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Shadows are ubiquitous in high-resolution images, especially in urban regions where there are more serious shadow occlusions. In order to improve the detection effect of shadows, this paper analyzes the characteristics and properties of shadows in orthophotos, and proposes an orthophoto shadow detection method under artificial shadow. Firstly, the shadow modeling tool is used to calculate the shadow regions (i.e. artificial shadow) caused by the building obstructing the sun's rays. Secondly, the relaxation matching algorithm is extended by the position and the shape of the shadow polygon as characteristic constraints. The relaxation matching algorithm is extended by the position and shape as shadow polygon’s characteristic constraints. Thirdly, the feature constraint value is calculated which between the shadow polygons of the two images. The correlation coefficient is used to obtain the initial probability value of each shadow polygon in the orthophoto. Finally, the optimal solution is obtained by continuous correction and iteration of the initial probability value. The method performs an overall matching of the two images and obtains the position of the shadow regions of the buildings in the orthophoto image. Experiment shows that this method reduces the mismatch rate and improves the matching accuracy. This method can detect shadow regions of buildings in orthophoto quickly and efficiently.

In order to solve the problem that the source of LiDAR data error needs to be adjusted and the data volume is large, the adjustment speed between the voyages is slow and cannot be automatically adjusted. Based on the iterative nearest point (ICP) algorithm, this paper proposes an improved iterative closest point (ICP) algorithm based on GPU parallel octree. The algorithm quickly constructs the octree of LiDAR nautical belt data in the GPU, uses the octree to quickly find the overlapping area of the nautical band, and then uses the ICP algorithm in the overlapping area to solve the adjustment parameters R and T quickly. Then the entire flight belt is quickly adjusted. Experiments with example data show that this method can quickly and automatically adjustment a large number of LiDAR data, and the adjustment precision can meet the precision requirements of the production.

This paper analyzes a varieties of procedure of remote sensing data processing, and explores the common mathematical models, common algorithm models, and public function processing units of data processing shared by different tasks or even different parts within an individual task. Public modules are established to improve the parallelism of remote sensing data processing based on FPGA, which has excellent parallel processing performance. In addition, in order to reduce the resource consumption and increase the calculation efficiency of the designed FPGA program, the method of avoiding floating-point arithmetic and division operation in FPGA programming are discussed in this paper. There are a large number of common calculation modules between different tasks, such as the rotation matrix calculation module in attitude solution, geometric correction, and orthorectification task. Image preprocessing, feature information extraction, image threshold separation, and connected region markers are all common processing modules for a target detection task. In the same task, there is also a common calculation module. When using the FPGA design program, the power series of 2 can be used to convert the floating-point operation to fixed-point operation with an acceptable precision. A similar approach can transform the division operation into multiplication and shift operations, thereby improve the computational performance of FPGA programming.

This paper mainly uses manual calibration technology to check the elements Yaw, Pitch and Roll (YPR) in the LiDAR DGPS/IMU system and obtained the error value. Combined with the error angle, the external azimuth angle elements Kappa, Omega and Phi required by photogrammetry are obtained. The paper points out that the placement angle error will have a serious impact on the LiDAR foot position. Therefore, this paper puts forward a method to check the placement angle of the steeple roof and flat straight highway, and gives the design scheme of the optimized route to reduce the number of flights. This paper focuses on the specific process of YPR calibration, and gives a mathematical calibration model based on the influence of attitude angles Yaw, Pitch and Roll on the LiDAR foot during the flight. The placement angle error is obtained after the calibration, and the error angle matrix is used to convert the elements YPR and OPK. After checking and error correction, the point cloud obtained from adjacent airlines have achieved better coincidence effect. The experimental results show that the theory and method of YPR element calibration are correct and feasible, which simplifies the conversion process of YPR and OPK. Compared with the traditional calibration method that requires control points, this method can greatly improve the efficiency and reliability of the inspection.

The survey and monitoring system of natural resources is the basis for finding out and monitoring the background data in the new era. The classification standard is an important cornerstone in the survey and monitoring system. The classification standard appears in the whole process of natural resources, such as survey, monitoring, evaluation, planning and control etc. Classification results are widely used in natural resource asset management, territorial space use controlling, ecological protection and restoration. Therefore, only a classification standard with the unified, scientific and practical characteristics is constructed, a survey and monitoring system with “six unifications” can be built. This paper refines the existing status and the main problem of existing classification standards, and then puts forward the construction ideas and three suggestions for the new classification standards, which hoping to provide a reference for local survey and monitoring pilots and national classification standard construction.

Optical property parameters play an important role in ocean colour studies. As a key variable, the absorption coefficient is of great significance for calculating the content of each component in water and simulating the physical, chemical and biological properties of water. The inversion algorithms mainly include empirical model, semi-analytical model and neural network model. In this study, we focused on the QAA_V6, which is the newest version of Quasi-Analytical Algorithm (QAA). It is necessary to test the QAA_V6 model in different conditions. IOCCG data set is used to verify the accuracy of QAA_V6. Additionally, MODIS data of case 1 waters and case 2 waters were selected. After extraction and matching, the data was finally imported into QAA_V6 model to calculate the absorption coefficient with a R2 of 0.999 in both case 1 waters and case 2 waters, thus the QAA_V6 model showed a high accuracy and robust applicability in the inversion of inherent optical properties. Subsequently, it can be further verified for the waters in more complicated areas, providing a firm foundation for implementing QAA into the research of ocean colour remote sensing.

Due to the influence of the occlusion of objects or the complexity of the measured terrain in the scanning process of airborne lidar, the point cloud data inevitably appears holes after filtering and other processing. The incomplete data will inevitably have an impact on the quality of the reconstructed digital elevation model, so how to repair the incomplete point cloud data has become an urgent problem to be solved. To solve the problem of hole repair in point cloud data, a hole repair algorithm based on improved moving least square method is proposed in this paper by studying existing hole repair algorithms. Firstly, the algorithm extracts the boundary of the point cloud based on the triangular mesh model. Then we use k-nearest neighbor search to obtain the k-nearest neighbor points of the boundary point. Finally, according to the boundary point and its k-nearest neighbor point, the improved moving least squares method is used to fit the hole surface to realize the hole repair. Combined with C++ and MATLAB language, the feasibility of the algorithm is tested by specific application examples. The experimental results show that the algorithm can effectively repair the point cloud data holes, and the repairing precision is high. The filled hole area can be smoothly connected with the boundary.

Aiming at the problems of low accuracy and slow speed in the current remote sensing image classification algorithm,In order to improve remote sensing image classification, a quantum entanglement algorithm is proposed.The model transforms the classification process of remote sensing image into a random self-organization process of quantum particles in the state configuration space. The state configuration formed by entanglement of quantum particles evolves with time and finally converges to an average probability distribution.Taking Kunming city of Yunnan province as the research area, this paper compares the classification method in this paper with the traditional remote sensing classification method by using the 02C image data of yuanyuan1.Compared with other classification methods, the classification accuracy of this paper meets the requirements.

As one of the most popular surveillance technologies in the 21st century, Lidar is applied in commercial, military and civilian applications. paper mainly introduces the development process of Chinese and American marine lidar detection technology, compares the hardware technical parameters of marine airborne laser lidar between China and the United States, and summarizes China's current airborne lidar detection technology and developed countries. Find the gap between developed countries. It introduces the most important application of this technology, and its contribution to the development of science and technology. Finally, summarize the various problems encountered in the development of the technology, analyse the reasons, and look forward to the future development trend.

There are some problems in the visualization of 3D model of buildings at present, such as redundant texture data and large memory occupation of loading texture data, which pose challenges to the smooth loading of 3D building visualization. In this paper, we propose a method which using fractal quadtrees to simplify texture data and compress management. Firstly, this method uses the fractal self-similarity and the feature that the same texture has the same fractal dimension to screen all the textures, when the fractal dimension of multiple textures is within the threshold range. Radon transform will be performed on these textures to calculate their standard deviation and further simplify the texture. Secondly, we use fractal texture compression to create a multi-resolution texture data structure with quadtree structure, so that the building 3D model can achieve dynamic visualization of different scales. Finally, the parallel texture mapping of all faces of the 3D model of the building is implemented according to the texture calling rules. Experimental results demonstrate that the texture is managed by the method proposed in this paper, which shortens the loading time of texture and reduces the memory occupation by about 48.92%. Therefore, the method of texture simplification and compression proposed in this paper has a significant effect in the process of building 3D model visualization.

There are many intertidal zones and island reefs in the coastal area, the traditional shipborne acoustic measurement method is extremely inefficient, so the coastal area three-dimensional integrated measurement has always been a difficult point in the field of remote sensing. Because the sea blue-green light window has good transparency and the laser point cloud data can quickly and accurately distinguish the characteristics of shallow sea water topography. At present, the most effective detection method for coastal areas in the world is the airborne dual-frequency laser radar detection technology, which has high measurement rate and wide coverage. The laser outputs both 1064nm and 532nm dual-wavelength laser, 1064nm laser forms sea surface echo, and 532nm laser penetrates sea water to form shallow sea and deep sea echo. However, during the propagation of seawater, the number of photon scattering increases with the increase of water depth, which will cause the attenuation of the echo signal. As a result, the detection of weak light in the large dynamic range is not high, which has been a difficult point for near-shore airborne sounding. To solve this problem, we designed a split-field, three-channel optical receiving system. The ZEMAX simulation results show that the dual-channel laser radar three-channel receiving optical system effectively reduces the optical crosstalk between the optical components and the channels, and achieves energy harvesting in different water depth channels. The structure dynamically compresses the photoelectric signal and improves the signal to noise ratio.

Due to the semi-random characteristics of ground points collected by airborne LIDAR system, it is difficult to control the laser pin points to fall on the control points with known coordinates in actual measurement, so the accuracy can not be evaluated by directly comparing coordinate data. In this paper, based on the target plate designed by air-to-ground, the fuzzy c-means clustering analysis algorithm is proposed to extract the point cloud data on the target according to the different echo intensity data of laser on different ground objects. The center point coordinates of the target were fitted by the point cloud data on the target using the method of circumscribed circle of edge points, so as to realize the plane precision and elevation accuracy of airborne LIDAR system of evaluation. The results show that the model fitting method can quickly and effectively evaluate the accuracy of airborne LIDAR, and the method is simple and feasible.

Although many efforts have been made on the extraction of houses from LiDAR (Light Detection and Ranging) and/or aerial imagery and/or their fusion, little investigation using co-registration between the orthoimage map and LiDAR on the basis of geodetic coordinates as element for house extraction. For this reason, this paper first overviews the advances of LiDAR and investigates the advantages and disadvantages of LiDAR system vs. traditional photogrammetry, and then indicates that LiDAR technology has not yet resolved all existing problems that traditional photogrammetry remained so far, such as texture information, LiDAR point cloud density. A comprehensive comparison in extraction of houses (feature information) from LiDAR data set and from aerial imagery are also presented. It has been widely accepted and admitted that full automation for extraction of houses (feature information in city area) from LiDAR point cloud has still been difficult. Therefore, this paper proposes a human-computer interaction operation for houses extraction through combination of LiDAR point cloud and the orthorectified high-resolution aerial imagery. The real data is utilized for validation of the proposed method.

The evaluation of the bathymetric capability of traditional airborne lidar system is mostly based on the formula of bathymetric capability by evaluating the diffuse attenuation coefficient (Kd). This method is derived form the assumption that the reflectance of sediment is fixed. In this study ,however,the reflectance of sediment is not fixed. Therefore, this study improves the ability of bathymetric formula, and proposes a particle scattering classification algorithm to obtain the transmissivity value. The algorithm filters the scattering modes of particles by scattering discrimination factor (q), and obtains the transmissivity values by using the scattering intensity formulas. Experiments show that, when the transmissivity is in the range of 0–1 and the average values of Kd(532 nm) are 0.1150 m−1, 0.0894 m−1 and 0.0903 m−1 in January, June and October respectively, accordingly, the bathymetric capabilities are 0–44 m, 0–61.5 m and 0–52.5 m, respectively. Compared with the original bathymetric method, these results show that the maximum bathymetric value has measured by the improved bathymetric capability formula and scattering classification algorithm has decreased under the influence of the change of sediment reflectance, and the result is more consistent with the actual situation and more accurate.

In the exploration of outer space and international space activities, civilian remote sensing satellites have made rapid development since the 1970s, and countries around the world have accelerated their civilian satellite development and its policy formulation as well. Regarding the regulations on the peaceful use of outer space and related space launches, the United Nations respectively formulated the "Five Treaties on Space" in the 1960s and 1970s to regulate the peaceful uses of outer space. However, in the development of civilian remote sensing satellites, orbital resources and application rules of remote sensing data, the implementation of "first-come, first-occupy" and "non-discriminatory access to remote sensing data" is mainly led by western developed countries, especially the space powers such as the United States and Russia. Based on the outer space policies and regulations, this article will make a comparative study of civilian remote sensing satellite development policies and related laws and regulations in major countries and regions in the world, so as to analyze the policies and legal principles of civilian remote sensing satellites, as well as its corresponding issues and problems.

Karst rocky desertification (KRD) is used to characterize the processes that transform a karst area covered by vegetation and soil into a rocky landscape almost devoid of soil and vegetation. This situation seriously affects and threatens the living environment and standards of local people, which results in a series of social problems. In view of the importance and harmfulness of KRD, many scholars have studied the spatial and temporal evolution of KRD and its driving forces. In this paper, the Visual Interpretation Marks of Rocky Desertification in Southwest China in 1960s are constructed by using the DISP image of the United States, combined with DEM data and Hydrogeological data. The area of rocky desertification in Guangnan and Funing counties, where rocky desertification is more serious, is about 2457.729 km2. The area of rocky desertification can be used as the basic data for studying the historical changes in southwestern China by researchers.

This paper proposes a novel low-complexity implementation with one parameter two dimensions cubic convolution interpolation (2D-CCI) of image interpolation for spaceborne georeferencing. The experiment results demonstrate that (1) the proposed scheme can achieve better performance without increasing the computational complexity compared to the traditional CCI; (2) the number of multiplication and addition is reduced to 33.33% and 40% respectively compared with original CCI; (3) the occupied resources of LUTs, register, DSP and memory are reduced to 23.7%, 21.9%, 18.5% and 25%, respectively; (4) the speedup time of the proposed Implementation is about 25 times higher than that when using the PC-based implementation.

The wavelet threshold method is widely used in signal denoising. However, traditional hard threshold method or soft threshold method is deficient for depending on fixed threshold and instability. In order to achieve efficient denoising of echo signals, an adaptive wavelet threshold denoising method, absorbing the advantages of the hard threshold and the soft threshold, is proposed. Based on the advantages of traditional threshold method, new threshold function is continuous, steerable and flexibly changeable by adjusting two parameters. The threshold function is flexibly changed between the hard threshold and the soft threshold function by two parameter adjustments. According to the Stein unbiased risk estimate (SURE), this new method can determine thresholds adaptively. Adopting different thresholds adaptively at different scales, this method can automatically track noise, which can effectively remove the noise on each scale. Therefore, the problems of noise misjudgement and incomplete denoising can be solved, to some extent, in the process of signal processing. The simulation results of MATLAB show that compared with hard threshold method and soft threshold method, the signal-to-noise ratio (SNR) of the proposed de-noising method is increased by nearly 2dB, and 4dB respectively. It is safely to conclude that, when background noise eliminated, the new wavelet adaptive threshold method preserves signal details effectively and enhances the separability of signal characteristics.

Although contemporary geospatial science has made great progress, spatial data fusion of vector and raster data is still a problem in the geoinformation science environment. In order to solve the problem, this paper proposes a method which merges vector and raster data. Firstly, the row and column numbers of the raster data, and the X, Y values of the vector data are represented by Morton code in the C++ environment, respectively. Secondly, we establish the the raster data table and the vector data table in the Oracle database to store the vector data and the raster data. Third, this paper uses the minimum selection bounding box method to extract the top data of the building model. Finally, we divide the vector and raster data into four steps to obtain the fusion data table, and we call the fusion data in the database for 3D visualization. This method compresses the size of data of the original data, and simultaneously divides the data into three levels, which not only solves the problem of data duplication storage and unorganized storage, but also can realize vector data storage and the raster data storage in the same database at the same time. Thus, the fusion original orthophoto data contains the gray values of building roofs and the elevation data, which can improve the availability of vector data and the raster data in the 3D Visualization application.

At present, the main LiDAR is single-point lidar. APD arrays and laser arrays are restricted to exit, so the number of area array LiDAR is scarce. Single-point lidar can't form a scanning pattern with only one laser point on the ground after launching laser, so it must have a set of scanning device for single-point lidar. The scanning device designed in this paper forms a circular scanning area on the ground by rotating the refraction prism, and at the same time forms a conical field of view. At present, marine LiDAR uses this kind of scanner more frequently. The advantages of this scanner are: simple mechanical structure and smooth operation. Overlapping elliptical scanning trajectories can be obtained during flight, which increases scanning density. Ultra-low dispersion glass is used as refractive prism in this paper. In a certain range of laser frequencies, the refractive prism has almost the same effect on laser refraction at different frequencies. The simulation results show that the scanner can be used as a common LiDAR scanner or a dual-frequency LiDAR scanner.

Remote sensing digital image mosaic refers to the splicing of two or more remote sensing images into a panoramic image to meet the application requirements of wide images. It is becoming more and more important to cover large areas of mosaic images. The data pre-processing and mosaic process are different for different images. In this paper, the declassified intelligence satellite photography (DISP) in the 1960s was used as experimental data, taking Qujing in Yunnan Province as an example, a total of 92 scene images were used for DISP image processing and seamless mosaic. Firstly, In order to make full use of the image, it is necessary to perform orthorectification on the KH-4B images covering Qujing. Considering that the satellite orbit parameters and other parameters are unknown, several models for orthorectification of satellite images are proposed. After experiments and analysis, it is concluded that the third order polynomial is the optimal. Secondly, given the problem of radiation imbalance caused by the difference of time phase, the histogram equalization method is used for color balance, the image of the seam line is eliminated. Finally, the seamless mosaic is achieved. The map of the 1960s DISP in Qujing is obtained. The map can provide material basis for future research and other fields. The processing methods of historical images can be used for reference by others.

Bathymetry is a key variable in ocean monitoring and measurement research. It becomes more and more important for development of rapid method to invert shallow sea water depth. In this study, a water depth inversion method based on multi-band model is established to analyze the relationship between different bands of Landsat 8 OLI multi-spectral and measured data. The average absolute error of the model is 1.48m at 10–20m water depth and the average relative error is 13.12%. The water depth inversion accuracy under normal conditions are achieved, indicating that the model will have a promising practical application in the future.

This paper reviews the development of in-orbit radiometric calibration methods in the past 40 years. It summarizes the development of in-orbit radiometric calibration technology of typical satellite sensors in the visible/near-infrared bands and the thermal infrared band. Focuses on the visible/near-infrared bands radiometric calibration method including: Lamp calibration and solar radiationbased calibration. Summarizes the calibration technology of Landsat series satellite sensors including MSS, TM, ETM+, OLI, TIRS; SPOT series satellite sensors including HRV, HRS. In addition to the above sensors, there are also summarizing ALI which was equipped on EO-1, IRMSS which was equipped on CBERS series satellite. Comparing the in-orbit radiometric calibration technology of different periods but the same type satellite sensors analyzes the similarities and differences of calibration technology. Meanwhile summarizes the in-orbit radiometric calibration technology in the same periods but different country satellite sensors advantages and disadvantages of calibration technology.

Homogeneous low phosphorus availability was reported to regulate root architecture in Arabidopsis via auxin, but the roles of auxin in root architecture plasticity to heterogeneous P availability remain unclear. In this study, we employed auxin biosynthesis-, transport- and signalling-related mutants. Firstly, we found that in contrast to low P (LP) content in the whole medium, primary root (PR) growth of Arabidopsis was partially rescued in the medium divided into two parts: upper with LP and lower with high P (HP) content or in the reverse arrangement. The down part LP was more effective to arrest PR growth as well as to decrease density of lateral roots (DLR) than the upper LP, and effects were dependent on polar auxin transport. Secondly, we verified that auxin receptor TIR1 was involved in the responses of PR growth and lateral root (LR) development to P supply and loss of function of TIR1 inhibited LR development. Thirdly, effects of heterogeneous P on LRD in the upper part of PR was dependent on PIN2 and PIN4, and in the down part on PIN3 and PIN4, whereas density of total LRs was dependent on auxin transporters PIN2 and PIN7. Finally, heterogeneous P availability altered the accumulation of auxin in PR tip and the expression of auxin biosynthesisrelated genes TAA1, YUC1, YUC2, and YUC4. Taken together, we provided evidences for the involvement of auxin in root architecture plasticity in response to heterogeneous phosphorus availability in Arabidopsis.

Precise quantification of the cloud condensation nuclei (CCN) number concentration is crucial for understanding aerosol indirect effects and characterizing these effects in models. An evaluation of various methods for CCN parameterization was carried out in this paper based on in situ measurements of aerosol activation properties within HaChi (Haze in China) project. Comparisons were made by closure studies between methods using CCN spectra, bulk activation ratios, cut-off diameters and size-resolved activation ratios. The estimation of CCN number concentrations by the method using aerosol size-resolved activation ratios, either averaged over a day or with diurnal variation, was found to be most satisfying and straightforward. This could be well expected since size-resolved activation ratios include information regarding the effects of size-resolved chemical compositions and mixing states on aerosol activation properties. The method using the averages of critical diameters, which were inferred from measured CCN number concentrations and particle number size distributions, also provided a good prediction of the CCN number concentration. Based on comparisons of all these methods in this paper, it was recommended that the CCN number concentration be predicted using particle number size distributions with inferred critical diameters or size-resolved activation ratios.

Based on the methods of vector angular spectrum and stationary phase, the analytical expressions of the electromagnetic field for the Gaussian vortex beam and its transverse electric (TE) and transverse magnetic (TM) terms are derived in the far field. The analytical formulae of the energy flux distributions of the Gaussian vortex beam and its TE and TM terms are also presented in the far field. The analytical expressions for the ratios of the powers of the TE and TM terms to the power of the Gaussian vortex beam are further given. Based on the second-order moment of the energy flux distribution, the analytical formulae of the far field divergence angles of the Gaussian vortex beam and its TE and TM terms are also derived without any approximation. The influences of the f-parameter and the topological charge on the energy flux distributions, the ratios of the powers of the TE and TM terms to the power of the Gaussian vortex beam, and the far field divergence angles are numerically analysed. This research further reveals the structural properties of a Gaussian vortex beam in the far field and is beneficial to the practical applications of a Gaussian vortex beam. [ABSTRACT FROM AUTHOR]

Based on the vector angular spectrum representation of an optical beam and appropriate mathematical methods, the analytical vectorial structure of the hollow Gaussian beam (HGB) close to the source is derived without any approximation. The analytical expressions of the energy flux for the transverse electric (TE) term, the transverse magnetic (TM) term and the HGB are presented in the source region, respectively. The energy flux distributions of the TE term, the TM term and the HGB close to the source are illustrated with numerical examples. Moreover, the contribution of the evanescent plane waves to the energy flux distributions of the TE term, the TM term and the HGB is examined in the source region. This research is beneficial to the atom manipulation with a HGB. [ABSTRACT FROM AUTHOR]