ABSTRACT:Vegetation plays a leading role in ecosystems. Plant communities are the main components of ecosystems. Green plants in ecosystems are the primary producers, and they provide the living organic matter for the survival of other organisms. The dynamics of most landscapes are driven by both natural processes and human activities. In this study, the growing season GIMMS NDVI3g and climatic data were used to analyse the vegetation trends and drivers in Beijing-Tianjin-Hebei region from 1982 to 2013. Result shows that, the vegetation in Beijing-Tianjin-Hebei region shows overall restoration and partial degradation trend. The significant restoration region accounts for 61.5% of Beijing-Tianjin-Hebei region, while the significant degradation region accounts for 2.1%. The dominant climatic factor for time series NDVI were analyzed using the multi-linear regression model. Vegetation growth in 17.9% of Beijing-Tianjin-Hebei region is dominated by temperature, 35.5% is dominated by precipitation, and 11.68% is dominated by solar radiance. Human activities play important role for vegetation restoration in Beijing-Tianjin-Hebei Region, where the large scale forest restoration programs are the main human activities, such as the three-north shelterbelt construction project, Beijing-Tianjin-Hebei sandstorm source control project and grain for green projects.
Abstract. In order to study the land subsidence trend since the construction of the Xiong’an New Area, 125 images of Sentinel-1 from January 2017 to September 2020 was obtained in this paper, and the average land subsidence rate and cumulative land subsidence of Xiong’an New Area is obtained by the SBAS-InSAR technology of multi-main image coherent target by GAMMA and the Self-developed software, and the causes of land subsidence from the geographical space in the Xiong’an New Area were analyzed by the divisional timing analysis method. The results showed that about 80% of Xiong’an New Area had slight land subsidence with the rate less than 1cm/yr and the cumulative subsidence less than 3cm, and the maximum subsidenc occurred in the northern of Xiongxian County with rate 7cm/yr and the cumulative subsidence was 30cm. Furthermore, the average subsidence rate and the cumulative maximum subsidence in the north and the northwest of Xiongxian County, the Baima Village and the Beifeng Village were studied. The research results showed that the land subsidence in Xiong’an New Area was related to the over exploitation of geothermal resources and groundwater, and the results could provide important reference values for keep abreast of the land subsidence status of the Xiong’an New Area, as well as the healthy development and long-term planning of the New Area.
ABSTRACT:Due to the improvement of satellite radiometric resolution and the color difference for multi-temporal satellite remote sensing images and the large amount of satellite image data, how to complete the mosaic and uniform color process of satellite images is always an important problem in image processing. First of all using the bundle uniform color method and least squares mosaic method of GXL and the dodging function, the uniform transition of color and brightness can be realized in large area and multi-temporal satellite images. Secondly, using Color Mapping software to color mosaic images of 16bit to mosaic images of 8bit based on uniform color method with low resolution reference images. At last, qualitative and quantitative analytical methods are used respectively to analyse and evaluate satellite image after mosaic and uniformity coloring. The test reflects the correlation of mosaic images before and after coloring is higher than 95% and image information entropy increases, texture features are enhanced which have been proved by calculation of quantitative indexes such as correlation coefficient and information entropy. Satellite image mosaic and color processing in large area has been well implemented.
KEY WORDS: Time Synchronization, GPS Common-View, GPSABSTRACT:In recent years, with the development of satellite orbit and clock parameters accurately determining technology and the popularity of geodetic GPS receivers, Common-View (CV) which proposed in 1980 by Allan has gained widespread application and achieved higher accuracy time synchronization results. GPS Common View (GPS CV) is the technology that based on multi-channel geodetic GPS receivers located in different place and under the same common-view schedule to receiving same GPS satellite signal at the same time,and then calculating the time difference between respective local receiver time and GPST by weighted theory, we will obtain the difference between above local time of receivers that installed in different station with external atomic clock。 Multi-channel geodetic GPS receivers have significant advantages such as higher stability、higher accuracy and more common-view satellites in long baseline time synchronization application over the single-channel geodetic GPS receivers. At present, receiver hardware delay and surrounding environment influence are main error factors that affect the accuracy of GPS common-view result. But most error factors will be suppressed by observation data smoothing and using of observation data from different satellites in multi-channel geodetic GPS receiver. After the SA(Selective Availability)cancellation, Using a combination of precise satellite ephemeris ,ionospheric-free dual-frequency P-code observations and accurately measuring of receiver hardware delay, we can achieve time synchronization result on the order of nanoseconds (ns). In this paper, 6 days observation data of two IGS core stations with external atomic clock (PTB, USNO distance of two stations about 6000 km) were used to verify the GPS common-view theory. Through GPS observation data analysis, there are at least 2-4 common-view satellites and 5 satellites in a few tracking periods between two stations when the elevation angle is 15 °,even there will be at least 2 common-view satellites for each tracking period when the elevation angle is 30°. Data processing used precise GPS satellite ephemeris, double-frequency P-code combination observations without ionosphere effects and the correction of the Black troposphere Delay Model. the weighted average of all common-viewed GPS satellites in the same tracking period is taken by weighting the root-mean-square error of each satellite, finally a time comparison data between two stations is obtained, and then the time synchronization result between the two stations (PTB and USNO) is obtained. It can be seen from the analysis of time synchronization result that the root mean square error of REFSV (the difference between the local frequency standard at the mid-point of the actual tracking length and the tracked satellite time in unit of 0.1 ns) shows a linear change within one day, However the jump occurs when jumping over the day which is mainly caused by satellites position being changed due to the interpolation ...
Abstract. Inspired by the immense success of deep neural network in image processing and object recognition, learning-based image super resolution (SR) methods have been highly valued and have become the mainstream direction of super resolution research. Base on the recent proposed state-of-art convolution neural network (CNN) super-resolution methods, this paper proposed a generative adversarial network for single satellite image Super Resolution reconstruction. It built on a trained deep residual network to generate preliminary SR images, combined with a discriminative network learns to differentiate preliminary SR images and High resolution samples. The experiments results show that our method can use existing model parameters to refine SR image performance.
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