Extraction and Analysis of Gully Head of Loess Plateau in China Based on Digital Elevation Model

In China′s Loess Plateau area, gully head is the most active zone of a drainage system in gully areas. The differentiation of loess gully head follows geospatial patterns and reflects the process of the loess landform development and evolution of its drainage system to some extent. In this study, the geomorphic meaning, basic characteristics, morphological structure and the basic types of loess gully heads were systematically analysed. Then, the loess gully head′s conceptual model was established, and an extraction method based on Digital Elevation Model(DEM) for loess gully head features and elements was proposed. Through analysing the achieved statistics of loess gully head features, loess gully heads have apparently similar and different characteristics depending on the different loess landforms where they are found. The loess head characteristics reflect their growth period and evolution tendency to a certain degree, and they indirectly represent evolutionary mechanisms. In addition, the loess gully developmental stages and the evolutionary processes can be deduced by using loess gully head characteristics. This study is of great significance for development and improvement of the theoretical system for describing loess gully landforms.

Properties of L-band differential InSAR for monitoring mining-induced subsidence in coalfield of Jining, Northern China

The properties and feasibility of L-band differential InSAR for detecting and monitoring mining-induced subsidence were systematically analyzed and demonstrated. The largest monitored subsidence gradient of 7.9×10-3 and magnitude of 91 cm were firstly derived by theoretical derivation. Then, the stronger phase maintaining capacity and weaker sensitivity to minor land subsidence compared with C-band DInSAR were illustrated by phase simulation of the actual mine subsidence. Finally, the data processing procedure of two-pass DInSAR was further refined to accurately observe subsidence of a coalfield of Jining in Northern China using 7 ALOS PALSAR images. The largest monitored subsidence magnitude of 39.22 cm and other properties were better investigated by testing results interpretation and subsidence analysis, and the absolute difference varying from 0.5 mm to 17.9 mm was obtained by comparison with leveling-measured subsidence. All of results show that L-band DInSAR technique can investigate the location, amount, area and other detailed subsidence information with relatively higher accuracy.

An improved, SSH-based method to automatically identify mesoscale eddies in the ocean

Mesoscale eddies are an important component of oceanic features.How to automatically identify these mesoscale eddies from available data has become an important research topic.Through careful examination of existing methods,we propose an improved,SSH-based automatic identification method.Using the inclusion relation of enclosed SSH contours,the mesoscale eddy boundary and core(s) can be automatically identified.The time evolution of eddies can be examined by a threshold search algorithm and a tracking algorithm based on similarity.Sea-surface height(SSH) data from Naval Research Laboratory Layered Ocean Model(NLOM) and sea-level anomaly(SLA) data from altimeter are used in the many experiments,in which different automatic identification methods are compared.Our results indicate that the improved method is able to extract the mesoscale eddy boundary more precisely,retaining the multiple-core structure.In combination with the tracking algorithm,this method can capture complete mesoscale eddy processes.It can thus provide reliable information for further study of reconstructing eddy dynamics,merging,splitting,and evolution of a multi-core structure.

Association between Arctic autumn sea ice concentration and early winter precipitation in China

Associations between autumn Arctic sea ice concentration(SIC) and early winter precipitation in China are studied using singular value decomposition analysis. The results show that a reduced SIC almost everywhere in the Arctic Ocean, except the northern Greenland Sea and Canadian Basin, are accompanied by dry conditions over central China, extending northeast from the Tibetan Plateau toward the Japan Sea, the Bohai Sea and the Yellow Sea, and wet conditions over South China and North China. Atmospheric circulation anomalies associated with SIC variability show two wave-train structures, which are persistent from autumn to winter, leading to the identified relationship between autumn Arctic SIC and early winter precipitation in China. Given that the decline in autumn SIC in the Arctic Ocean is expected to continue as the climate warms, this relationship provides a possible long-term outlook for early winter precipitation in China.

Correction for Depth Biases to Shallow Water Multibeam Bathymetric Data

Vertical errors often present in multibeam swath bathymetric data. They are mainly sourced by sound refraction, internal wave disturbance, imperfect tide correction, transducer mounting, long period heave, static draft change, dynamic squat and dynamic motion residuals, etc. Although they can be partly removed or reduced by specific algorithms, the synthesized depth biases are unavoidable and sometimes have an important influence on high precise utilization of the final bathymetric data. In order to confidently identify the decimeter-level changes in seabed morphology by MBES, we must remove or weaken depth biases and improve the precision of multibeam bathymetry further. The fixed-interval profiles that are perpendicular to the vessel track are generated to adjust depth biases between swaths. We present a kind of postprocessing method to minimize the depth biases by the histogram of cumulative depth biases. The datum line in each profile can be obtained by the maximum value of histogram. The corrections of depth biases can be calculated according to the datum line. And then the quality of final bathymetry can be improved by the corrections. The method is verified by a field test.

Forest Road Detection Using LiDAR Data

We developed a three-step classification approach for forest road extraction utilizing LiDAR data. The first step employed the IDW method to interpolate LiDAR point data(first and last pulses) to achieve DSM, DTM and DNTM layers(at 1 m resolution). For this interpolation RMSE was 0.19 m. In the second step, the Support Vector Machine(SVM) was employed to classify the LiDAR data into two classes, road and non-road. For this classification, SVM indicated the merged distance layer with intensity data and yielded better identification of the road position. Assessments of the obtained results showed 63% correctness, 75% completeness and 52% quality of classification. In the next step, road edges were defined in the LiDAR-extracted layers, enabling accurate digitizing of the centerline location. More than 95% of the LiDAR-derived road was digitized within 1.3 m to the field surveyed normal. The proposed approach can provide thorough and accurate road inventory data to support forest management.

Arctic autumn sea ice decline and Asian winter temperature anomaly

Associations between the autumn Arctic sea ice concentration(SIC) and Asian winter temperature are discussed using the singular value decomposition analysis.Results show that in recent 33 years reduced autumn Arctic sea ice is accompanied by Asian winter temperature decrease except in the Tibetan plateau and the Arctic Ocean and the North Pacific Ocean coast.The autumn SIC reduction excites two geopotential height centers in Eurasia and the north Arctic Ocean,which are persistent from autumn to winter.The negative center is in Barents Sea/Kara Sea.The positive center is located in Mongolia.The anomalous winds are associated with geopotential height centers,providing favorable clod air for the Asian winter temperature decreasing in recent 33 years.This relationship indicates a potential long-term outlook for the Asian winter temperature decrease as the decline of the autumn sea ice in the Arctic Ocean is expected to continue as climate warms.

A new method of weight choice in InSAR least squares unwrapping

The de-coherence phenomena such as Low-SNR radar signal, shadows and layover caused by topography, etc., causing phase data discontinuity, makes the result of unwrapping phase inaccuracy or even completely wrong. Based on the analysis of influencing factors to weight choice, this thesis develops a new method to choose the weights based on the measure of the confidence in the frequency domain. Experiments show that it could overcome the defect of sub-estimate to the slope of least squares method very well, which has a better rationale, stability and performance.

A new method of weighted choice in InSAR Least Squares unwrapping

The decorelation phenomena such as Low-SNR radar signal,shadows and layover caused by topography etc,causes phase data discontinuous and makes the result of unwrapping phase inaccurate or completely wrong.Based on the analysis of influencing factors to the weight selection,this paper develops a new method to choose the weights based on the measurement of confidence in frequency domain.Results show that it is more precise and robust than other methods,and can make up for the defect of sub-estimate to the slope of least squares method.

Data organization and management of mine typical object spectral libraries

With the development of mining industry,people have obtained profits from it,but they are facing environmental damages.In order to monitor these environmental changes,a spectral library is set up for the spectrum data organization and management of mine typical objects.Most of the spectrum data come from the long-term field measuring in mining area and other spectral libraries.For the data quality control and error detection in the measuring data,an inner precision calculation method is presented and a series of interactive graphical controls are developed for the spectrum visualization and analysis.Through extracting and saving spectrum characters for the mine typical objects,realizs spectrum matching and classification for new measured spectrum samples are realized by using Euclidean distance,Aitchison distance,Pearson correlation coefficient and vector angular cosine methods.Based on the matching result,this work is able to gather dynamically physicochemical environment parameters from the library and gives an early warning for the mine environmental changes.

Design a New Model to Evaluate the Ecological Potential Land for Urban Development and Service (City of Zanjan)

This study aimed to design a new ecological model to be used in ecological land evaluation studies, using careful planning and sustainable resource in the region to develop a sustainable and comprehensive guide. The results show that the study area has grade 1 and 2 urban sustainable planning. Capability Grade 1 has area 149,724.25 hectares equal 22.2% that is stretched from East to West Range. Capability Grade2 has area about 18533.28 hectares equal 2.7% that located in the South, East and South-East. The results show that the greater extent of this range is the unsustainable site, which extends over 506,664.81 hectares, equivalent to 75.1% that areas compliance by the Environmental Protection area. Another important result of this study is unsuitable area for urban development and the range of services already seating workshops and industrial units. This is due to the arrival of adverse environmental effects. Therefore, this study has been focusing on reform of the status of land of use and the optimal use of the ecological potential.

Sensitivity studies of a high accuracy surface modeling method

The sensitivities of the initial value and the sampling information to the accuracy of a high accuracy surface modeling(HASM) are investigated and the implementations of this new modeling method are modified and enhanced. Based on the fundamental theorem of surface theory, HASM is developed to correct the error produced in geographical information system and ecological modeling process. However, the earlier version of HASM is theoretically incomplete and its initial value must be produced by other surface modeling methods, such as spline, which limit its promotion. In other words, we must use other interpolators to drive HASM. According to the fundamental theorem of surface theory, we modify HASM, namely HASM.MOD, by adding another important nonlinear equation to make it independent of other methods and, at the same time, have a complete and solid theory foundation. Two mathematic surfaces and monthly mean temperature of 1951–2010 are used to validate the effectiveness of the new method. Experiments show that the modified version of HASM is insensitive to the selection of initial value which is particular important for HASM. We analyze the sensitivities of sampling error and sampling ratio to the simulation accuracy of HASM.MOD. It is found that sampling information plays an important role in the simulation accuracy of HASM.MOD. Another feature of the modified version of HASM is that it is theoretically perfect as it considers the third equation of the surface theory which reflects the local warping of the surface. The modified HASM may be useful with a wide range of spatial interpolation as it would no longer rely on other interpolation methods.

An improved HASM method for dealing with large spatial data sets

Surface modeling with very large data sets is challenging. An efficient method for modeling massive data sets using the high accuracy surface modeling method(HASM) is proposed, and HASM_Big is developed to handle very large data sets. A large data set is defined here as a large spatial domain with high resolution leading to a linear equation with matrix dimensions of hundreds of thousands. An augmented system approach is employed to solve the equality-constrained least squares problem(LSE) produced in HASM_Big, and a block row action method is applied to solve the corresponding very large matrix equations.A matrix partitioning method is used to avoid information redundancy among each block and thereby accelerate the model.Experiments including numerical tests and real-world applications are used to compare the performances of HASM_Big with its previous version, HASM. Results show that the memory storage and computing speed of HASM_Big are better than those of HASM. It is found that the computational cost of HASM_Big is linearly scalable, even with massive data sets. In conclusion,HASM_Big provides a powerful tool for surface modeling, especially when there are millions or more computing grid cells.

2018年中国基本城市土地利用类型制图(EULUC-China)

土地利用是人类活动在土地空间的重要表现形式.由于数据和资金支持的限制,全国尺度城市土地利用的遥感制图研究仍相对缺乏.针对这一难题,本文提出了涵盖居住-休闲-交通-工业-办公五大类用地的"基本城市土地利用类型(EULUC)"的概念,并综合利用2018年的10米分辨率哨兵卫星数据,OpenStreetMap,珞珈一号夜间灯光数据,以及腾讯移动定位和高德兴趣点(POI)等社会大数据,实现了全国范围内城市土地利用制图.第一版中国基本城市土地利用制图结果共包括440798个地块(除道路用地),5大一级类和12个二级类总体分类精度分别为61.2%和57.5%.这是中国首套结合遥感和众源大数据,以地块尺度生产的面向对象的高分辨率城市土地利用图.