December, water storage quickly decreases with a 38.8 billion m3 of drop in only half month time from December to January, while it keeps rather stable at a lower level in other months. There is a two months’ time lag between the maximum lake water storage and the Mekong River peak flood, which shows the lake’s huge flood regulation role to downstream Mekong River. It shows that this remote sensing approach is feasible and reliable in quantitative monitoring of data scarce lakes.
STUDY OF AEROSOL OPTICAL PROPERTIES OVER TWO SITES IN THE FOOTHILLS OF THE CENTRAL HIMALAYAS
Authors: Rupakheti D. , Kang S. , Cong Z. , Rupakheti M. , Tripathee L. , Panday A. K. , Holben B.
Published: April 2018

Abstract. Atmospheric aerosol possesses impacts on climate system and ecological environments, human health and agricultural productivity. The environment over Himalayas and Tibetan Plateau region are continuously degraded due to the transport of pollution from the foothills of the Himalayas; mostly the Indo-Gangetic Plain (IGP). Thus, analysis of aerosol optical properties over two sites; Lumbini and Kathmandu (the southern slope of central Himalayas) using AERONET’s CIMEL sun photometer were conducted in this study. Aerosol optical depth (AOD at 500 nm), angstrom exponent (α or AE), volume size distribution (VSD), single scattering albedo (SSA) and asymmetry parameter (AP) were studied for 2013–2014 and the average AOD was found to be: 0.64 ± 0.41 (Lumbini) and 0.45 ± 0.30 (Kathmandu). The average AE was found to be: 1.25 ± 0.24 and 1.26 ± 0.18 respectively for two sites. The relation between AOD and AE was used to discriminate the aerosol types over these sites which indicated anthropogenic, mixed and biomass burning origin aerosol constituted the major aerosol types in Lumbini and Kathmandu. A clear bi-modal distribution of aerosol volume size was observed with highest volume concentration during the post-monsoon season in fine mode and pre-monsoon season in coarse mode (Lumbini) and highest value over both modes during pre-monsoon season in Kathmandu. The single scattering albedo (SSA) and asymmetry parameter (AP) analyses suggested aerosols over the Himalayan foothills sites are dominated by absorbing and anthropogenic aerosols from urban and industrial activities and biomass burning. Long-term studies are essential to understand and characterize the nature of aerosol over this research gap zone.
PROVIDING DATA QUALITY INFORMATION FOR REMOTE SENSING APPLICATIONS
Authors: Albrecht F. , Blaschke T. , Lang S. , Abdulmutalib H. M. , Szabó G. , Barsi Á. , Batini C. , Bartsch A. , Kugler Zs. , Tiede D. , Huang G.
Published: April 2018

Abstract. The availability and accessibility of remote sensing (RS) data, cloud processing platforms and provided information products and services has increased the size and diversity of the RS user community. This development also generates a need for validation approaches to assess data quality. Validation approaches employ quality criteria in their assessment. Data Quality (DQ) dimensions as the basis for quality criteria have been deeply investigated in the database area and in the remote sensing domain. Several standards exist within the RS domain but a general classification – established for databases – has been adapted only recently. For an easier identification of research opportunities, a better understanding is required how quality criteria are employed in the RS lifecycle. Therefore, this research investigates how quality criteria support decisions that guide the RS lifecycle and how they relate to the measured DQ dimensions. Subsequently follows an overview of the relevant standards in the RS domain that is matched to the RS lifecycle. Conclusively, the required research needs are identified that would enable a complete understanding of the interrelationships between the RS lifecycle, the data sources and the DQ dimensions, an understanding that would be very valuable for designing validation approaches in RS.
PRELIMINARY EVALUATION OF GAOFEN-3 POLARIMETRIC AND RADIOMETRIC ACCURACY BY CORNER REFLECTORS IN INNER MONGOLIA
Authors: Shi L. , Ding X. , Li P. , Yang J. , Zhao L. , Yang L. , Chang Y. , Yan L.
Published: April 2018

Abstract. On August 10, 2016, China launched its first C-band full polarimetric radar satellite, named Gaofen-3 (GF-3), for urban and agriculture monitoring, landslide detection, ocean applications, etc. According to the design specification, GF-3 is expected to work at −35 dB crosstalk and 0.5 dB channel imbalance, with less than 10 degree error. The absolute radiometric bias is expected to be less than 1.5 dB in a single scene and 2.0 dB when operating for a long time. To complete the calibration and evaluation, the Institute of Electronics, Chinese Academy Sciences (IECAS) built a test site at Inner Mongolia, and deployed active reflectors (ARs) and trihedral corner reflectors (CRs) to solve and evaluate the hardware distortion. To the best of the authors’ knowledge, the product accuracy of GF-3 has not been comprehensively evaluated in any open publication. The remote sensing community urgently requires a detailed report about the product accuracy and stability, before any subsequent application. From June to August of 2017, IECAS begun its second round ground campaign and deployed 10 CRs to evaluate product distortions. In this paper, we exploit Inner Mongolia CRs to investigate polarimetric and radiometric accuracy of QPSI I Stripmap. Although some CRs found fall into AR side lobe, the rest CRs enable us to preliminarily evaluate the accuracy of some special imaging beams. In the experimental part, the image of July 6, 2017 was checked by 5 trihedral CRs and the integration estimation method demonstrated the crosstalk varying from −42.65 to −32.74 dB, and the channel imbalance varying from −0.21 to 0.47 with phase error from −2.4 to 0.2 degree. Comparing with the theoretical radar cross-section of 1.235 m trihedral CR, i.e. 35 dB, the radiometric error varies about 0.20 ± 0.29 dB in HH channel and 0.40 ± 0.20 dB in VV channel.
PRELIMINARY GAOFEN-3 INSAR DEM ACCURACY ANALYSIS
Authors: Chen Q. , Li T. , Tang X. , Gao X. , Zhang X.
Published: April 2018

Abstract. GF-3 satellite, the first C band and full-polarization SAR satellite of China with spatial resolution of 1 m, was successfully launched in August 2016. We analyze the error sources of GF-3 satellite in this paper, and provide the interferometric calibration model based on range function, Doppler shift equation and interferometric phase function, and interferometric parameters calibrated using the three-dimensional coordinates of ground control points. Then, we conduct the experimental two pairs of images in fine stripmap I mode covering Songshan of Henan Province and Tangshan of Hebei Province, respectively. The DEM data are assessed using SRTM DEM, ICESat-GLAS points, and ground control points database obtained using ZY-3 satellite to validate the accuracy of DEM elevation. The experimental results show that the accuracy of DEM extracted from GF-3 satellite SAR data can meet the requirements of topographic mapping in mountain and alpine regions at the scale of 1 : 50000 in China. Besides, it proves that GF-3 satellite has the potential of interferometry.
AN IMPROVED IMAGE MATCHING METHOD BASED ON SURF ALGORITHM
Authors: Chen S. J. , Zheng S. Z. , Xu Z. G. , Guo C. C. , Ma X. L.
Published: April 2018

Abstract. Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.
INFRARED ROTATION PLANE RADAR CHANGE DETECTION
Authors: Wang Y. , Li J. , Zhang W. , Xiao Y. , Liu P. , Zhang S.
Published: April 2018

Abstract. The existing change detection method mainly stays on the pixel-level, which is very susceptible to light, shadow, etc. And the complex calculation and analysis for each pixel reduce the detection efficiency. Moreover, there is no modeling determination method to initialize standard deviation of each element for existing mixed Gaussian background modeling methods. In this paper, an improved mixed Gaussian background modeling method is proposed, with the use of infrared rotation plane radar. The relationship between the corrected standard deviation of distance and the detection intensity is used to establish the curve of standard deviation of distance with detected intensity. For each data point, the standard deviation is initialized by the value estimated by the change curve, and the detected distance is used to establish the Gaussian mixture background model. The detection effect of the method is discussed and compared with the traditional Gauss background modeling in the experiment, the result shows that it has certain advantages in processing speed, adaptability to change background and accuracy of change detection.
APPLICATION OF INSAR TECHNOLOGY IN GEOGRAPHICAL SITUATION MONITORING
Authors: Wang Y. , Tian Q.
Published: April 2018

Abstract. In this paper, based on the geographical situation monitoring project of the earthquake zone of ludian county, zhaotong city, yunnan province,using the data of the radarsat-2 satellite (time frame is 20140304–20150416), InSAR technology is used to monitor the topography of the earthquake zone(about 420 square kilometers of monitoring area). Through the analysis of topographic deformation results, the scope of the terrain change is obtained, and the application and problems of InSAR technique in topographic geomorphological monitoring are discussed.
APPLICATION OF GIS RAPID MAPPING TECHNOLOGY IN DISASTER MONITORING
Authors: Wang Z. , Tu J. , Liu G. , Zhao Q.
Published: April 2018

Abstract. With the rapid development of GIS and RS technology, especially in recent years, GIS technology and its software functions have been increasingly mature and enhanced. And with the rapid development of mathematical statistical tools for spatial modeling and simulation, has promoted the widespread application and popularization of quantization in the field of geology. Based on the investigation of field disaster and the construction of spatial database, this paper uses remote sensing image, DEM and GIS technology to obtain the data information of disaster vulnerability analysis, and makes use of the information model to carry out disaster risk assessment mapping.Using ArcGIS software and its spatial data modeling method, the basic data information of the disaster risk mapping process was acquired and processed, and the spatial data simulation tool was used to map the disaster rapidly.
STUDY ON BIG DATABASE CONSTRUCTION AND ITS APPLICATION OF SAMPLE DATA COLLECTED IN CHINA'S FIRST NATIONAL GEOGRAPHIC CONDITIONS CENSUS BASED ON REMOTE SENSING IMAGES
Authors: Cheng T. , Zhou X. , Jia Y. , Yang G. , Bai J.
Published: April 2018

Abstract. In the project of China's First National Geographic Conditions Census, millions of sample data have been collected all over the country for interpreting land cover based on remote sensing images, the quantity of data files reaches more than 12,000,000 and has grown in the following project of National Geographic Conditions Monitoring. By now, using database such as Oracle for storing the big data is the most effective method. However, applicable method is more significant for sample data’s management and application. This paper studies a database construction method which is based on relational database with distributed file system. The vector data and file data are saved in different physical location. The key issues and solution method are discussed. Based on this, it studies the application method of sample data and analyzes some kinds of using cases, which could lay the foundation for sample data’s application. Particularly, sample data locating in Shaanxi province are selected for verifying the method. At the same time, it takes 10 first-level classes which defined in the land cover classification system for example, and analyzes the spatial distribution and density characteristics of all kinds of sample data. The results verify that the method of database construction which is based on relational database with distributed file system is very useful and applicative for sample data’s searching, analyzing and promoted application. Furthermore, sample data collected in the project of China's First National Geographic Conditions Census could be useful in the earth observation and land cover’s quality assessment.
POTENTIAL LANDSLIDE EARLY DETECTION NEAR WENCHUAN BY A QUALITATIVELY MULTI-BASELINE DINSAR METHOD
Authors: Dai K. , Chen G. , Xu Q. , Li Z. , Qu T. , Hu L. , Lu H.
Published: April 2018

Abstract. Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.
SPATIO-TEMPORAL CHANGE OF VEGETATION COVERAGE AND ITS DRIVING FORCES BASED ON LANDSAT IMAGES: A CASE STUDY OF CHANGCHUN CITY
Authors: Dong L. , Jiang H. , Yang L.
Published: April 2018

Abstract. Based on the Landsat images in 2006, 2011 and 2015, and the method of dimidiate pixel model, the Normalized Difference Vegetation Index (NDVI) and the vegetation coverage, this paper analyzes the spatio-temporal variation of vegetation coverage in Changchun, China from 2006 to 2015, and investigates the response of vegetation coverage change to natural and artificial factors. The research results show that in nearly 10 years, the vegetation coverage in Changchun dropped remarkably, and reached the minimum in 2011. Moreover, the decrease of maximum NDVI was significant, with a decrease of about 27.43 %, from 2006 to 2015. The vegetation coverage change in different regions of the research area was significantly different. Among them, the vegetation change in Changchun showed a little drop, and it decreased firstly and then increased slowly in Yushu, Nong’an and Dehui. In addition, the temperature and precipitation change, land reclamation all affect the vegetation coverage. In short, the study of vegetation coverage change contributes scientific and technical support to government and environmental protection department, so as to promote the coordinated development of ecology and economy.
ASSESSMENT OF GRASSLAND HEALTH BASED ON SPATIAL INFORMATION TECHNOLOGY IN CHANGJI AUTONOMOUS PREFECTURE, XINJIANG
Authors: Du M. J. , Zheng J. H. , Mu C.
Published: April 2018

Abstract. Based on the “pressure-state-response” (PSR) model, comprehensively applied GIS and RS techniques, 20 evaluation indicators were selected based on pressure, state and response, the entropy weight method was used to determine the weight of each index and build a grassland health evaluation system in Changji Prefecture, Xinjiang. Based on this, evaluation and dynamic analysis of grassland health in Changji Prefecture from 2000 to 2016, using GIS/RS technology, the trend of grassland health status in Changji is analyzed and studied. The results show that: 1) Grassland with low health leveld, lower health level, sub-health level, health level and high health level accounts for 1.46 %,27.67 %,38.35 %,29.21 % and 3.31 % of the total area of Changji. Qitai County, Hutubi County, and Manas County are lower health levels, Jimsar County, Changji City, and Mulei County are at a relatively high level, and Fukang City has a healthy level of health. 2) The level of grassland health in Changji County decreased slightly during the 17 years, accounting for 38.42 % of the total area. The area of 23,87 % showed a stable trend, and the improved area accounted for 37.31 % of the vertical surface area.
SALIENCY-GUIDED CHANGE DETECTION OF REMOTELY SENSED IMAGES USING RANDOM FOREST
Authors: Feng W. , Sui H. , Chen X.
Published: April 2018

Abstract. Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.
BASELINE ERROR ANALYSIS AND EXPERIMENTAL VALIDATION FOR HEIGHT MEASUREMENT OF FORMATION INSAR SATELLITE
Authors: Gao X. , Li T. , Zhang X. , Geng X.
Published: April 2018

Abstract. In this paper, we proposed the stochastic model of InSAR height measurement by considering the interferometric geometry of InSAR height measurement. The model directly described the relationship between baseline error and height measurement error. Then the simulation analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of baseline error to height measurement. Furthermore, the whole emulation validation of InSAR stochastic model 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 fully evaluated.
RESEARCH ON THE CONSTRUCTION OF REMOTE SENSING AUTOMATIC INTERPRETATION SYMBOL BIG DATA
Authors: Gao Y. , Liu R. , Liu J. , Cheng T.
Published: April 2018

Abstract. Remote sensing automatic interpretation symbol (RSAIS) is an inexpensive and fast method in providing precise in-situ information for image interpretation and accuracy. This study designed a scientific and precise RSAIS data characterization method, as well as a distributed and cloud architecture massive data storage method. Additionally, it introduced an offline and online data update mode and a dynamic data evaluation mechanism, with the aim to create an efficient approach for RSAIS big data construction. Finally, a national RSAIS database with more than 3 million samples covering 86 land types was constructed during 2013–2015 based on the National Geographic Conditions Monitoring Project of China and then annually updated since the 2016 period. The RSAIS big data has proven to be a good method for large scale image interpretation and field validation. It is also notable that it has the potential to solve image automatic interpretation with the assistance of deep learning technology in the remote sensing big data era.
TASK AND PROGRESS OF IAEG-SDGS: WGGI IN MONITORING SDGS THROUGH A ‘GEOGRAPHIC LOCATION’ LENS
Authors: Geng W. , Chen J. , Zhang H. P. , Xu K.
Published: April 2018

Abstract. In September 2015, the 193 Member States of the United Nations (UN) unanimously adopted the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs), aiming to transform the world over the next 15 years (ESDN, 2016). To meet the ambitions and demands of the 2030 Agenda, it is necessary for the global indicator framework to adequately and systematically address the issue of alternative data sources and methodologies, including geospatial information and Earth observations in the context of geographic location (UN-GGIM, 2016). For this purpose, the Inter-Agency and Expert Group on Sustainable Development Goals Indicator (IAEG-SDGs) created the Working Group on Geospatial Information (IAEG-SDGs: WGGI) to give full play to the role of geospatial data in SDGs measurement and monitoring. The Working Group reviewed global indicators through a ‘geographic location’ lens to pick out those which geospatial information can significantly support the production, and analyzed the methodological and measurements issues. This paper has discussed the progress in monitoring SDGs ever since the establishment of IAEG-SDGs: WGGI, as well as the existing problems, appropriate solutions and plans for the next stage of work.
PHOTOGRAMMETRIC PROCESSING OF PLANETARY LINEAR PUSHBROOM IMAGES BASED ON APPROXIMATE ORTHOPHOTOS
Authors: Geng X. , Xu Q. , Xing S. , Hou Y. F. , Lan C. Z. , Zhang J. J.
Published: April 2018

Abstract. It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.
THREE-DIMENSIONAL RECONSTRUCTION OF THE VIRTUAL PLANT BRANCHING STRUCTURE BASED ON TERRESTRIAL LIDAR TECHNOLOGIES AND L-SYSTEM
Authors: Gong Y. , Yang Y. , Yang X.
Published: April 2018

Abstract. For the purpose of extracting productions of some specific branching plants effectively and realizing its 3D reconstruction, Terrestrial LiDAR data was used as extraction source of production, and a 3D reconstruction method based on Terrestrial LiDAR technologies combined with the L-system was proposed in this article. The topology structure of the plant architectures was extracted using the point cloud data of the target plant with space level segmentation mechanism. Subsequently, L-system productions were obtained and the structural parameters and production rules of branches, which fit the given plant, was generated. A three-dimensional simulation model of target plant was established combined with computer visualization algorithm finally. The results suggest that the method can effectively extract a given branching plant topology and describes its production, realizing the extraction of topology structure by the computer algorithm for given branching plant and also simplifying the extraction of branching plant productions which would be complex and time-consuming by L-system. It improves the degree of automation in the L-system extraction of productions of specific branching plants, providing a new way for the extraction of branching plant production rules.
CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE
Authors: Gu M. , Lyu S. , Hou M. , Ma S. , Gao Z. , Bai S. , Zhou P.
Published: April 2018

Abstract. There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.
POST-DISASTER DAMAGE ASSESSMENT THROUGH COHERENT CHANGE DETECTION ON SAR IMAGERY
Authors: Guida L. , Boccardo P. , Donevski I. , Lo Schiavo L. , Molinari M. E. , Monti-Guarnieri A. , Oxoli D. , Brovelli M. A.
Published: April 2018

Abstract. Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.
FUSING PANCHROMATIC AND SWIR BANDS BASED ON CNN – A PRELIMINARY STUDY OVER WORLDVIEW-3 DATASETS
Authors: Guo M. , Ma H. , Bao Y. , Wang L.
Published: April 2018

Abstract. The traditional fusion methods are based on the fact that the spectral ranges of the Panchromatic (PAN) and multispectral bands (MS) are almost overlapping. In this paper, we propose a new pan-sharpening method for the fusion of PAN and SWIR (short-wave infrared) bands, whose spectral coverages are not overlapping. This problem is addressed with a convolutional neural network (CNN), which is trained by WorldView-3 dataset. CNN can learn the complex relationship among bands, and thus alleviate spectral distortion. Consequently, in our network, we use the simple three-layer basic architecture with 16 × 16 kernels to conduct the experiment. Every layer use different receptive field. The first two layers compute 512 feature maps by using the 16 × 16 and 1 × 1 receptive field respectively and the third layer with a 8 × 8 receptive field. The fusion results are optimized by continuous training. As for assessment, four evaluation indexes including Entropy, CC, SAM and UIQI are selected built on subjective visual effect and quantitative evaluation. The preliminary experimental results demonstrate that the fusion algorithms can effectively enhance the spatial information. Unfortunately, the fusion image has spectral distortion, it cannot maintain the spectral information of the SWIR image.
PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON
Authors: Annala L. , Eskelinen M. A. , Hämäläinen J. , Riihinen A. , Pölönen I.
Published: April 2018

Abstract. Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.
DISASTER EMERGENCY RAPID ASSESSMENT BASED ON REMOTE SENSING AND BACKGROUND DATA
Authors: Han X. , Wu J.
Published: April 2018

Abstract. The period from starting to the stable conditions is an important stage of disaster development. In addition to collecting and reporting information on disaster situations, remote sensing images by satellites and drones and monitoring results from disaster-stricken areas should be obtained. Fusion of multi-source background data such as population, geography and topography, and remote sensing monitoring information can be used in geographic information system analysis to quickly and objectively assess the disaster information. According to the characteristics of different hazards, the models and methods driven by the rapid assessment of mission requirements are tested and screened. Based on remote sensing images, the features of exposures quickly determine disaster-affected areas and intensity levels, and extract key disaster information about affected hospitals and schools as well as cultivated land and crops, and make decisions after emergency response with visual assessment results.
COMPENSATION OF THE IONOSPHERIC EFFECTS ON SAR INTERFEROGRAM BASED ON RANGE SPLIT-SPECTRUM AND AZIMUTH OFFSET METHODS – A CASE STUDY OF YUSHU EARTHQUAKE
Authors: He Y. F. , Zhu W. , Zhang Q. , Zhang W. T.
Published: April 2018

Abstract. InSAR technique can measure the surface deformation with the accuracy of centimeter-level or even millimeter and therefore has been widely used in the deformation monitoring associated with earthquakes, volcanoes, and other geologic process. However, ionospheric irregularities can lead to the wavy fringes in the low frequency SAR interferograms, which disturb the actual information of geophysical processes and thus put severe limitations on ground deformations measurements. In this paper, an application of two common methods, the range split-spectrum and azimuth offset methods are exploited to estimate the contributions of the ionosphere, with the aim to correct ionospheric effects in interferograms. Based on the theoretical analysis and experiment, a performance analysis is conducted to evaluate the efficiency of these two methods. The result indicates that both methods can mitigate the ionospheric effect in SAR interferograms and the range split-spectrum method is more precise than the other one. However, it is also found that the range split-spectrum is easily contaminated by the noise, and the achievable accuracy of the azimuth offset method is limited by the ambiguous integral constant, especially with the strong azimuth variations induced by the ionosphere disturbance.
URBAN SHANTY TOWN RECOGNITION BASED ON HIGH-RESOLUTION REMOTE SENSING IMAGES AND NATIONAL GEOGRAPHICAL MONITORING FEATURES – A CASE STUDY OF NANNING CITY
Authors: He Y. , He Y.
Published: April 2018

Abstract. Urban shanty towns are communities that has contiguous old and dilapidated houses with more than 2000 square meters built-up area or more than 50 households. This study makes attempts to extract shanty towns in Nanning City using the product of Census and TripleSat satellite images. With 0.8-meter high-resolution remote sensing images, five texture characteristics (energy, contrast, maximum probability, and inverse difference moment) of shanty towns are trained and analyzed through GLCM. In this study, samples of shanty town are well classified with 98.2 % producer accuracy of unsupervised classification and 73.2 % supervised classification correctness. Low-rise and mid-rise residential blocks in Nanning City are classified into 4 different types by using k-means clustering and nearest neighbour classification respectively. This study initially establish texture feature descriptions of different types of residential areas, especially low-rise and mid-rise buildings, which would help city administrator evaluate residential blocks and reconstruction shanty towns.
ON THE INFLUENCE OF GLOBAL WARMING ON ATLANTIC HURRICANE FREQUENCY
Authors: Hosseini S. R. , Scaioni M. , Marani M.
Published: April 2018

Abstract. In this paper, the possible connection between the frequency of Atlantic hurricanes to the climate change, mainly the variation in the Atlantic Ocean surface temperature has been investigated. The correlation between the observed hurricane frequency for different categories of hurricane’s intensity and Sea Surface Temperature (SST) has been examined over the Atlantic Tropical Cyclogenesis Regions (ACR). The results suggest that in general, the frequency of hurricanes have a high correlation with SST. In particular, the frequency of extreme hurricanes with Category 5 intensity has the highest correlation coefficient (R = 0.82). In overall, the analyses in this work demonstrates the influence of the climate change condition on the Atlantic hurricanes and suggest a strong correlation between the frequency of extreme hurricanes and SST in the ACR.
THE EARLY DETECTION OF THE EMERALD ASH BORER (EAB) USING MULTI-SOURCE REMOTELY SENSED DATA
Authors: Hu B. , Naveed F. , Tasneem F. , Xing C.
Published: April 2018

Abstract. The objectives of this study were to exploit the synergy of hyperspectral imagery, Light Detection And Ranging (LiDAR) and high spatial resolution data and their synergy in the early detection of the EAB (Emerald Ash Borer) presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, an advanced individual tree delineation method was developed to delineate individual trees using the combined high-spatial resolution worldview-3 imagery was used together with LiDAR data. Individual trees were then classified to ash and non-ash trees using spectral and spatial information. In order to characterize the health state of individual ash trees, leaves from ash trees with various health states were sampled and measured using a field spectrometer. Based on the field measurements, the best indices that sensitive to leaf chlorophyll content were selected. The developed framework and methods were tested using worldview-3, airborne LiDAR data over the Keele campus of York University Toronto Canada. Satisfactory results in terms of individual tree crown delineation, ash tree identification and characterization of the health state of individual ash trees. Quantitative evaluations is being carried out.
MEASUREMENT OF SEAWARD GROUND DISPLACEMENTS ON COASTAL LANDFILL AREA USING RADAR INTERFEROMETRY
Authors: Baek W.-K. , Jung H.-S.
Published: April 2018

Abstract. In order to understand the mechanism of subsidence and help reducing damage, researchers has been observed the line-of-sight subsidence on the Noksan industrial complex using SAR Interferometry(InSAR) and suggested subsidence prediction models. Although these researches explained a spatially uneven ground subsidence near the seaside, they could not have been explained the occurrence of the newly proposed seaward horizontal, especially nearly north-ward, displacement because of the geometric limitation of InSAR measurements. In this study, we measured the seaward ground displacements trend on the coastal landfill area, Noksan Industrial Complex. We set the interferometric pairs from an ascending and a descending orbits strip map data of ALOS PALSAR2. We employed InSAR and MAI stacking approaches for the both orbits respectively in order to improve the measurement. Finally, seaward deformation was estimated by retrieving three-dimensional displacements from multi-geometric displacements. As a results, maximally 3.3 and 0.7 cm/year of ground displacements for the vertical and seaward directions. In further study, we plan to generate InSAR and MAI stacking measurements with additional SAR data to mitigate tropospheric effect and noise well. Such a seaward observation approach using spaceborne radar is expected to be effective in observing the long-term movements on coastal landfill area.
RESEARCH ON VISUALIZATION OF GROUND LASER RADAR DATA BASED ON OSG
Authors: Huang H. , Hu C. , Zhang F. , Xue H.
Published: April 2018

Abstract. Three-dimensional (3D) laser scanning is a new advanced technology integrating light, machine, electricity, and computer technologies. It can conduct 3D scanning to the whole shape and form of space objects with high precision. With this technology, you can directly collect the point cloud data of a ground object and create the structure of it for rendering. People use excellent 3D rendering engine to optimize and display the 3D model in order to meet the higher requirements of real time realism rendering and the complexity of the scene. OpenSceneGraph (OSG) is an open source 3D graphics engine. Compared with the current mainstream 3D rendering engine, OSG is practical, economical, and easy to expand. Therefore, OSG is widely used in the fields of virtual simulation, virtual reality, science and engineering visualization. In this paper, a dynamic and interactive ground LiDAR data visualization platform is constructed based on the OSG and the cross-platform C++ application development framework Qt. In view of the point cloud data of .txt format and the triangulation network data file of .obj format, the functions of 3D laser point cloud and triangulation network data display are realized. It is proved by experiments that the platform is of strong practical value as it is easy to operate and provides good interaction.
ALTERATION MINERALS EXTRACTION USING AIRBORNE HYPERSPECTRAL DATA CASI AND SASI IN WUYI METALLOGENIC BELT, CHINA
Authors: Huang Z. , Zheng J.
Published: April 2018

Abstract. Hydrothermal alteration is an important content in the study of epithermal deposit, and its deep part is often accompanied by porphyry mineralization. The objective of research is to mapping the alteration minerals for mineral exploration using mixture tuned matched filtering (MTMF) approach based on airborne hyperspectral data CASI and SASI in Wuyi metallogenic belt, China, which has complex geological structure and excellent mineralization conditions and high regional forest coverage rate. Gold mineralization is closely related to the Yanshan period epithermal intrusive rocks, and often exists in external contact zone of allgovite, monzomite porphyrite, granite porphyry, quarz porphyry, et al.. The main mineral alteration types include silicification (quartz), sericitization (sericite, illite), pyritization (pyrite), chloritization (chlorite), and partial calcitization (calcite). The alteration minerals extraction based on integrated CASI_SASI reflectance data were processed by MTMF algorithm with the input imagery which was pre-processed by MNF and the input endmember spectra measured by SVC spectrometer to performs MF and add an infeasibility image. The MTMF results provide an estimate to mineral subpixel fractions leading to the abundances of alteration minerals at each pixel and alteration minerals distribution. The accuracy of alteration mineral extraction refers to the extent which it agrees with a set of reference data measured in the field reconnaissance. So the CASI_SASI airborne hyperspectral image provides the efficient way to map the detailed alteration minerals distribution for mineral exploration in high forest coverage area.