This PDF file contains the front matter associated with SPIE Proceedings Volume 9299, including the Title Page, Copyright information, Table of Contents, Authors, Introduction (if any), and Conference Committee listing.

The harm of oil spills has caused extensive public concern. Remote sensing technology has become one of the most effective means of monitoring oil spill. However, how to evaluate the information extraction capabilities of various sensors and choose the most effective one has become an important issue. The current evaluation of sensors to detect oil films was mainly using in-situ measured spectra as a reference to determine the favorable band, but ignoring the effects of environmental noise and spectral response function. To understand the precision and accuracy of environment variables acquired from remote sensing, it is important to evaluate the target detection sensitivity of the entire sensor-air-target system corresponding to the change of reflectivity. The measurement data associated with the evaluation is environmental noise equivalent reflectance difference (NEΔRE ), which depends on the instrument signal to noise ratio(SNR) and other image data noise (such as atmospheric variables, scattered sky light scattering and direct sunlight, etc.). Hyperion remote sensing data is taken as an example for evaluation of its oil spill detection capabilities with the prerequisite that the impact of the spatial resolution is ignored. In order to evaluate the sensor’s sensitivity of the film of water, the reflectance spectral data of light diesel and crude oil film were used. To obtain Hyperion reflectance data, we used FLAASH to do the atmospheric correction. The spectral response functions of Hyperion sensor was used for filtering the measured reflectance of the oil films to the theoretic spectral response. Then, these spectral response spectra were normalized to NEΔRE, according to which, the sensitivity of the sensor in oil film detecting could be evaluated. For crude oil, the range for Hyperion sensor to identify the film is within the wavelength from 518nm to 610nm (Band 17 to Band 26 of Hyperion sensors), within which the thin film and thick film can also be distinguished. For light diesel oil film, the range for Hyperion sensor to identify the film is within the wavelength from 468nm to 752nm (Band 12 to Band 40 of Hyperion sensors).

In the north China Sea district, sea ice disaster is very serious every winter, which brings a lot of adverse effects to shipping transportation, offshore oil exploitation, and coastal engineering. In recent years, along with the changing of global climate, the sea ice situation becomes too critical. The monitoring of sea ice is playing a very important role in keeping human life and properties in safety, and undertaking of marine scientific research. The methods to monitor sea ice mainly include: first, shore observation; second, icebreaker monitoring; third, satellite remote sensing; and then aerial remote sensing monitoring. The marine station staffs use relevant equipments to monitor the sea ice in the shore observation. The icebreaker monitoring means: the workers complete the test of the properties of sea ice, such as density, salinity and mechanical properties. MODIS data and NOAA data are processed to get sea ice charts in the satellite remote sensing means. Besides, artificial visual monitoring method and some airborne remote sensors are adopted in the aerial remote sensing to monitor sea ice. Aerial remote sensing is an important means in sea ice monitoring because of its strong maneuverability, wide watching scale, and high resolution. In this paper, several methods in the sea ice monitoring using aerial remote sensing technology are discussed.

Due to diastrophism, tide action and human activities, the coastline is always in flux. There are lots of coral islands in the south sea of China. Remote sensing survey for the coastline not only can reassert the necessity and importance of coral protection, but also can provide basic data and scientific basis for island ecologic protection, reasonable utilization of land resources. The study area named Zhao Shu Island lies in Jintong Islands of Xisha. It is a coral island which has people inhabited. Using WorldView-2 satellite remote sensing images as data sources we carry out three phases of coastline investigation and monitoring. The satellite data phases are 2002, 2010 and 2013. Firstly, affirm the bands valuable for color composition on the basis of spectral and correlation analysis. Then extract the coastline by a series of image process, such as image correction, fusion, waterline extraction and coastline revision. Finally determine the coastline types and length by artificial interpretation. The results show that the island length is gradually smaller, which means the island area is reducing. The beach bedrock coast in northern island was eroded seriously especially during the period between 2010 and 2013. In addition, the shoal head shape in the western island changed a lot.

In this paper, the operating principle of daylight UV imagers was introduced first, emphasizing the SBUV(solar blind UV) technology, which utilizes the fact that ultra violet between 240nm~280nm is being absorbed by the ozone so that signals detected on earth in this spectral range originate on earth. And then several influencing factors were explained, including observation distance, observing angle, imager gain settings and environmental conditions. Experimental data measured in the UHV(ultra high-voltage) DC converter station in Changzhi, Shanxi, China were analyzed using SRA(single regression analysis) method, and mathematical equations with acceptable deviation were calculated, with simulating curves plotted. The results show that environmental conditions including humidity and temperature, observation distance and imager gain settings all contribute to the measuring result, exhibiting as exponential function and convex function respectively. Concluded from the above analysis and calculation, observing conditions of a clear observing angle at the same observation distance with mediate gain settings on days of low humidity were recommended. This conclusion may guide further ultra-violet imaging appliance in high-voltage electrical devices corona discharge sensing.

This paper provides a relative radiometric calibration method based on the linear CCD imaging the same region of non-uniform scene, which makes full use of the ability of yaw angle control to ensure all the linear CCD detectors imaging the same scene. Firstly, when it is needed to perform the satellite relative radiometric calibration task, the initial drift angle will be calculated, according to which the yaw angle can be adjusted to ensure on-orbit satellite performing the calibration imaging mode, and in this mode the linear CCD and the satellite motion are in the approximate direction. Secondly, in calibration imaging process the yaw angle will be continuously adjusted to control the push-broom direction, and the linear CCD camera can be sequentially on the same region of non-uniform scene, which can obtain the remote-sensing image observing the same region with all the CCD detectors. Finally, after obtaining the same region image with the linear CCD camera, histogram matching method is used to establish the high-precision nonlinear relative radiometric calibration model, and this method overcomes the nonlinear response problem caused by the camera photon noise, the dark current noise. This method needs neither the on orbit calibration device, nor the ground uniform scaling field, and the general earth observation scene can meet the requirements. This method does not need a lot of on-orbit imaging data for statistical analysis compared with the statistical method, and each track is scaled to meet the conditions for calibration imaging, which avoids the unreliable problem of the calibration source itself caused by the unstable differences between the different tracks.

Micro pulse lidar(MPL) is an effective tool for atmospheric aerosol and cloud detecting. In order to make the structure of the micro pulse lidar more compact, solve the problem that it always very difficult to adjust the transmitting and receiving optical paths to parallel in the traditional system, avoid the influence of the geometric overlap factor and reduce the complexity of the data processing, Anhui institute of optics and fine mechanics of the Chinese academy of sciences designs a new type of micro pulse lidar, particularly designs the followed up optical unit of the micro pulse lidar. A combination of emitting and receiving fibers in a signal bundle changes the structure of the subsequent optical unit in the traditional system to make the transmitting and receiving optical paths coaxial. The public end of the Y type optical fiber bundle is composed of a transmitting optical fiber in the center and eight receiving optical fibers in the periphery. After a brief introduction of the new system, the key parameters of the new micro pulse lidar system and the Y type optical fiber bundle were described in some detail. In order to verify the feasibility of the new structure of the micro pulse lidar system, a continuous observation experiment was carried out in Hefei area to detect the horizontal distribution of the atmospheric aerosol and pollutions. The data measured in the experiment in the November 2013 was processed with Fernald method and the profile of the atmospheric aerosol horizontal extinction coefficient distribution was inverted. The data inversion results showed that: the data acquired by the new lidar system and the extinction coefficient distribution inverted by Fernald algorithm are all very reasonable, and the time-space distribution of atmospheric aerosols extinction coefficient can reflect the distribution of the atmospheric aerosol and pollutions near the ground effectively. All of the experiment results indicate that the design of the new micro pulse lidar system is effective.

A design scheme of transient light signal simulator based on Field Programmable gate Array (FPGA) was proposed in this paper. Based on the characteristics of transient light signals and measured feature points of optical intensity signals, a fitted curve was created in MATLAB. And then the wave data was stored in a programmed memory chip AT29C1024 by using SUPERPRO programmer. The control logic was realized inside one EP3C16 FPGA chip. Data readout, data stream cache and a constant current buck regulator for powering high-brightness LEDs were all controlled by FPGA. A 12-Bit multiplying CMOS digital-to-analog converter (DAC) DAC7545 and an amplifier OPA277 were used to convert digital signals to voltage signals. A voltage-controlled current source constituted by a NPN transistor and an operational amplifier controlled LED array diming to achieve simulation of transient light signal. LM3405A, 1A Constant Current Buck Regulator for Powering LEDs, was used to simulate strong background signal in space. Experimental results showed that the scheme as a transient light signal simulator can satisfy the requests of the design stably.

The development of laser range profile, Doppler spectra and Range Resolved Doppler imaging technologies including the experiments, simulations and engineering applications have been summarized and reviewed in this paper. It was analyzed the problems of the laser radar imaging system which need to solve in experiments and models. The achievements and the key technologies of Range profile, Doppler spectra and Range Doppler imaging laser radar are reported in detail. Different typically theoretical simulated models have been built to show the last technologies of target recognition for laser radar in order to be based on the further studying on designing the laser radar imaging systems in many applications and offering the precise data of the detected target.

A multi-spectral time delay and integration charge couple device(TDICCD) focal plane imaging and processing system is introduced in this paper. FPGA is the core logic control of the system. The main hardware component of the system and the implementation method of FPGA are described and the diagrams of main modules are presented. Software workflow and a variety of image processing methods are also given. Test results show that the design achieves data transfer speed of 4.48Gbps and realizes real-time processing of image for high-speed multi-channel TDICCD camera so that meets the system requirement.

Dunhuang Gobi site, a pseudo-invariant ground target, has been extensively used to calibrate the remote sensing instruments because of its high spatial and spectral uniformity and good temporal stability. Four Charge Coupled Device (CCD) sensors onboard HUANGJING-A/B (HJ-1A/B) satellites have been running 5-years since launched in 2008, and provided important remote sensing data for land surface reflectance retrieval, bio/geophysical variables estimation and environment pollution /disaster monitoring. The radiometric performance of HJ-1A/B CCD may change after launched because of many factors, thus, we have carried out many ground measurement campaigns at a pseudo-invariant test site-Dunhuang gobi to perform radiometric calibration of these sensors. This article describes the characteristics of Dunhuang gobi site and lifetime radiometric calibration monitoring results obtained for four CCD sensors. The results indicate that the long-term changes in calibration coefficients trending exceeding the dark-noise changes are primarily due to the drifts in the CCD radiometric responsivity, and the degradations of HJ-1A/B CCD are from -2.3%/year to -9.5%/year.

Spacing movable mechanic components are needed not only to move in wide range but also to complete series of actions with high degree of accuracy and stability when processing on orbit. So, visual monitor system including the surveillance and measuring cameras must be equipped to achieve precise spacing location and posture information, and monitor and administer of movable mechanic components can be realized combined with the algorithm. Based on the requirements of the camera and the after algorithm for the center of mass and the distribution of spot on image plane at different object distance, the design peculiarity and difficulties are analyzed, optical design examples are also given at last. The optical system adopted telecentric structure, the relative aperture is 1/3.5, field of view reaches seventy-six degrees, wavelength ranges from 500nm to 800nm, the center of mass of the spot on image plane varies non-obviously, high modulation transfer function, low distortion and high relative illumination are achieved, all of these can wholly satisfied the using demands of the surveillance and measuring camera.

This paper studies the basic principle of laser photothermal interferometry method of aerosol particles absorption coefficient. The photothermal interferometry method with higher accuracy and lower uncertainty can directly measure the absorption coefficient of atmospheric aerosols and not be affected by scattered light. With Jones matrix expression, the math expression of a special polarization interferometer is described. This paper using folded Jamin interferometer, which overcomes the influence of vibration on measuring system. Interference come from light polarization beam with two orthogonal and then combine to one beam, finally aerosol absorption induced refractive index changes can be gotten with four beam of phase orthogonal light. These kinds of styles really improve the stability of system and resolution of the system. Four-channel detections interact with interference fringes, to reduce the light intensity ‘zero drift’ effect on the system. In the laboratory, this device typical aerosol absorption index, it shows that the result completely agrees with actual value. After heated by laser, cool process of air also show the process of aerosol absorption. This kind of instrument will be used to monitor ambient aerosol absorption and suspended particulate matter chemical component. Keywords: Aerosol absorption coefficient; Photothermal interferometry; Suspended particulate matter.

A catastrophic earthquake with a Richter magnitude of 8.0 occurred at Wenchuan area of Sichuan province on May 12, 2008. The earthquake destroyed forests and natural vegetation. As a result, it is necessary to assess the vegetation recovery rate for decision making and policy planning in earthquake region. In this paper, we calculated the vegetation index in 2001, 2009, 2010, 2013 employing RS methods. According to the analysis of mean change trend of vegetation index, the vegetation index in 2009 was clear lower than that in 2001, the main reason is that the vegetation loss caused by the 2008 Wenchuan earthquake; the vegetation index mean in 2010 was lower than that in 2009, and image imaging at different times, vegetation index mean reduction is caused by seasonal changes; the vegetation index mean in 2013 is slightly higher than that in 2010, it showed that vegetation coverage began to be slowly recovering after the earthquake. According to the standard deviation of vegetation index, vegetation index has the smallest standard deviation in 2001, this showed it has a good homogeneous distribution before the earthquake; vegetation index has the largest standard deviation in 2009, indicates poor homogeneity after the earthquake; from 2009 to 2010 and to 2013, the standard deviation of vegetation index becomes smaller year by year, means that the homogeneity becomes better and vegetation cover also slowly get better. We anticipate that these results will be helpful in decision making and policy planning for recovery and reconstruction in the earthquake-affected area.

An efficient algorithm for typhoon center location is proposed using fractal feature and gradient of infrared satellite cloud image. The centers are generally located in this region for a typhoon except the latter disappearing typhoon. The characteristics of dense cloud region are smoother texture and higher gray values than those of marginal clouds. So the window analysis method is used to select an appropriate cloud region. The window whose difference value between the sum of the gray-gradient co-occurrence matrix and fractal dimension is the biggest is chosen as the dense cloud region. The temperature gradient of the region, which is near typhoon center except typhoon eye, is small. Thus the gradient information is strengthened and is calculated by canny operator. Then we use a window to traverse the dense cloud region. If there is a closed curve, the region of curve is considered as the typhoon center region. Otherwise, the region in which there is the most texture intersection and the biggest density is considered as the typhoon center region. Finally, the geometric center of the center region is determined as the typhoon center location. The effectiveness is test by Chinese FY-2C stationary satellite cloud image. And the result is compared with the typhoon center location in the “tropical cyclone yearbook” which was compiled by Shanghai typhoon institute of China meteorological administration. Experimental results show that the high location accuracy can be obtained.

A novel snapshot imaging spectrometer with large field-of-view (FOV) up to 100° is achieved by taking the advantages of a multiscale fore-optics and a compact Offner imaging spectrograph. Based on the diffraction imaging theory, the multiscale fore-optics composed of a monocentric spherical lens and multi-channel microlens array is designed, over which panchromatic images with small FOV are of uniform image quality. And identical imaging spectrographs with a dimension less than 30 cubic millimeters and with a high spectral resolution of about 2nm are designed correspondingly. The presented imaging spectrometer works at the visible wavelength range which is from 400nm to 780nm. It is of a fast speed about F/2.4 and a compact configuration of only 200mm×300mm×300mm in dimension. But the smile and keystone distortions are negligible.

Along with the further application of optical remote sensing, it becomes main trend to realize high spatial resolution, high time resolution, high spectrum resolution and high irradiance sensitivity simultaneously. We present a new satellite-based imaging system that will provide images with these high performances. The structure of the system is compact with small size and light weight. The IR imager, a new generation of high resolution optical remote sensing, is universally acknowledged as the most effective approach to surveil dynamic changes in the environment on the earth. Pushbroom imaging fashion with high efficiency and long-array focal plane detector with passive cooling are adopted to realize area imaging relevant to the flight direction of satellite. The instrument is a dual-optical-path system with long-wave infrared (LWIR) and mid-short-wave infrared (MW-SWIR) bands，which has 4 narrow spectrum bands respectively. An IR dichroic beam-splitter is use to divide wideband incident infrared into LWIR and MW-SWIR. Then two pieces of joint filters, which are integrated in front of detectors and then enveloped by IR Dewars, are used to divide the LWIR and MWIR into 4 spectral bands separately. The focal plane arrays (FPA) are fixed on the optical imaging plane of the lens. The LWIR and MW-SWIR FPA are cooled around 80K or even below. For cooled FPA, optical system must provide a real, accessible exit pupil coupled with a fast f/number refractive component in a Dewar and very close to the FPA. Compared to traditional infrared instruments, high spatial resolution and spectrum resolution can be obtained simultaneously within mass, volume and performance constraints.

There always are some breakpoints and bifurcation points in measured data of target radiation and scattering characteristics, which have a great impact on the data effectiveness. While among the existed pre-processing methods, the original bifurcation point becomes more prominent or makes a part of a signal. These pre-processing methods will have an effect on subsequent extraction and recognition for features. A data pre-processing method based on multi-threshold which effectively removes the numerical singularity and enhances the signal to noise ratio without changing the original signal is given in this paper.

The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

Earth observation is an important field of infrared remote sensing. Hyper-spectral remote sensing play an important role in weather forecast, environmental protection, agricultural production and geological survey. Now, Fourier-transform spectrometer (FTS) based on theory of Michelson interferometer has successfully been used to view the earth as a satellite-based instrument. The technology of FTS is an important research direction. This paper state the application of the FTS and give the analysis and research on interference signal sample and acquisition, in addition, it give a solution in which FPGA is used to complete the parallel capture of signal. In a conclusion, this design can accomplish the multi-channel and high-speed interferometer signal acquisition and transmission which is a base for further spectrum inversion and application.

Atmospheric trace gases exist in the atmosphere of the earth rarely. But the atmospheric trace gases play an important role in the global atmospheric environment and ecological balance by participating in the global atmospheric cycle. And many environmental problems are caused by the atmospheric trace gases such as photochemical smog, acid rain, greenhouse effect, ozone depletion, etc. So observations of atmospheric trace gases become very important. Multi Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) developed recently is a kind of promising passive remote sensing technology which can utilize scattered sunlight received from multiple viewing directions to derive vertical column density of lower tropospheric trace gases like ozone, sulfur dioxide and nitrogen dioxide. It has advantages of simple structure, stable running, passive remote sensing and real-time online monitoring automatically. A MAX-DOAS has been developed at Shandong Academy of Sciences Institute of Oceanographic Instrumentation (SDIOI) for remote measurements of lower tropospheric trace gases (NO₂, SO₂, and O₃). In this paper, we mainly introduce the stucture of the instrument, calibration and results. Detailed performance analysis and calibration of the instrument were made at Qingdao. We present the results of NO₂, SO₂ and O₃ vertical column density measured in the coastal boundary layer over Jiaozhou Bay. The diurnal variation and the daily average value comparison of vertical column density during a long-trem observation are presented. The vertical column density of NO₂ and SO₂ measured during Qingdao oil pipeline explosion on November 22, 2013 by MAX-DOAS is also presented. The vertical column density of NO₂ reached to a high value after the explosion. Finally, the following job and the outlook for future possible improvements are given. Experimental calibration and results show that the developed MAX-DOAS system is reliable and credible.

Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.

Mapping precision of space-borne stereo mapping camera is primarily determined by attitude angle errors of the satellite. Time synchronization errors of space-borne stereo mapping camera will bring on extra attitude angle errors. In this paper model of space-borne stereo mapping camera was established in satellite tool kit (STK) to obtain the regularity of attitude angles changing with time. Influence of space-borne stereo mapping camera’s time synchronization precision on attitude angle errors was analyzed by combing the regularity of attitude angles changing with time and the sampling theory. As a result digitalized model of extra attitude angle errors and time synchronization errors of space-borne stereo mapping camera was put forward. In validation experiments real attitude angle data of a stereo mapping satellite were collected and extra attitude angle errors caused by specific time synchronization errors of space-borne stereo mapping camera were obtained. Results of the experiments and analysis indicated that extra attitude angle errors caused by specific time synchronization error could be reduced from 0.01939 arc second to 0.00003879 arc second as time synchronization precision was optimized from 1ms to 20μs.

It is known that Strapdown Inertial Navigation System (SINS), Global Navigation Satellite System (GNSS) and Celestial Navigation System (CNS) can complement each other’s advantages. The SINS/CNS integrated system, which has the characteristics of strong autonomy, high accuracy and good anti-jamming, is widely used in military and civilian applications. Similar to SINS/GNSS integrated system, the SINS/CNS integrated system can also be divided into three kinds according to the difference of integrating depth, i.e., loosely coupled pattern, tightly coupled pattern and deeply coupled pattern. In this paper, the principle and characteristics of each pattern of SINS/CNS system are analyzed. Based on the comparison of these patterns, a novel deeply coupled SINS/CNS integrated navigation scheme is proposed. The innovation of this scheme is that a new star pattern matching method aided by SINS information is put forward. Thus the complementary features of these two subsystems are reflected.

Considering that Double-density dual-tree(DD-DT)complex wavelet has translation invariance, anti-aliasing properties and more compact space intervals, based on the quantum-inspired parameter estimation, this paper proposed a new quantum-inspired noise reduction method based on DD-DT complex wavelet transform for remote sensing images, especially the SAR images. The general process is addressed as below: conduct a logarithmic transformation for the SAR images, convert the multiplicative speckle noises to additive noises; then decompose the DD-DT complex wavelets for each image, thus to get the wavelet coefficient for each layer in all detailed directions; consider the inter-scale correlation of wavelet coefficient, utilize the Bayesian estimation theory along with the quantum mechanics principle of superposition, calculate the estimated wavelet coefficient; and then process the data layer by layer, refactor the SAR images using the processed coefficients. Then conduct a anti-logarithmic transformation to get the noise reduction result. Compare with the results of traditional methods, the resulting images have a significant improvement in different evaluation functions such as the Peak Signal Noise Ratio, Edge Preserve Index etc. The results have also shown better noise reduction quality in the images.

Production management of winter wheat is more complicated than other crops since its growth period is covered all four seasons and growth environment is very complex with frozen injury, drought, insect or disease injury and others. In traditional irrigation and fertilizer management, agricultural technicians or farmers mainly make decision based on phenology, planting experience to carry out artificial fertilizer and irrigation management. For example, wheat needs more nitrogen fertilizer in jointing and booting stage by experience, then when the wheat grow to the two growth periods, the farmer will fertilize to the wheat whether it needs or not. We developed a spatial decision support system for optimizing irrigation and fertilizer measures based on WebGIS, which monitoring winter wheat growth and soil moisture content by combining a crop model, remote sensing data and wireless sensors data, then reasoning professional management schedule from expert knowledge warehouse. This system is developed by ArcIMS, IDL in server-side and JQuery, Google Maps API, ASP.NET in client-side. All computing tasks are run on server-side, such as computing 11 normal vegetable indexes (NDVI/ NDWI/ NDWI2/ NRI/ NSI/ WI/ G_SWIR/ G_SWIR2/ SPSI/ TVDI/ VSWI) and custom VI of remote sensing image by IDL; while real-time building map configuration file and generating thematic map by ArcIMS.

Most recently, an emerging Compressed Sensing (CS) theory has brought a major breakthrough for data acquisition and recovery. It asserts that a signal, which is highly compressible in a known basis, can be reconstructed with high probability through sampling frequency which is well below Nyquist Sampling Frequency. When applying CS to Remote Sensing (RS) Video imaging, it can directly and efficiently acquire compressed image data by randomly projecting original data to obtain linear and non-adaptive measurements. In this paper, with the help of distributed video coding scheme which is a low-complexity technique for resource limited sensors, the frames of a RS video sequence are divided into Key frames (K frames) and Non-Key frames (CS frames). In other words, the input video sequence consists of many groups of pictures (GOPs) and each GOP consists of one K frame followed by several CS frames. Both of them are measured based on block, but at different sampling rates. In this way, the major encoding computation burden will be shifted to the decoder. At the decoder, the Side Information (SI) is generated for the CS frames using traditional Motion-Compensated Interpolation (MCI) technique according to the reconstructed key frames. The over-complete dictionary is trained by dictionary learning methods based on SI. These learning methods include ICA-like, PCA, K-SVD, MOD, etc. Using these dictionaries, the CS frames could be reconstructed according to sparse-land model. In the numerical experiments, the reconstruction performance of ICA algorithm, which is often evaluated by Peak Signal-to-Noise Ratio (PSNR), has been made compared with other online sparse representation algorithms. The simulation results show its advantages in reducing reconstruction time and robustness in reconstruction performance when applying ICA algorithm to remote sensing video reconstruction.

Leaf Area Index (LAI) is an essential parameter for many process-based ecological and climate models. A large number of LAI products at local, regional, continental, or global scales have been derived from different remotely sensed data. However, due to the lack of the foliage clumping index, most LAI products can only provide the effective LAI (LAIe), which cannot fully satisfy the requirements of ecological and land surface models. In this study, based on the new 500 m resolution foliage clumping index, a new true LAI at 500 m resolution in 8-day intervals from 2003 to 2008 over China is retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The temporal and spatial characteristics of the new LAI over China are analyzed. The results show that the true LAI and LAI_e have similar spatial distribution patterns over China mainly depending on vegetation types. Forests have the maximum LAI larger than 6 averaged over the country in July, followed by shrubs with a mean LAI of 2.45 in July, and croplands and grasslands with the values of 1.5 and 1.0, respectively. Furthermore, the new LAI has been validated using the field measurements in two forest and two grassland areas in China through an upscaling process using Landsat5-TM images. Compared with MOD15A2 LAI, the new LAI shows much stronger correlation with the reference TM LAI in these validation areas.

Compressed sensing (CS) breaks Shannon/Nyquist sampling theorem bottleneck. It captures and represents signals at a sampling rate significantly below the Nyquist rate, and then original signals can be accurately or high precisely recovered by solving sparse optimization problems based on signal sparsity or compressibility. CS has a good application prospect in remote sensing imagery, especially in Infrared Remote Sensing Video. The CS-based remote sensing includes two stages: onboard encoding imaging and offline decoding recovery. Video offline decoding recovery is one of the core questions in CS-Based Infrared Remote Sensing Video systems. In this paper, firstly, we introduce a coupled optimization models which is composed of a single model and an error model for video offline decoding recovery. This paper shows that the coupled models can easily improve speed and accuracy to recover video of Infrared Remote Sensing. Secondly, we review the Bregman method and linearized Bregman method. Furthermore, a linearized Bregman error iteration algorithm is proposed for solving the coupled models, thus lead to better convergence rates and error performances. In numerical experiments, we compare the convergence rates of the original Bregman method and the linearized Bregman method from the first frame picture, and test the performance of the linearized Bregman method for video recovery with the single model and coupled models. Numerical experiments demonstrate the effectiveness of the proposed algorithm. The comparison with the single model is included.

As the second Chinese civilian high spatial resolution satellite, the ZY-02C satellite was successfully launched on December 22, 2011. In this paper, we used two different methods, subjective evaluation and external evaluation, to evaluate radiation quality of ZY-02C panchromatic image, meanwhile, we compared with quality of CBERS-02B, SPOT-5 satellite. The external evaluation could give us quantitative image quality. The EIFOV of ZY-02C, one of parameters, is less than SPOT-5. The results demonstrate the spatial resolution of ZY-02C is greater than SPOT-5. The subjective results show that the quality of SPOT-5 is little preferable to ZY-02C，CBERS-02B, and the quality of ZY-02C is better than CBERS-02B for most land-cover types. The results in the subjective evaluation and the external evaluation show the excellent agreement. Therefore the comprehensive result of the image quality will be got based on combining parameters introduced in this paper.

Return signal of oceanographic Lidar is a decaying exponential function of the attenuation coefficient which is related to the optical properties of water. The Lidar attenuation coefficient ( K_lidar ) obtained from traditional oceanographic Lidar with single field of view (FOV) cannot be used to effectively estimate parameters of the water optical properties due to the deficiency of Lidar equation. However, this exponential decay of elastic backscattering from water is strongly dependent on both FOV of Lidar and optical properties of water. Thus, an approach using a variable FOV receiver has become a potential way to compensate the deficiency in the measurement by traditional Lidar. Three major parts are presented in the paper. Firstly, on the basis of historical models of oceanographic Lidar, a practical model between K_lidar and FOV angles is derived to estimate the optical property parameters, namely a (absorption coefficient), b (scattering coefficient) and K_d (diffuse attenuation coefficient). Secondly, for the purpose of getting the appropriate FOVs of a shipboard oceanographic Lidar, return signals are simulated under different FOVs to analyze the relationship between K_lidar and the water optical parameters with the impact of background noise taken into account. Finally, the experiments are conducted to measure optical properties of water by using oceanographic Lidar with different FOVs. The optical properties of water bodies are estimated in the cases of different FOVs, and the accuracy of measurements is analyzed. Experimental analysis verifies the feasibility of measuring multiple optical properties of seawater by oceanographic Lidar with variable FOV.

In this paper, we try to find a model that can apply to predict the polarization characteristics of the targets on the ground correctly. In the first place, we give an introduction to several kinds of existing models which are divided into three categories: Empirical models are precise but occupy too much source of computer; Physical-based models can predict the phenomenon of reflection exactly but hardly get the final results; Semi-empirical models have both advantages mentioned above and avoid their disadvantages effectively. Then we make an analysis of the Priest-Germer（PG）pBRDF model, one of semi-empirical models, which is suitable for our study. The methods of parameters inversing and testing are proposed based on this model and the test system from which we can get enough data to verify the accuracy of the model is designed independently. At last, we make a simulation of the whole process of the parameters inversing based on PG pBRDF model. From the analysis of the simulation curves, we briefly know the direction we go in the following work to make an amendment.

Pipeline leakage is a complex scenario for sensing system due to the traditional high cost, low efficient and labor intensive detection scheme. TDLAS has been widely accepted as industrial trace gas detection method and, thanks to its high accuracy and reasonable size, it has the potential to meet pipeline gas leakage detection requirements if it combines with the aerial platform. Based on literature study, this paper discussed the possibility of applying aerial TDLAS principle in pipeline gas leak detection and the key technical foundation of implementing it. Such system is able to result in a high efficiency and accuracy measurement which will provide sufficient data in time for the pipeline leakage detection.

The image quality of a high resolution space camera may be degraded by wavefront aberrations and optical axis jitters. It is desirable to use an in-orbit instrument to measure these errors and then correct them with on-line adaptive optical technologies or off-line image restoration algorithms. An integrated method of measuring wavefront aberrations and optical axis jitters of the space camera based on the ground scene Shack-Hartmann wavefront sensor is studied. When working in jitter-sensing mode, only parts of the sub-images are read to enhance the frame rate. Factors affect the precision are analyzed. Experiments are made which show that this method has a good performance by choosing proper parameters.

Taking Meitanba mining area in Hunan Province as an example, by using the achieved high accuracy and high resolution point-cloud data and digital image data by airborne LiDAR system, this research built the 3D landform of the vegetation-covered areas, got the features of micro landform in the areas, and offered quantity factors for research of geo phenomenon which related to regional landforms and geoscience process. Based on the high accuracy data from airborne LiDAR system and combined with the basic data of geology,the forming mechanism of the karst collapse of Meitanba mining area in Hunan Province and the relationship of surface collapse and mining activities are analyzed. The research mentioned that the reason of the karst collapse in Meitanba mining area is with the basic conditions of forming karst landform and plus the increasing water flow and exchange rate of the underground water, and then the water level decrease, finally different degrees of the regional karst collapse have happened.

Signal de-noising remains an important problem in lidar signal processing. This paper presents a de-noising method based on singular value decomposition. Experimental results on lidar simulated signal and real signal show that the proposed algorithm not only improves the signal-to-noise ratio effectively, but also preserves more detail information.

As hyperspectral remote sensing image have the features of high spectral resolution, high dimension, it brings a serious problem of choosing the appropriate band combination from numerous bands. To solve the problem，the present paper, basing on Optimum Index Factor, proposes a modified band selection algorithm. It aims to reduce the dimension through the improved block adaptive band selection. According to the strong correlation among the bands of hyperspectral remote sensing image，the paper introduces hyperspectral band selection method based on the correlation between bands. The modified algorithm can overcome some shortages of Optimum Index Factor, such as inefficient of selecting bands. However, it can also remain some characteristics from Optimum Index Factor. For instance, the selected band combination, through the modified algorithm, can retain rich amount of information and weak correlation between the selected bands. And the compute complication is decreased rapidly. Taking Hyperion hyperspectral remote sensing image from EarthObserving-1 as example, the present paper contrast the practical effect of the modified algorithm of sub regional selection band and Optimum Index Factor.

TM data of 1998, 2002 and OLI data of 2013 were chosen in Lu County. Fractional Vegetation Cover of study area was obtained based on the basic processing of data measurement ascertaining atmospheric correction, the retrieval of surface albedo and the calculation of Normalized Difference Vegetation Index (NDVI) in this research. Spatial differences and influencing factors of Fractional Vegetation Cover in Lu County over past twenty five years were obtained through statistical and analysis. Studies have shown that vegetation cover changed for the better in the 35.62 percent areas of Lu County from 1988 to 2002 and 15.54 percent areas changed for the worse. The main factor that vegetation cover changed for the better is the change of imaging time. Significant increase could be found in vegetation cover because rice was not harvested on August 5 in 2002, but the opposite of September 5 in 1988. Meanwhile, scattered residential building construction in the southeast, agricultural land and mall-scale urban construction in the southwest could be main factors that had made vegetation cover changed for the worse. From 2002 to 2013, vegetation cover changed for the better in the 12.29 percent areas where located in the southeast of Lu County mainly because regional vegetation change. Meanwhile, vegetation cover changed for the worse in the 39.28 percent areas mainly because a large number of urban construction and mining development area in the middle and west and a large number of new scattered residential and agricultural land in the west and east.

Snow disaster is a natural phenomenon owning to widespread snowfall for a long time and usually affect people's life, property and economic. During the whole disaster management circle, snow disaster in pastoral area of northern china which including Xinjiang, Inner Mongolia, Qinghai, Tibet has been paid more attention. Thus do a good job in snow cover monitoring then found snow disaster in time can help the people in disaster area to take effective rescue measures, which always been the central and local government great important work. Remote sensing has been used widely in snow cover monitoring for its wide range, high efficiency, less conditions, more methods and large information. NOAA/AVHRR data has been used for wide range, plenty bands information and timely acquired and act as an import data of Snow Cover Monitoring Model (SCMM). SCMM including functions list below: First after NOAA/AVHRR data has been acquired, geometric calibration, radiometric calibration and other pre-processing work has been operated. Second after band operation, four threshold conditions are used to extract snow spectrum information among water, cloud and other features in NOAA/AVHRR image. Third snow cover information has been analyzed one by one and the maximum snow cover from about twenty images in a week has been selected. Then selected image has been mosaic which covered the pastoral area of China. At last both time and space analysis has been carried out through this operational model ,such as analysis on the difference between this week and the same period of last year , this week and last week in three level regional. SCMM have been run successfully for three years, and the results have been take into account as one of the three factors which led to risk warning of snow disaster and analysis results from it always play an important role in disaster reduction and relief.

The modeling and the validation methods of the spectral BRDF on the material surface of space target were presented. First, the microscopic characteristics of the space targets’ material surface were analyzed based on fiber-optic spectrometer using to measure the direction reflectivity of the typical materials surface. To determine the material surface of space target is isotropic, atomic force microscopy was used to measure the material surface structure of space target and obtain Gaussian distribution model of microscopic surface element height. Then, the spectral BRDF model based on that the characteristics of the material surface were isotropic and the surface micro-facet with the Gaussian distribution which we obtained was constructed. The model characterizes smooth and rough surface well for describing the material surface of the space target appropriately. Finally, a spectral BRDF measurement platform in a laboratory was set up, which contains tungsten halogen lamp lighting system, fiber optic spectrometer detection system and measuring mechanical systems with controlling the entire experimental measurement and collecting measurement data by computers automatically. Yellow thermal control material and solar cell were measured with the spectral BRDF, which showed the relationship between the reflection angle and BRDF values at three wavelengths in 380nm, 550nm, 780nm, and the difference between theoretical model values and the measured data was evaluated by relative RMS error. Data analysis shows that the relative RMS error is less than 6%, which verified the correctness of the spectral BRDF model.

This paper presents a precise laboratory goniometer system to quickly collect bidirectional reflectance distribution factor(BRDF)of typical materials such soil, canopy and artificial materials in the laboratory. The system consists of the goniometer, SVC HR1024 spectroradiometer, and xenon long-arc lamp as light source. the innovation of cantilever slab can reduce the shadow of the goniometer in the principle plane. The geometric precision of the footprint centre is better than ±4cm in most azimuth directions, and the angle-controlling accuracy is better than 0.5°. The light source keeps good stability, with 0.8% irradiance decrease in 3 hours. But the large areal heterogeneity of the light source increase the data processing difficulty to capture the accurate BRDF. First measurements are taken from soil in a resolution of 15° and 30° in zenith and azimuth direction respectively, with the ±50° biggest view angle. More observations are taken in the hot-spot direction. The system takes about 40 minutes to complete all measurements. A spectralon panel is measured at the beginning and end of the whole period. A simple interactive interface on the computer can automatically control all operations of the goniometer and data-processing. The laboratory experiment of soil layer and grass lawn shows that the goniometer can capture the the multi-angle variation of BRDF.

A Dual-wavelength Mie Polarization Raman Lidar has been developed for cloud and aerosol optical properties measurement. This idar system has built in Hefei and passed the performance assessment in 2012, and then moved to Jinhua city to carry out the long-term continuous measurements of vertical distribution of regional cloud and aerosol. A double wavelengths (532 and 1064 nm) Nd-YAG laser is employed as emitting source and four channels are used for detecting back-scattering signals from atmosphere aerosol and cloud including 1064 nm Mie, 607 nm N2 Raman, two 532 nm Orthogonal Polarization channels. The temporal and spatial resolutions for this system, which is operating with a continuing mode (24/7) automatically, are 30s and 7.5m, respectively. The measured data are used for investigating the aerosol and cloud vertical structure and cloud phase from combining of cloud signal intensity, polarization ratio and color ratio.

Sun sensor is a key device in satellite’s attitude determination system. It acquires satellite’s attitude information by measuring sun light direction. Compared with area array CMOS sun sensor, the linear CMOS sun sensor has the advantages of low power consumption, light weight and relatively simple algorithm. Considering the pixel number, power consumption and efficiency of output, most sun sensors equipped with a single photosensitive unit usually have (±60)x(±60) field of view(FOV). Satellites usually use multiple sun sensors for semi-sphere field of view in total to meet the need of attitude measurement in all directions. Considering the need of large-scale FOV measurement and high integration level, this paper proposes a semi-sphere FOV sun sensor, of which coverage area can be (±90)x(±90) . A prototype has been made and the calibration of key component has been conducted. By integrating four photosensitive units, the semi-sphere FOV sun sensor is achieved, as a result, the demand of high integration can be realized for a micro-satellite device. The photosensitive unit consists of an N-shape slit mask and a linear CMOS image sensor. An N-shape slit model is established to acquire biaxial sun angles from analyzing the shift of 3 peak values from the image of the linear sensor. Embedded system has been designed and developed, in which the MCU control four photosensitive units. Calibration of one photosensitive unit, which is the key step in the process of the whole calibration of semi-sphere FOV sun sensor, has been conducted. As a result of the symmetry of N-shape slit, initial position of the linear image sensor can be fixed. Due to the installation error and machining deviation, centroid algorithm and data gridding technique is adopted to improve the accuracy. Experiments show that the single photosensitive unit can reach an angle accuracy of 0.1625°. Consequently, from the point of significant component in the sun sensor, initial calibration ensures the angle accuracy of semi-sphere FOV sun sensor.

A novel method to SAR image segmentation based on fuzzy support vector machine (FSVM) for object recognition is proposed. First, the feature of river domain is extracted by analyzing bridge and its background in SAR image. Then, FSVM is used to make classification model by training example data for segmenting river region. Last, the summation minimum of direction energy is used as the rule for identifying a bridge in the binary image of river class. Experimental results show that the proposed method can effectively recognize more than one bridge over water in complex scene.

As the remote sensing technology transformation from military use to civil use becomes deeper and faster, the resolution is better and better, and the relative techniques of the civil optical remote sensing satellite are richer and richer. So, modes such as civil use replacing military use, civil use covering military use, and civil use supporting military use are the real portraiture of high-resolution optical satellite remote sensing development currently. Taking the situations of the Taiwan authorities buying commercial remote sensing image to military reconnaissance, and the so-called military establishments exposed by media using satellite image as an example, the military reconnaissance application of civil high-resolution optical satellite remote sensing is discussed. Then, the actuality and reasons of huge measure engineering and ruled configuring, environment and signs of military area, equipment and exercitation establishments and three-dimension information of engineering and equipment which can be detected easily by remote sensing are analyzed.

Laser space communication has obvious advantages in interstellar transmission，but the space environment will have a direct impact on laser communication system. The function of the analysis of space environment identity effectively could reduce and avoid the bug and invalidation produced by the overload to prolong the using span of effective load and increase the credibility of effective load, meanwhile it is also the main principle to design and research .This article summarizes the characteristics of vacuum space environment(Effect of vacuum outlet, Molecular contamination effect, Vacuum Mount, Cold welding effect, Heat radiation effect under vacuum), low temperature environment, background radiation (including space background radiation caused by thermal radiation, space background radiation caused by light noise). Space background radiation for the performance of space laser communication load is two aspects: one is the background of space radiation caused by thermal radiation, it mainly affects the satellite platform and payload of the thermal control design; Background spectrum caused by radiation and space, it will affect the space laser communication of the signal-to-noise ratio of the receiving unit, which affect the acquisition probability, tracking accuracy and error rate of communication, and particle radiation environment (Including total dose effects, single event effect), the plasma environment in five areas from the characteristics of space environment, for the problem of Space channel Influence the laser communication system performance. On this basis ,this article analysis the influence of space environment on the laser communication system with some examples, which will lay the foundation for the application of space laser communication system of our country.

The status quo of performance evaluation method for optical imaging system in our country is introduced in the article. At the same time, the definitions and applied fields for discrimination probability，National Imagery Interpretability Rating Scale（NIIRS）and General Image Quality Equation (GIQE) are introduced, too. Under ideal conditions, utilizing ground resolution distance the dependence model between NIIRS and discrimination probability is established. Utilizing this model, we can solve the difficulties of optical imaging system performance evaluation using these two different evaluation methods.

Based on Aerosol Optical Thickness (AOT) in the 550nm NPP-EDR data, GOCIAOT in the 555nm for detecting and tracing sudden haze event on 2013 December in the Yangtze River Delta, while CDAS-NCEP/NCAR Reanalysis wind data is utilized to analyze the migrating routine The results show that: 1)GOCIAOT (555nm)<1 and NPPAOT (550nm)<1 is an effective indictor of distinguishing the haze event.2) The two-stream approximation algorithm can be used to retrieve GOCIAOT especially in China with high concentration of aerosol.3)Combined with high-temporal resolution of GOCIAOT is utilized for analyzing the forming mechanism of a sudden outbreak of haze event in Yangtze River Delta .The migration driven mechanism is diagnosed with CDAS-NCEP/NCAR Reanalysis wind data.4)the study suggests that the haze was formed in Hebei and Henan province on December 3, 2013.Under the strong northwest wind with the average rate of 4m/s, the haze rapidly moved to the Yangtze River Delta on December 4^th2013, resulting in the most serious haze event in 2013 in there. Under the northwest wind control, the haze area expanded rapidly from 70,000km² to 200,000km² during its migration. The research suggests that it could be a feasible routine monitoring pattern in detecting the occurrence, migration of haze events in Yangtze River Delta.

To monitor the temporal and spatial characteristics of particulate matter and water vapor in the aerosol pollution and haze episodes, the polarization Raman Mie lidar system has been developed. The lidar system includes four detection channels and it can measure the extinction coefficient and depolarization ratio of particulate matter as well as water vapor mixing ratio. The extinction coefficient indicates the visibility of atmosphere and it associates with the concentration of particulate matter. The depolarization ratio demonstrates the nonsphericity of particulate matter and is useful to distinguish the dust and pollution aerosol. The water vapor mixing ratio denotes the content of water vapor in the air and it is an important factor to influence of the hygroscopic growth on the pollution aerosol. The lidar system can operate in the automatic and continuous modes through a window on the roof of the observation room regards of the weather, and it takes continuous measurement from 20 November 2013 to 6 February 2014 over Hefei, China. During the experiment, the typical results of particulate matter measured with lidar in clear air, aerosol pollution and haze, and dust episodes are analyzed and given. The lidar observations are also compared with the air quality data and the meteorological data on the ground.

The Stokes imaging polarimeter using a retarder and a polarizer is a direct and conventional method to detect the full Stokes vector of the scene. This method has been widely used for different imaging architectures, such as division of time and division of aperture. System calibration is necessary in polarimetric imagery. The polarization optical elements angular deviation belongs to adjustment error and should be calibration when the device is set up. In this paper we propose a novel method to calibration the angular deviation using Fourier series analysis. A linear polarization state generator including a light source and a linear polarizer is installed before the imaging polarimeter. The polarizer rotates 360-degree uniform and the signal intensity of the input light is recorded by the imaging polarimeter. The angle of the fast axis of the quarter-waveplate respect to the pass axis of the polarizer can be calculated from the obtained data by use of Fourier series analysis. The mathematic model of the presented method is established and proved by mathematical simulation.