AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION

In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection.

THE REMOTE SENSING IN COAL GEOLOGY——A study on detection of coal spontanous burning by remote sensing in the coal fields in the north of China

The spontaneous burning has been lasting for thousands of years in the coal fields in the north of China. It spreads from the west (Tianshan coal field) to the east (Huolinhe coal field). Its E-W extension is up to 3750km, concentrating in N35°toN45°, its vertical depth up to 260m, and the surface temprature locally up to 270℃. Annually, it burns out 0, 250-300 million tones of coal, causing economic loss equivalent to 2-3 billion R.M.B. Yuan.It destroies coal resources and causes hazards in coal mines. In order to locate the extent and the direction in coal burning areas, the remote sensing technique has heen used and has produced an obvious benefit.

Sensing Time Optimization in Energy-Harvesting Cognitive Radio with Interference Rate Control

In this paper,an energy-harvesting cognitive radio(CR) is considered,which allows the transmitter of the secondary user(SU) to harvest the primary signal energy from the transmitter of the primary user(PU) when the presence of the PU is detected.Then the harvested energy is converted into the electrical power to supply the transmission of the SU at the detected absence of the PU.By adopting the periodic spectrum sensing,the average total transmission rate of the SU is maximized through optimizing the sensing time,subject to the constraints of the probabilities of false alarm and detection,the harvested energy and the interference rate control.The simulation results show that there deed exists an optimal sensing time that maximizes the transmission rate,and the maximum transmission rate of the energy-harvesting CR can better approach to that of the traditional CR with the increasing of the detection probability.

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.

TEST STUDY OF DETECTING OIL AND GAS BY USING REMOTE SENSING TECHNIQUE

Ⅰ The Indexes of Detecting Oil and Gas Resources The deeply buried reservoir which in a dynamic equilibrium state has a great pressure inside, and between it and earth surface there is a great difference of pressure. Therefore the hydrocarbon must spread and move vertically to the surface along the pressure gradient orientation. Hydrocarbons in the reservoir along some small rifts, cracks, joints and cleavages penetrate the overlying strata and seepage onto the surface. Thus the hydrocarbons become unvisble oil and gas signs. This process is called the phenomena of hydrocarbon microseepage of reservoir. Hydrocarbons microseepage in the process

Mechanistic study of TPE-Ph COF for fluorescent ammonia detection

In this study,the interaction between TPE-Ph COF and ammonia molecules,as well as the mechanism of fluorescence detection of ammonia,were comprehensively investigated using density functional theory(DFT)and time-dependent density functional theory(TD-DFT).It was found that the binding between TPE-Ph COF and ammonia molecules occurs primarily through coordination bonds or hydrogen bonds.Specifically,the formation of coordination bonds significantly changes the intramolecular charge transfer of TPE-Ph COF,leading to fluorescence quenching.Computational analysis revealed the changes in electron and hole distributions upon the binding of ammonia to TPE-Ph COF,as well as the competition between nonradiative and radiative transitions during the photophysical processes,thereby elucidating the intrinsic mechanism of fluorescence response.

Novel conductive metallo-supramolecular polymer AIE gel for multi-channel highly sensitive detection of hydrazine hydrate

Hydrazine hydrate(DH)is an important fine chemical intermediate and as fuel for rockets,however,it also has serious toxic for humans and environment.Developing novel materials and methods for sensitive detection of DH in water and air is an important task.In order to effectively detect DH,a novel conductive supramolecular polymer metallogel(PQ-Ag)has been constructed by the coordination of bis-5-hydroxyquinoline functionalized pillar[5]arene(PQ5)with Ag+.The metallogel PQ-Ag could realize the multi-channel sensitive detection of DH through naked-eye,fluorescence,and electrochemical methods.The lowest limit of detection(LOD)is 0.1 mg/m^(3)in air and 2.68×10^(−8)mol/L in water,which is lower than the standard of the US Environmental Protection Agency(EPA)for DH of maximum allowable concentration in drinking water.More importantly,an electronic device for DH detection based on the metallogel PQ-Ag was designed and prepared,which can realize conveniently and efficiently multi-channel detection and alert of DH through sound and light alarms not only in water but also in air.

Monitoring of winter wheat distribution and phenological phases based on MODIS time-series： A case study in the Yellow River Delta, China

Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.

Sensorless Sensing with WiFi

Can WiFi signals be used for sensing purpose？ The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world＇s largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications.

RS analysis of glaciers change in the Heihe River Basin, Northwest China, during the recent decades

The Heihe River Basin is the second largest inland river basin in Northwest China and it is also a hotspot in arid hydrology, water resources and other aspects of researches in cold regions. In addition, the Heihe River Basin has complete landscape, moderate watershed size, and typical social ecological environmental problems. So far, there has been no detailed assessment of glaciers change information of the whole river basin. 1：50,000 topographic map data, Landsat TM/ETM＋ remote sensing images and digital elevation model data were used in this research. Through integrated computer automatic interpretation and visual interpretation methods, the object-oriented image feature extraction method was applied to extract glacier outline information. Glaciers change data were derived from analysis, and the glacier variation and its response to climate change in the period 1956/1963–2007/ 2011 were also analyzed. The results show that：（1） In the period 1956/1963–2007/2011, the Heihe River Basin＇s glaciers had an evident retreat trend, the total area of glaciers decreased from 361.69 km2 to 231.17 km^2; shrinking at a rate of 36.08%, with average single glacier area decrease 0.14 km^2; the total number of the glaciers decreased from 967 to 800.（2） Glaciers in this basin are mainly distributed at elevations of 4300–4400 m, 4400–4500 m and 4500–4600 m; and there are significant regional differences in glaciers distribution and glaciers change.（3） Compared with other western mountain glaciers, glaciers retreat in the Heihe River Basin has a higher rate.（4） Analysis of the six meteorological stations＇ annual average temperature and precipitation data from 1960 to 2010 suggests that the mean annual temperature increased significantly and the annual precipitation also showed an increasing trend. It is concluded that glacier shrinkage is closely related with temperature rising, besides, glacier melting caused by rising temperatures greater than glacier mass supply by increased precipitation to some extent.