电离层残差法探测与修复周跳特性分析

载波相位观测值中的周跳进行探测和修复一直是GPS精密定位数据处理中的一个十分重要的问题。主要讨论基于双频探测的电离层残差法,编制了相应程序,并通过实例分析了在不同采样率条件下探测与修复周跳效果,针对其探测盲区提出了解决方案。     

Discharge and suspended sediment flux estimated along the mainstream of the Amazon and the Madeira Rivers (from in situ and MODIS Satellite Data)

Water and suspended sediment fluxes are considered during the period 2000–2008 in a region including the full Amazon River from the confluence of the Negro River to Santarém, the end part of the Solimões River, and the lower part of the Madeira River. Three types of data are used: water discharge estimated from field measurements, and suspended sediment obtained from field measurements and derived from MODIS satellite data. A generalized least square method including a propagating term is developed in order to propagate the signal upward and downward the river. The approach is introduced and tested. Several experiments are considered in order, first, to estimate the ability to propagate the signal from stations located before the confluences of Negro and Madeira Rivers to stations located on the Amazon River; second to investigate the possibility to propagate the signal along the Amazon River which dynamics is coupled with floodplains dynamics; and third to produce optimal solutions of water and sediment fluxes. For each experiment, the influence of field and satellite data is compared. The approach is efficient in the upper part of the region of study where the Solimões, the Negro and the Madeira Rivers meet and fails in the lower part of the region where interactions between Amazon River and floodplains play an important role on the fluxes’ dynamics. The optimal experiment includes in situ and satellite data from all the stations available and is used to analyse the recent evolution of suspended sediment flux along the Amazon River and its interaction with the large coupled floodplains. A high accumulation rate is observed during the 2000–2002 period, followed by decreasing rates until 2005 and by increasing values in 2006 and 2007. Our results suggest that floodplains extending along a river reach of 390 km-long between Itacoatiara and Óbidos trap about 15% of the suspended sediment flux passing at Óbidos. The simulated deposition rate is of about 0.3 Mt km⁻¹ yr⁻¹ corresponding to an accretion rate of about 27 mm yr⁻¹.     

Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the Detection of the Invasive Shrub Lonicera maackii in Southwestern Ohio Forests

We tested how accurately image data from the Advanced Land Imager (ALI) sensor vs. the Landsat Thematic Mapper (TM) predict the land cover of Lonicera maackii in the forest understory, taking advantage of this invasive shrub's extended leaf retention in the fall when the canopy is leafless. Percent cover of L. maackii in 20 woodlots in southwestern Ohio was regressed on values for spectral vegetation indices (SVIs) derived for each image. The land cover of L. maackii was best explained by the Simple Ratio (SR) using TM data (R ² = 0.537). The regression results for SVIs from TM vs. ALI suggest that the ALI image was acquired too late in the fall to accurately detect this invasive shrub.     

Detection of Changes in Glacier Mass Balance Using Satellite and Meteorological Data in Tirungkhad Basin Located in Western Himalaya

Himalayan glaciers and their mass balance are poorly sampled through direct mass balance measurements. Thus, based on Landsat datasets of ETM⁺ (2000), ETM⁺ (2006) and TM (2011), mass balance studies of 32 glaciers was carried out using accumulation area ratio (AAR) method in the Tirungkhad river basin, a tributary of Satluj River, located in western Himalayan region. The overall specific mass balance was negative varying from ?27 cm (2000) to ?41 cm (2011). Out of 32 glaciers, 27 glaciers (81.2 %) showed negative mean mass balance and 5 glaciers (18.7 %) showed positive mean mass balance. Mean of specific mass balance for the year 2000, 2006 and 2011 was found to be ?48 cm, ?55 cm and ?0.61 cm respectively, in case of glaciers with negative mass balance while in case of glaciers with positive mass balance, it was 0.67 cm (2000), 0.56 cm (2006) and 0.47 cm (2011). The investigations suggested a loss of ?0.034 km³ of glacial ice for 2000, 0.036 km³ for 2006 and 0.038 km³ for 2011 respectively. The negative mass balance of the glaciers since 2000 correlates well with the increasing trend of annual mean temperature and decreasing trend of precipitation (snow water equivalent (SWE) and rainfall). Based on Mann Kendall test the temperature and SWE trends were significant at 95 % confidence level, however, the rainfall trend was insignificant.     

Estimation of the Aerial Cover of Seagrasses of Lakshadweep Islands (India) Using Indian Remote Sensing Satellite (IRS P6 LISS IV)

Seagrasses ecosystems are fragile yet highly productive ecosystems of the world showing declining trend throughout the world due to natural and anthropogenic pressures. Effective conservation and management plan is thus required to protect these resources, to aid with conservation need mapping and monitoring of seagrasses using high resolution remote sensing data is very much required. Hence, the present study was made to record the seagrass aerial cover in the Lakshadweep islands using IRS P6 LISS IV satellite data. The suitability of LISS IV sensor for seagrass mapping was tested for the first time with an overall accuracy of 73.16%. The study found an area of 2590.2?ha of seagrasses in Lakshadweep islands with 1310.8?ha and 1279.4?ha dense and sparse seagrass cover respectively. The study recommends the use of LISS IV data for mapping the shallow water seagrasses, as mapping efficiency increases nearly 4 times more than the LISS III data, as the former (LISS IV) picks up the small patches of seagrasses and delineates the coral and reef vegetation patches from seagrass class.     

Dynamics of vegetation indices in tropical and subtropical savannas defined by ecoregions and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover

In this study, we explored the capacity of vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance products to characterize global savannas in Australia, Africa and South America. The savannas were spatially defined and subdivided using the World Wildlife Fund (WWF) global ecoregions and MODIS land cover classes. Average annual profiles of Normalized Difference Vegetation Index, shortwave infrared ratio (SWIR32), White Sky Albedo (WSA) and the Structural Scattering Index (SSI) were created. Metrics derived from average annual profiles of vegetation indices were used to classify savanna ecoregions. The response spaces between vegetation indices were used to examine the potential to derive structural and fractional cover measures. The ecoregions showed distinct temporal profiles and formed groups with similar structural properties, including higher levels of woody vegetation, similar forest–savanna mixtures and similar grassland predominance. The potential benefits from the use of combinations of indices to characterize savannas are discussed.     

PCI Geomatica 2013（GXL）软件在地理国情监测卫星影像生产中的应用

根据第一次全国地理国情普查项目的实际需求,本文首先阐述了利用RPC参数进行卫星影像区域网平差的原理,然后结合GXL软件的特点,介绍了GXL软件的影像纠正方案,最后分析了地理国情监测卫星影像正射校正工作的解决思路。通过实践证明,在进行大量的卫星影像纠正任务时,使用GXL软件的区域网平差模块能够获得高效精确的正射影像,而且可以减少大量的野外控制点测量时间。     

Integrated Use of Optical and Radar Satellite Data for Active Faults and Corresponding Displaced Landforms in Kozani Basin (Greece)

Abstract

The usefulness of integration of SAR (ERS-1) and Landsat TM data for study active faults and the corresponding displaced landforms in flat or almost flat areas has been demonstrated. The study area is the Kozani basin which in May 13, 1995 was affected by a strong earthquake (Ms=6.6). After co-registration and resampling the two data sets were merged to form a combined image. The combined image offers the spectral characteristics of the TM data with the spatial resolution and roughness sensitivity of SAR images. The merging method used was the IMS to RGB transform. The criteria and parameters examined were geomorphic features, drainage network analysis, slope processes, terrain analysis, and observations on spatial distribution of soil cover as well as linear features that correspond to fracture zones crossing the basin. The use of the combined image allowed us to identify tectonic terraces in the basin produced by activity of normal faults located in the adjacent relief zone.     

Classification of Satellite Images in Assessing Urban Land Use Change Using Scale Optimization in Object-Oriented Processes (A Case Study: Ardabil City,Iran)

By using satellite imagery, the recognition and evaluation of various phenomena and extraction of information necessary for the planning of land resources or other purposes are easily accomplished. The purpose of this study is to compare the efficiency of seven commonly used methods of monitored classification of satellite data to evaluate land use changes using TM and OLI Landsat, IRS, Spot5 and Quick Bird bands as well as different color combinations of these images to detect agricultural land, residential areas and aquatic areas using object-oriented processing. Digital processing of satellite images was carried out in 1998 and 2016 using advanced methods. Training samples were extracted in five user classes by eCognition software using segmentation scale optimization, different color combinations and coefficients of shape and compression. The appropriate segmentation scale for arable land, human complications and the blue areas were, respectively, 50, 8 and 10. Then each image was classified separately using seven methods and extracted samples, and efficiency of each classification method was obtained by calculating two general health and Kappa coefficients. The results show that the accuracy of each classification method and the neural network with a total accuracy of 94.475 and Kappa coefficient of 92.095 were selected as the most accurate classification method. These results show that the sampling of educational samples with proper precision of the classes in the images and dependency probability of each satellite images pixel can be useful in classifying group available in helpful area.     

GRACE时变重力场位系数相关误差的滤波消除技术

利用UTCSR发布的2003-01~2013-07GRACE RL05月平均重力场模型,分析比较了高斯滤波、各向异性滤波、扇形滤波和维纳滤波,并结合去相关滤波在反演南极地区冰盖质量变化方面的差异。通过计算得到以下结论：①基于121组重力场模型阶方差分布得到维纳滤波与半径为300 km的高斯滤波效果最为接近,说明300 km滤波半径完全可以满足质量变化信号的提取;②在一定范围内,提高滤波半径能提高反演结果信噪比,建议南极区域的滤波半径为500 km;采用相同滤波半径,不同空间滤波算法计算的质量变化率基本一致,在南极区域可以选取任一滤波方法;③与其他算法相比,去相关滤波算法能在一定程度消除球谐系数中存在的系统误差,改善反演结果。     

Synergistic Application of Optical and Radar Data for Archaeological Exploration in the Talakadu Region,Karnataka

Talakadu is a well known historic place situated on bank of the river Cauvery in Mysore district of Karnataka. The place is close to concave side of a prominent meander where large amount of sand has accumulated. It is believed that after construction of a reservoir upstream, sand was exposed to wind action burying the structures of Ganga dynasty and other later kingdoms. A number of buried sites have been identified by archaeological excavations conducted so far. Presently the area forms sand dunes with thick plantation cover. Analysis of RADAR data (fine beam RADARSAT and ENVISAT ASAR) led to identifying a hitherto unknown buried channel through the Old Talakadu town adjoining the excavated archaeological sites. The study suggests that RADAR penetration through the plantation canopy seems to have occurred as observed by comparing with corresponding optical data of LISS-IV. Below the canopy, sand and shrubs on top of the channel (topographically low area) are acting as smooth surface providing dark tone on radar imagery. During field validation GPS was extensively used to navigate through the forest canopy and locate the buried channel, excavated archaeological sites as well as other anomalous patterns. Synergistic application of optical (RESOURCESAT-1 LISS-IV and CARTOSAT-1 & 2) and radar (fine beam RADARSAT and ENVISAT ASAR) data led to identifying remote sensing based guides for archaeological exploration. Integration of known archaeological sites with the identified anomalous patterns was done in GIS environment. This study adds on to the knowledge base of the site and compliments already known information and suggested new areas for further archaeological exploration.     

1:10000地形图(DLG)数据生产的质量控制与检测

结合武汉市1:10000地形图生产项目,给出了1:10000地形图(DLG)数据生产的技术方法与流程,阐述了1:10000地形图(DLG)数据生产的质量控制过程及检测项目的具体内容。     

GNSS天线阵列接收机与无线传感器网络在灾害监测中的集成方法研究

主要讨论如何将GPS、GLONASS和Galileo系统集成到天线阵列接收机中,如何与无线传感器网络集成,实现数据传输的自动化,并利用无线传感器网络自组网、自适应等特点,实现节点定位,将GNSS天线阵列接收机的几何监测功能与传感器的物理监测功能结合起来,实现地面/地下、几何/物理的三维立体自动化监测。     

Multi-Index Soil Moisture Estimation from Satellite Earth Observations: Comparative Evaluation of the Topographic Wetness Index (TWI), the Temperature Vegetation Dryness Index (TVDI) and the Improved TVDI (iTVDI)

Soil moisture estimation from satellite earth observation has emerged effectively advantageous due to the high temporal resolution, spatial resolution, coverage, and processing convenience it affords. In this paper, we present a study carried out to estimate soil moisture level at every location within Enugu State Nigeria from satellite earth observation. Comparative analysis of multiple indices for soil moisture estimation was carried out with a view to evaluating the robustness, correlation, appropriateness and accuracy of the indices in estimating the spatial distribution of soil moisture level in Enugu State. Results were correlated and validated with In-Situ soil moisture observations from multi-sample points. To achieve this, the Topographic Wetness Index (TWI), based on digital elevation data, the Temperature Vegetation Dryness Index (TVDI) and an improved TVDI (iTVDI) incorporating air temperature and a Digital Elevation Model (DEM) were calculated from ASTER global DEM and Landsat images. Possible dependencies of the indices on land cover type, topography, and precipitation were explored. In-Situ soil moisture data were used to validate the derived indices. The results showed that there was a positive significant relationship between iTVDI versus TVDI (R = 0.53, P value < 0.05), while in iTVDI versus TWI (R = 0.00, P value > 0.05) and TVDI versus TWI (R = ?0.01, P value > 0.05) no significant relationship existed. There was a strong relationship between iTVDI and topography, land cover type, and precipitation than other indices (TVDI, TWI). In situ measured soil moisture values showed negative significant relationship with TVDI (R = ?0.52, P value < 0.05) and iTVDI (R = ?0.63, P value < 0.05) but not with TWI (R = ?0.10, P value > 0.05). The iTVDI outperformed the other two index; having a stronger relationship with topography, precipitation, land cover classes and soil moisture. It concludes that although iTVDI outperformed other indices (TVDI, TWI) in soil moisture estimation, the decision of which index to apply is dependent on available data, the intent of usage and spatial scale.     

Description of a New Method for Retrieving the Aerosol Optical Thickness from Satellite Remotely Sensed Imagery Using the Maximum Contrast Value and Darkest Pixel Approach

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative remotely sensed imagery and quantitative data, such as aerosol optical depth which is the basic unknown parameter for any atmospheric correction method in the pre‐processing of satellite imagery. This article presents a new method for retrieving aerosol optical thickness directly from satellite remotely sensed imagery for short wavelength bands in which atmospheric scattering is the dominant contribution to the at‐satellite recorded signal. The method is based on the determination of the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the ‘tracking’ of the suitable darkest pixel in the scene. The proposed method that needs no a‐priori information has been applied to LANDSAT‐5 TM, LANDSAT‐7 ETM+, SPOT‐5 and IKONOS data of two different geographical areas: West London and Cyprus. The retrieved aerosol optical thickness values show high correlations with in‐situ visibility data acquired during the satellite overpass. Indeed, for the West London area a logarithmic regression was fitted for relating the determined aerosol optical thickness with the in‐situ visibility values. A high correlation coefficient (r²= 0.82; p= 0.2) was found. Plots obtained from Tanre et al. (1979, 1990) and Forster (1984 ) were reproduced and estimates for these areas were generated with the proposed method so as to compare the results. The author's results show good agreement with Forster's aerosol optical thickness vs. visibility results and a small deviation from Tanre's model estimates.     

Quantifying deforestation in the Brazilian Amazon using Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) and Shuttle Imaging Radar (SIR)-C data

The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud.     

应用卫星与气象数据及其关系研究黄河流域的荒漠化现状

本文应用20年（1981—2000年）的卫星数据反演归一化差值植被指数（NDVI）,同时获取地面格网的温度与降雨数据,并分析这些数据之间的关系。基于地面的温度和降雨格网数据将研究区划分为8个气候区域,再利用NDVI数据把降雨量最少的3个气候区——区1,2,3各划分为10个等级。此外,分析这3个气候区在1983—1998年15年间的NDVI变化状况,结果显示出研究区荒漠化状况的加剧。     

Integrated study of aitutaki's lagoon (cook islands) using spot satellite data and in situ measurements: Bathymetric modelling

In the framework of a prospecting survey on the atoll of Aitutaki (Cook Islands) undertaken by the SOPAC, IFREMER has been charged with a pilot project, the purpose of which was to assess the use of remote sensing (SPOT) in the geomorphologic and bathymetric cartography of an atoll lagoon. The results of this project are presented according to two chapters. The first chapter proposes a numerical method for decorrelating the original variables and computing a textural parameter, which can be used to provide a map easy to interpret as far as geomorphologie studies are concerned. The second chapter proposes a method for inverting the relationship between radiometry and bathymetry, with a fit based on in situ measurements, resulting in the achievement of a bathymetric model for Aitutaki's lagoon.     

Model Building to Investigate the Role of Spatial Location in Classifying Satellite Image Using SVM,CART and mBACT: A Case Study

This paper investigates the importance of spatial location of pixels in terms of row-column as an additional explanatory variable in classification along with available spectral bands of remotely sensed data. In view of this, a forward step-wise variable selection algorithm is used to select significant bands/variables and build an optimal model to extract the maximum accuracy. Author performed a case study on the area of town of Wolfville acquired by LANDSAT 5 TM data containing six 30 m resolution spectral bands and pixel location as an additional variable. Data are classified into seven classes using three advanced classifiers i.e. classification and regression trees (CART), support vector machines (SVM) and multi-class Bayesian additive classification tree (mBACT). Traditionally, it is assumed that addition of more explanatory variables always increase the accuracy of classified satellite images. However, results of this study show that adding more variables may sometimes confuse the classifier, that is, if selected carefully, fewer variables can provide the more accurate classification. Importance of row-column information turns out to be more beneficial for mBACT followed by SVM. Interestingly, spatial locations did not turn out to be useful for CART. Based on the findings of this study, mBACT appears to be a slightly better classifier than SVM and a substantially better than CART.     

卫星网与地面网联合平差坐标转换模型的等价性

本文阐述了卫星网与地面网联合平差中Bursa模型所确定的参考椭球中心位置与Молоденский和Veis两个模型所确定的参考中心几何意义上的差别,导出了三个模型转换参数之间的变换矩阵,进而证明了以上三个模型在确定转换参数的联合平差中的等价性。指出三个模型方程状态上的差异对联合平差及坐标系统转换的最后结果和精度来说,并无丝毫影响。