ALBERT

Description: Sensors, Vol. 18, Pages 3114: Application of Time-Domain Full Waveform Inversion to Cross-Hole Radar Data Measured at Xiuyan Jade Mine, China Sensors doi: 10.3390/s18093114 Authors: Sixin Liu Xintong Liu Xu Meng Lei Fu Qi Lu Li Deng Xiuyan Jade, produced in Xiuyan County, Liaoning Province, China is one of the four famous jade in China. King Jade, which is deemed the largest jade body of the world, was broken out from a hill. The local government planned to build a tourism site based on the jade culture there. The purpose of the investigation was to evaluate the stability of subsurface foundation, and the possible positions of mined-out zones to prevent the further rolling of the jade body. Cross-hole radar tomography is the key technique in the investigation. Conventional travel time and attenuation tomography based on ray tracing theory cannot provide high-resolution images because only a fraction of the measured information is used in the inversion. Full-waveform inversion (FWI) can provide high-resolution permittivity and conductivity images because it utilizes all the information provided by the radar signals. We deduce the gradient expression of the time-domain FWI with respect to the permittivity and conductivity using a method that is different from that of the previous work and realize the FWI algorithm that can simultaneously update the permittivity and conductivity by using the conjugate gradient method. Inverted results from synthetic data show that time-domain FWI can significantly improve the resolution compared with the ray-based tomogram methods. FWI can distinguish targets that are as small as one-half to one-third wavelength and the inverted physical values are closer to the real ones than those provided by the ray tracing method. We use the FWI algorithm to the field data measured at Xiuyan jade mine. Both the inverted permittivity and conductivity can comparably delineate four mined-out zones, which exhibit low-permittivity and low-conductivity characteristics. Furthermore, the locations of the interpreted mined-out zones are in good agreement with the existing mining channels recorded by geological data.

Description: Atmosphere, Vol. 9, Pages 323: Analysis on the Changes of Agro-Meteorological Thermal Indices in Northeast China under RCP4.5 Scenario Using the PRECIS2.1 Atmosphere doi: 10.3390/atmos9080323 Authors: Xinhua Li Yinlong Xu Chunchun Meng Lei Zhang Changgui Wang As a main grain production area in China, Northeast China (NEC) is highly influenced by the higher warming trend than elsewhere in China or even the globe. As the warming trend goes on, scientific understanding of the changes of thermal conditions in NEC will be essential for taking agricultural adaptation measures. In this paper, the high-resolution (25 km) corrected outputs of PRECIS (Providing Regional Climates for Impacts Studies) under the Representative Concentration Pathway 4.5 (RCP4.5) scenario were used to analyze the changes of the agro-climatic thermal resources in NEC. Results showed that accumulated temperature ≥10 °C (AT10) could increase by 300–500 °C·day, 500–900 °C·day, and 750–1000 °C·day in 2011–2040 (2020s), 2041–2070 (2050s), and 2071–2100 (2080s), respectively, relative to the baseline period of 1961–1990. The potential growing season (PGS) would then be prolonged by 11–19 days, 23–35 days, and 25–37 days in 2020s, 2050s and 2080s, respectively, compared to baseline. The spatial features for the changes of thermal indices would show a large increase of AT10 and an extension of PGS and Frost-free period (FFP) in mountainous areas compared to plains; the increment of AT10 would be greater in southern NEC than that in the north, with over 1000 °C·day in the southern parts and 700–800 °C·day in the northern parts in the 2080s. Additionally, the three thermal indices would increase rapidly from 2020s to 2050s compared to the period from 2050s to the 2080s, coincides with the greenhouse gas concentrations peak around the mid-period of the 21st century, and the decline towards the end of the 21st century under RCP4.5 forcing. The results of this paper could act as a guide to taking advantage of increasing thermal resources in NEC, and would be helpful for local practitioners in decision-making.

Description: In this paper, we propose a novel method to continuously monitor land cover change using satellite image time series, which can extract comprehensive change information including change time, location, and “from-to” information. This method is based on a hidden Markov model (HMM) trained for each land cover class. Assuming a pixel’s initial class has been obtained, likelihoods of the corresponding model are calculated on incoming time series extracted with a temporal sliding window. By observing the likelihood change over the windows, land cover change can be precisely detected from the dramatic drop of likelihood. The established HMMs are then used for identifying the land cover class after the change. As a case study, the proposed method is applied to monitoring urban encroachment onto farmland in Beijing using 10-year MODIS time series from 2001 to 2010. The performance is evaluated on a validation set for different model structures and thresholds. Compared with other change detection methods, the proposed method shows superior change detection accuracy. In addition, it is also more computationally efficient.