Table of Content

20 October 2021, Volume 50 Issue 10

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Geodesy and Navigation

AOD adaptive prediction method based on GNSS PWV

ZHAO Qingzhi, SU Jing, YANG Pengfei, YAO Yibin

2021, 50(10):  1279-1289.  doi:10.11947/j.AGCS.2021.20210052

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Aerosol optical depth (AOD) is a basic parameter of total aerosol content, which plays an important role in the study of atmospheric air quality. In order to explore the impact of different types of AOD on air quality, this paper proposes two adaptive AOD prediction methods based on GNSS PWV. The proposed method considers the temporal autocorrelation of AOD between adjacent epochs, and the model coefficients can be updated adaptively. One method is to model the 550 nm AOD directly based on GNSS PWV, which is called TAF (total AOD forecast) model. Another AOD modeling method takes into account the sensitivity of five different types of AOD to PWV, referred to it simply as FTAF(five type based AOD forecast) model. The model first establishes the functional relationship between PWV and five types of AOD. Secondly, according to the relationship between 550 nm AOD and five types of AOD, the weight of different types of AOD in 550 nm AOD was determined. Finally, PWV is used to predict five types of AOD, and the final 550 nm AOD is obtained by weighted average. 16 GNSS stations in Beijing, Tianjin, Hebei region are selected to verify the accuracy of the proposed model. The results show that the two 550 nm AOD prediction models have high accuracy, and the FTAF model is better than the TAF model. The AOD prediction model proposed in this paper can effectively apply the tropospheric parameters retrieved from GNSS to remote sensing monitoring of atmospheric environment, which provides a new idea for the study of atmospheric environmental quality.

Characteristics of the short-term temporal variations of multi-constellation and multi-frequency GNSS receiver differential phase biases

MI Xiaolong, YUAN Yunbin, ZHANG Baocheng

2021, 50(10):  1290-1297.  doi:10.11947/j.AGCS.2021.20200489

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With the completion of the BeiDou-3 Navigation Satellite System (BDS-3) and the development of Galileo and quasi-zenith satellite system (QZSS), more and more satellites can be used to retrieve the atmospheric ionosphere. Generally, the short-time variation of receiver differential code biases (DCB) is considered as an important error source for ionospheric inversion using Global Navigation Satellite System (GNSS). However, some studies have shown that the short-time variation of receiver differential phase biases (DPB) may also affect the accuracy and reliability of ionospheric inversion. This paper presents a method to estimate the receiver DPB based on the single-differenced (SD) model without changing the reference satellite, which can realize the continuous estimation of the receiver DPB. DPB of the overlapping frequency combination of BDS-3, Galileo, GPS and QZSS is analyzed based on data collected from several multi-frequency and multi-constellation receivers capable of tracking the new signals of the BDS-3. The results show that ① The intraday changes of DPB of BDS-3, Galileo, GPS and QZSS are obvious and have a strong correlation with temperature. ② There is a strong correlation between the DPB of the overlapping frequency combinations of BDS-3, Galileo, GPS and QZSS. ③ There is a significant correlation between changes in DPB based on the baseline of the same type of combination.

Preliminary study on theory and method of ground-based GNSS-IR wind speed

WANG Xiaolei, HE Xiufeng, CHEN Shu, ZHANG Qin, SONG Minfeng

2021, 50(10):  1298-1307.  doi:10.11947/j.AGCS.2021.20200586

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With the development of Global Navigation Satellite Systems (GNSS), the multipath effect that was once regarded as one error source has been proven can be used to monitor reflecting surface parameters such as water level, snow depth, vegetation water content, and soil moisture using a technology named GNSS-interferometry reflectomety (GNSS-IR). In order to expand monitoring objects and applications of GNSS-IR, this paper proposed the theory and method to retrieve wind speed using ground-based GNSS-IR. The theory includes the signal-to-noise ratio (SNR) multipath oscillation theory, the scattering model theory, and wave spectrum theory. This paper simulated the mathematical model between the SNR cutoff elevation angle and the wind speed, and used the wavelet analysis to extract SNR cutoff elevation angle and a unified method to unify reference of cutoff elevation angle. Data of HKQT station, located in Hong Kong, during the period of "Mangkhut" and "Hato" were used. The results showed that the variations of GPS L5 SNR cutoff elevation angles had a good corresponding relationship with the measured wind speeds, and the correlation coefficient reached 70%~85%. Also, the variations of cutoff elevation angles can describe the change of wind speed from low wind speed to high wind speed and there was a specific mathematical relationship between them. Finally, this paper discussed two difficulties to overcome in the GNSS-IR wind speed retrieval technology.

Some numerical quadrature for singular integral of the altimetry gravity in the innermost area

ZONG Jingwen, LI Houpu, JI Bing, OUYANG Yongzhong

2021, 50(10):  1308-1319.  doi:10.11947/j.AGCS.2021.20200564

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In order to simplify the calculation process and improve the calculation efficiency of inverse Stokes formula method and the inverse Vening-Meinesz formula method to invert the gravity anomaly, the numerical quadrature method is adopted. A new study on the investigation of singular integral of inverse Stokes formula and inverse Vening-Meinesz formula based on Simpson formula and Cotes formula is done and the formula of gravity anomaly in innermost area are derived systematically. The analysis based on the theoretical model of geoidal height and vertical deflections shows that the formula can directly use the geoid height and vertical deviation at the grid node to calculate the gravity anomaly which have simple form, high precision and high calculation efficiency.These research results can provide theoretical basis for high-precision satellite altimetry inversion of gravity anomalies.

An empirical model for the vertical correction of precipitable water vapor considering the time-varying lapse rate for Mainland China

HUANG Liangke, MO Zhixiang, LIU Lilong, XIE Shaofeng

2021, 50(10):  1320-1330.  doi:10.11947/j.AGCS.2021.20200530

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Atmospheric precipitable water vapor (PWV) plays a key role in the study of global climate change and numerical weather prediction. However, the vertical correction of PWV mainly relies on a simple empirical correction model at present, which limite the high precision fusion of multi-source water vapor products and the comparisons between different water vapor products in a way. In this paper, for the characteristics of highly undulating terrain and diverse climate in China, the PWV vertical correction models which considering the time-varying lapse rate according to the whole areas in Mainland China and geographical divisions, named as C-PWVC1 model and C-PWVC2 model respectively, are established using ERA5 reanalysis data provided by the European Center for Medium Range Weather Forecast (ECMWF) from 2012 to 2017. Taking the profiles of 86 radiosonde stations in China in 2017 as reference values, the ERA5 and MERRA-2 reanalysis gridded data are interpolated into radiosonde stations to evaluate the performance of the newly established models, respectively. The results show that the performance of C-PWVC1 and C-PWVC2 models in PWV vertical correction is comparable. Compared with the condition without vertical correction, the performances of the C-PWVC model for ERA5 and MERRA-2 are improved by 16% and 8%, respectively. Compared with the commonly used PWV vertical correction model, C-PWVC model has little improvement for ERA5, but 12% for MERRA-2. C-PWVC model shows significant advantages when the height difference between two kinds of PWVs is large, and the correction capability for MERRA-2 is greater than ERA5. Moreover, for the ERA5 with different spatial resolutions, C-PWVC model has better interpolation precision and stability when compared with the commonly used PWV vertical correction model, especially in southern and western China. Therefore, the C-PWVC model has a good performance in PWV vertical correction for Mainland China, which can provide important application for the comparison and fusion of multi-source water vapor products in China.

Analysis of glacier changes in the Nyainqentanglha Mountain based on the combination of satellite gravity and optical remote sensing

ZHOU Miao, CHANG Xiaotao, ZHU Guangbin, QU Qingliang, LIU Wei

2021, 50(10):  1331-1337.  doi:10.11947/j.AGCS.2021.20200463

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The GRACE and GRACE-FO gravity satellite data were used to retrieve the glacier quality changes in the Nyainqentanglha Mountains from August 2002 to April 2020, and combined with remote sensing technology to estimate the glacier area and reserves changes in the western Nyainqentanglha. The main conclusions are as follows:①The glaciers in the Nyainqentanglha Mountains showed an overall retreat trend during the study period, and there was an accelerated melting trend after 2013. ②The correlation between temperature changes and glacier melting curves can be found by comparing with summer temperature changes and precipitation anomalies better, the precipitation continued to decrease during the study period, indicating that the increase in temperature and the decrease in precipitation are the main reasons for the continuous decrease in the mass of glaciers in the Nyainqentanglha. ③The glacier area of the West Nyainqentanglha Mountains decreased by 72.30 km² from 2003 to 2017, with an average annual decrease rate of 5.16 km²/a. The glacier area retreats most obviously in the altitude range of 5600~5800 m. ④The coordinated application of satellite gravity and optical remote sensing technology can complement each other's advantages. It can not only estimate changes in glacier quality, but also detect changes in glacier area and elevation. At present, there are still some shortcomings in the joint application of the two technologies, which need to be further studied.

Photogrammetry and Remote Sensing

Processing and preliminary accuracy validation of the GF-7 satellite laser altimetry data

LI Guoyuan, TANG Xinming, CHEN Jiyi, YAO Jiaqi, LIU Zhao, GAO Xiaoming, ZUO Zhiqiang, ZHOU Xiaoqing

2021, 50(10):  1338-1348.  doi:10.11947/j.AGCS.2021.20210025

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GF-7 satellite is equipped with the first full waveform laser altimeter of China for earth observation, which is mainly used to obtain sparse elevation control points on the ground, and ultimately improve the stereo mapping accuracy of stereo images without ground control points. The laser altimetry standardization processing of GF-7 satellite is the key step of surveying and mapping application, and the generated laser altimetry standard products are the important premise of subsequent distribution and application. Based on the GF-7 satellite laser altimetry data, this paper studies the method of laser altimetry data processing, and preliminarily validates the geometric accuracy of laser altimetry standard products. Three regions are selected to validate the accuracy of GF-7 satellite laser altimetry standard products, which contain the domestic geometric calibration area, Huayin of Shaanxi province, North Rhine-Westphalia of Germany. The results show that the planimetric accuracy of laser altimetry standard products SLA03 in calibration area is (3.896±1.029)m and (3.286±0.337)m, and elevation accuracy is (0.018±0.099)m,(-0.017±0.096)m in respectively for the two-beam lasers. Moreover, the elevation control point quality control parameter ECP_Flag can effectively identify the laser points that can be used for elevation control. The overall accuracy of Shaanxi Huayin area is (-0.113±2.519)m and (0.191±1.071)m, respectively for the two beams. The elevation accuracy of laser points marked with ECP_Flag=1 is (0.111±0.152)m and (-0.064±0.115)m. The overall accuracy of Norwich in Germany is (-0.897±5.485)m and (-0.202 ±6.207)m, and the elevation accuracy of laser points marked with ECP_Flag=1 is (-0.304±0.190)m and (-0.279±0.220)m, respectively for the two beams. At present, the laser altimetry standard products of GF-7 satellite have been daily produced in the Land Satellite Application Center of the Ministry of Natural Resources.

Change detection of remote sensing images by combining neighborhood information and structural features

YE Yuanxin, SUN Miaomiao, WANG Mengmeng, TAN Xin

2021, 50(10):  1349-1357.  doi:10.11947/j.AGCS.2021.20200130

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In order to improve the accuracy of pixel-level change detection methods, this paper proposes a novel change detection method for remote sensing images by combining neighborhood information (including the neighborhood correlation image (NCI) and matching errors) and structural features. First, a technique of neighborhood correlation analysis is used to obtain the NCI which represents the context information, and the cross-correlation of neighborhood pixels is used to obtain matching errors by a template matching scheme. Then, structure features of images are extracted using orientated gradient information, which are robust to spectral differences between images. Subsequently, the initial change detection results is obtained by using the NCI, the matching errors, and structural features as the classification attributes of a decision tree. Finally, the Markov Random Field (MRF) is used to optimize the results, yielding the final binary map. The proposed method has been evaluated with two sets of bi-temporal remote sensing images from different sensors. Experimental results demonstrate that this method effectively improves the accuracy of change detection compared with the change vector analysis method, the single neighborhood information method and the method combining neighborhood information and texture features.

Graph convolutional network method for small sample classification of hyperspectral images

ZUO Xibing, LIU Bing, YU Xuchu, ZHANG Pengqiang, GAO Kuiliang, ZHU Enze

2021, 50(10):  1358-1369.  doi:10.11947/j.AGCS.2021.20200155

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Existing based on convolutional neural network classification method of hyperspectral images usually rules of the square area of image convolution, not widely adapt to different terrain local area distribution and geometry appearance of the image, therefore, under the condition of small sample classification performance is poorer, and figure convolution can network topology information on the map represent irregular image area of the convolution. Therefore, a hyperspectral image classification method based on graph convolution network is proposed. In this method, the spatial spectral information of the image is considered in the process of constructing the graph, and the feature information of the neighbor node is aggregated by the graph convolution network. Experimental results on three data sets, Pavia university, Indian Pines and Salinas, show that this method can achieve a high classification accuracy with a small number of training samples.

Water extraction model of multispectral optical remote sensing image

DENG Kaiyuan, REN Chao

2021, 50(10):  1370-1379.  doi:10.11947/j.AGCS.2021.20200482

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Accurate monitoring of surface water is an important basic application of remote sensing. The principle of optical remote sensing water extraction is based on different ground features having different spectral reflection characteristics. Some ground features (ice, snow, shadows, clouds) have similar reflection characteristics to water bodies, which leads to the failure of extraction and classification. Aiming at the problem of misclassification and omission of traditional water body index in water body extraction, this paper proposes a normalized difference multi-band water index model. This paper uses two experiments to test the stability of the new index. The area of experiment 1 is the Linzhi area of Tibet. The data source is Landsat 8 and Sentinel 2 satellite images in the same time phase. The experimental results verify the ability of the new index to suppress snow and ice. The Kappa coefficient of the new index is 0.86, the overall accuracy is 0.93, and the misclassification error is 0.03, the omission error is 0.12, the drawing accuracy is 0.97, and the producer accuracy is 0.88, which are better than the existing index. The data source of experiment 2 was GF-1, and Hong Kong Disneyland was used as the experimental area. Experiment 3 extracted water bodies in multiple regions and verified the stability of the water body index in this paper. Water extraction was performed in an environment with a small amount of clouds, which proved that the new index can suppress clouds and their shadows. This paper uses multi-source optical remote sensing image to verify the feasibility of the new index. Without additional auxiliary data, the influence of snow, cloud and shadow can be eliminated, and the water can be more effectively and automatically extracted, which can be extended to coastal resource research, glacier change, inland lake change and other fields.

Non-subsampled shearlet transform remote sensing image fusion combined with parameter-adaptive PCNN

CHENG Feifei, FU Zhitao, HUANG Liang, CHEN Pengdi, HUANG Kun

2021, 50(10):  1380-1389.  doi:10.11947/j.AGCS.2021.20200589

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In order to solve the problem that the parameters of pulse-coupled neural network can't be adjusted adaptively in pan-sharpening image fusion, a non-subsampled shearlet transform remote sensing image fusion method based on the combination of parametric-adaptive pulse coupled neural network model and energy-attributing fusion strategy is proposed. First, the high and low frequency coefficients are obtained by extracting the Y luminance component of the multispectral image YUV color space transform and transforming it with the panchromatic image. Then, aiming at the low-frequency sub-band coefficients are fused by the EA method, the high-frequency sub-band coefficients are obtained by the PA-PCNN model to determine the optimal PCNN model, and then the high-frequency sub-band coefficients are fused; finally, the fusion image is obtained by inverse transformation of NSST and YUV. In this paper, six objective quality indexes, such as spatial frequency, relative dimensionless global error, ERGAS, correlation coefficient, visual information fidelity for fusion, gradient-based fusion performance and structural similarity index, are selected to evaluate the spectral and spatial detail information of the fused images, compared with SE, DGIF, COF and PA-PCNN fusion methods, the proposed method is validated by using multiple sets of high-and low-resolution panchromatic and multispectral remote sensing images, the results show that this method is generally superior to the traditional fusion method of panchromatic and multispectral remote sensing images in objective evaluation and visual perception.

A fast matching method of SAR and optical images using angular weighted orientated gradients

FAN Zhongli, ZHANG Li, WANG Qingdong, LIU Siting, YE Yuanxin

2021, 50(10):  1390-1403.  doi:10.11947/j.AGCS.2021.20200587

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To solve the problem of matching difficulty caused by the significant nonlinear grayscale differences between SAR and optical images, this paper proposes a fast matching algorithm based on image structural properties named SOFM(SAR-to-optical fast matching algorithm).The traditional methods based on image grayscale are generally difficult to resist the nonlinear grayscale differences between SAR and optical images, but the geometric constructs and shape features can exist stably among different types of images, so in our the proposed method both the magnitude and orientation information of image gradient are used to build a geometric structural feature descriptor named AWOG(angular weighted orientated gradients), then based on the template matching strategy, the sum of squared difference of the descriptors is used to define the similarity metric for matching and then the image matching function expressed in the frequency domain is given. A complete set of image matching process is established based on SOFM, and has been validated using multiple pairs of SAR and optical images, the results show that the proposed method can effectively resist the nonlinear grayscale differences between SAR and optical images, and outperforms the traditional classical image grayscale-based methods and existing image structural-based methods in matching performance and precision.

Cartography and Geoinformation

Latent semantic understanding of geographical environment spatio-temporal data based on topic model

ZHU Jie, ZHANG Hongjun, LIAO Xianglin, TIAN Jiangpeng

2021, 50(10):  1404-1415.  doi:10.11947/j.AGCS.2021.20200380

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Text is an important data mode of battlefield information. Mining spatial-temporal semantic information of geographical environment from battlefield text is an important method for machine to understand battlefield environment, which is helpful to expand battlefield environment spatial cognition and understanding. A method based on topic model is designed to reflect the semantic relationship between geographical spatio-temporal factors and event topics, and different topic classification with its distribution of word features are formed by the method of information extraction to mine the relevant information of topic elements; the joint distribution model of event topic and geographical spatio-temporal semantic features is established to automatically discover the correlation among time, space and event topics, thus generating the latent geographical spatio-temporal semantic topics; through the experimental verification and the application practice, we believe that the law of spatio-temporal distribution under different topics can be seek by using correlation between the event topics and location information with spatial analysis method, so as to provide the basis for the location prediction of new events and the countermeasures of seeking advantages and avoiding disadvantages, and expand the traditional thematic analysis of geographical events.

Summary of PhD Thesis

Study on optimization problem of Wi-Fi/PDR indoor hybrid positioning on smartphone

BI Jingxue

2021, 50(10):  1416-1416.  doi:10.11947/j.AGCS.2021.20200408

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Application of radial basis function in gravity field modeling and data fusion

MA Zhiwei

2021, 50(10):  1417-1417.  doi:10.11947/j.AGCS.2021.20200409

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Secular variation of gravity anomalies within the Tibetan Plateau derived from GRACE data

LIU Jie

2021, 50(10):  1418-1418.  doi:10.11947/j.AGCS.2021.20200410

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Development of surface roughness and soil moisture retrieval algorithm using passive microwave remote sensing data

WANG Shu

2021, 50(10):  1419-1419.  doi:10.11947/j.AGCS.2021.20200425

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Experimental study on the effect of roughness and observation angle on thermal infrared spectra characteristics and unmixing of rock

LI Tianzi

2021, 50(10):  1420-1420.  doi:10.11947/j.AGCS.2021.20200428

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