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Various lunar digital topographic models (DTMs) have been generated from the data collected from earlier and recent lunar missions. There are usually inconsistencies among them due to differences in sensor configurations, data acquisition periods, and production techniques. To obtain maximum value for science and exploration, the multi-source lunar topographic datasets must be co-registered in a common reference frame. Only such an effort will ensure the proper calibration, registration, and analysis of the datasets, which in turn will permit the full comparative and synergistic use of them. This study presents a multi-feature-based surface matching method for the co-registration of multiple lunar DTMs that incorporates feature points, lines, and surface patches in surface matching to guarantee robust surface correspondence. A combined adjustment model is developed for the determination of seven transformation parameters (one scale factor, three rotations, and three translations), from which the multiple DTMs could be co-registered. The lunar DTMs derived from the Chang’E-1, SELENE, and LRO laser altimeter data in the Apollo 15 landing area and the Sinus Iridum area are examined in this study. Small offsets were found among the Chang’E-1, SELENE, and LRO DTMs. Through experimental analysis, the developed multi-feature-based method was proven able to effectively co-register multiple lunar DTMs. The performances of the multi-feature-based surface matching method were compared with the point-based method, and the former was proven to be superior to the latter.

Lunar orbital imagery and laser altimeter data are two major data sources for lunar topographic modeling. Most of the previous work has processed imagery and laser altimeter data separately. Usually though, there are inconsistencies between the topographic models derived from them. This paper presents an endeavor to integrate the Chang'E-1 imagery and laser altimeter data for consistent and precision lunar topographic modeling. A combined adjustment model for the Chang'E-1 imagery and laser altimeter data is developed, in which the participants are the laser altimeter points, image exterior orientation (EO) parameters, and tie points collected from the stereo images. A weighting scheme is designed for the participants in the adjustment, and a local surface constraint is imposed to improve the adjustment performance. The output of the combined adjustment is the refined image EO parameters and laser ground points. Experimental results using the Chang'E-1 data in the Apollo 15 and 16 landing site areas show that the proposed combined adjustment approach can reduce the misregistrations between the imagery and the laser altimeter data by a maximum of 1-18 pixels in image space. The Japanese SELenological and ENgineering Explorer (SELENE) laser altimeter data at the Apollo 15 and 16 landing site areas are employed for comparison analysis. Small shifts between the SELENE and Chang'E-1 laser altimeter data were found. The topography derived from Chang'E-1 data after the combined adjustment shows a relatively consistent trend with the topography determined by the SELENE laser altimeter data.

With the existing GPS, the replenishment of GLONASS and the launching of Galileo there will be three satellite navigation systems in the future, with a total of more than 80 satellites. So it can be expected that the performance of the global navigation satellite system (GNSS) will be greatly improved, especially in urban environments. This paper studies the potential benefits of GPS/GLONASS/Galileo integration in an urban canyon – Hong Kong. The navigation performances of four choices (GPS alone, GPS+GLONASS, GPS+Galileo and GPS+GLONASS+Galileo) are evaluated in terms of availability, coverage, and continuity based on simulation. The results show that there are significant improvements in availability, coverage and continuity, by using GPS+GLONASS+Galileo compared with the other choices. But the performance is still not good enough for most navigation applications in urban environments.

Soil degradation is the core of land degradation. The lost of organic material is a signature of the quality degradation and productivity decline of soils. Therefore, it is of importance to develop a relatively rapid and economic method for mapping soil organic matter (SOM) at regional scale using remote sensing images. The study was to investigate the upscaling method of estimation model for mapping SOM using hyperspectral remote sensing images and multi-source data through segmentation of land degradation spectral response units (DSRUs). The estimation model of SOM based on DSRUs was developed to map SOM using Hyperion images of Hengshan County in the northern Shaanxi Province of China. Results showed that the DSRU estimation model, based on the relationship between the SOM content and features of spectral and regional variables of DSRUs, was valid to estimate the content of SOM. The determinative coefficient (R2) of the model increased from 0.562 at the scale level of 25, to 0.721 at the scale level of 50, and to 0.722 at the scale level of 100. The environmental variables of elevation, slope and vegetation index (MCARI) were included in the DSRU models, making it advantageous over the in situ models. The mapping content of SOM based on DSRU estimation model using Hyperion image agreed with that by the field survey and by the Kridge interpolation. Our research concluded that the DSRU model provides a relatively rapid, cost-effective, and accurate way to map the content of SOM for the land management of large area.

The pseudolite-augmented GPS technique can overcome the limitations of GPS-only surveys in unfavourable environments, like urban areas, deep open-pit mines and valleys. However, several problems need to be solved before pseudolites can be employed in precise surveys. This paper discusses the potential use of pseudolites for deformation monitoring in unfavourable survey environments. An analysis was conducted to illustrate how pseudolite measurements can improve the strength of the positioning geometry at a hydro-power dam. The methodology for the integration of GPS and pseudolite measurements has been developed, in particular the method/strategy to calibrate the pseudolite multipath effect, one of the severe sources of errors in pseudolite measurements. A set of real GPS pseudolite observations based on a 10×20 m network was processed to demonstrate the usefulness of the developed methodology.

Along with improvements in International GPS Services (IGS) products with regard to GPS satellite orbit and clock errors, the Precise Point Positioning (PPP) technique has been developed in recent years. Compared with conventional GPS relative positioning mode, the PPP technique does not require the presence of a nearby reference station, which makes it more attractive than other techniques for some applications. However, to achieve centimetre-level positioning accuracy, all GPS errors have to be modelled carefully and removed from measurements. Some errors that have not been seriously considered in a relative positioning mode have to be treated now. This paper analyses the effects of the earth tide, satellite antenna offset, and phase wind-up corrections on the accuracy of the PPP technique. Similar to relative positioning mode, we can also combine measurements from different satellites and different epochs to reduce errors in measurement in the PPP data processing. The positioning accuracies wit...

Although GPS has been widely used for precision surveys, many survey environments, like in urban areas, deep open-pit mines and valleys, limit the number of visible GPS satellites, deteriorating the survey accuracy. In addition some engineering projects require higher positioning accuracy in a particular direction. A GPS-only system hardly satisfies the requirements. Pseudolite-augmented GPS survey technique can strengthen the positioning geometry. Pseudolite (PL) measurements, however, suffer from various sources of errors different from GPS observations. In order to employ them for precise surveys these sources of errors must be treated properly. This paper discusses of the major sources of errors in PL measurements and the methodologies for their mitigation. Some experimental tests are then presented.

In this paper, the basic precise point positioning model has been reviewed. A recursive least square algorithm that separates the position coordinates and other parameters, such as ambiguities and tropospheric delays, is proposed for kinematic PPP applications. A test was carried out to test the method proposed in this paper, which made use of a GPS buoy equipped with a pressure and a tilt meter to monitor the sea level in Hong Kong. The initial results from kinematic PPP positioning compared with conventional kinematic positioning methods shows th

Ground settlement has long been a problem in Hong Kong, as most usable land in Hong Kong was reclaimed from the sea. Ground settlement may affect building structures and underground facilities such as water supply and sewage systems built on the land. Measurements of ground settlement can provide valuable data for assessing the impacts of ground settlement and for improving designs of future land reclamation projects. Experiments have been carried out to assess the performance of INSAR in the environment of Hong Kong especially the temporal decorrelations of SAR images and the potential atmospheric effects on INSAR measurements, and to use INSAR to study the ground settlement problem in Hong Kong. This study finds that the temporal decorrelation is an important problem in the heavily vegetated rugged areas as usually expected, and that the atmospheric effects can be very significant at times. Ground settlements measured over the airport and a residential area are presented. It can be seen from the results that both of the areas are still settling significantly many years after the reclamation.

Satellite synthetic aperture radar (SAR) interferometry is used to investigate the slowly accumulating ground settlement at the new Chek Lap Kok Airport in Hong Kong. Most of the land occupied by the airport was reclaimed from the sea and therefore certain ground settlement in the area has been expected. A pair of ERS-2 SAR images spanning nearly a year is used in the study. The high spatial resolution (20 mx20 m) ground settlement map derived indicates that the settlement that occurred in the area over the time period is as large as 50 mm. The SAR measurement results agree with the levelling measurements at some benchmarks in the area to well within 1 cm(rms error), and the overall correlation between the two types of results is 0.89. The paper presents some brief background of interferometric SAR, and outlines the data processing methods and results.

For the extraction of land degradation information we should use not only information on climate, soil, vegetation, physiognomy, land use and its productivities, but also the knowledge and methodologies of geosciences. It is of importance to study some conceptual issues about geographic image cognition (GEOIC) on studying land degradation. The study is to discuss some conceptual issues and the theoretical background of the approach of geographic image cognition (GEOIC) on studying land degradation for building its methodological framework. Some issues concerning the approach of GEOIC on studying land degradation, especially the factors of impacting human's visual cognition, were discussed. The results indicated that the GEOIC is the objectification cognition on remote sensing images and multi-source information using geo-knowledge. As an integrated approach, it is the extension of the methodology of OBIA. The key objective of the GEOIC on studying land degradation is to simulate the function and process of the visual interpretation by experts, and extract spatial features, spatial object and spatial pattern of land degradation under the cognition mode of feature-object-pattern from remote sensing images and multi-source information. The methodology of the GEOIC is realized through the segmentation of geo-objects or meaningful image objects using remote sensing information, geographic information, vegetation, soil, and other ancillary information with geosciences knowledge and intelligence.

Land degradation is a major environmental problem internationally. Soil degradation is one of the key factors of land degradation, which is related to susceptibility to erosion, soil suitability, and soil characteristics especially at regional scale. It is important and meaningful to evaluate objectively land degradation at regional scale. The study is to present the classification approaches for land degradation by Degraded Soil Line Index (DSLI) and object-oriented method by determination of land degradation spectral response units (DSRU) compared to the spectral angle mapping (SAM) method using Hyperion image data for mapping land degradation. The method was tested in a study area located in Hengshan county in ShaanXi province, China, where is in the agriculture-pasture mixed area in Loess Plateau in China with complex physical geographical situation. The results showed that the three methods of SAM, DSLI and DSRU have the ability to map land degradation and degraded soil classes, and the performance of the methods of DSLI and SAM is different and DSLI is prior to SAM for land degradation mapping in the study area. Moreover, the results also showed that the object-oriented analysis method based on DSRU approach is valid for extraction of land degradation information and clearly shows the degraded land classes with an overall accuracy of 0.88 and Kappa coefficients of 0.86.

Experimental studies have been carried out to employ GPS to measure the vibrations of the 384 m tall Di Wang building in Shenzhen, China. Two GPS receivers were employed in the experiment with one set on the top of the building and the other on a reference station on the ground near-by. The GPS data were collected at a rate of 4 sets per second. The experiment was conducted under different weather conditions over two 24-hour periods. This paper describes the GPS equipment used, the field operations, the data processing and analysis strategies, and the results obtained from the study. It is shown from the study that GPS can be successfully applied for monitoring structural vibrations. However cautions have to be exercised in analyzing GPS data to remove biases such as the so-called GPS multi-path errors. Besides, some practical issues still need resolved before GPS can be applied routinely for this type of applications.

[1] The accuracy of estimated Precipitable Water Vapor (PWV) content in near real time using ground based GPS/Met strongly depends on the quality of GPS orbits. The impact of the predicted GPS orbits in IGS Ultra-rapid products on PWV estimation is investigated in this paper. A few satellites of poor orbits will contaminate the estimated PWV. In this study, variance ratios derived from adjusted GPS double difference carrier phase observations for different satellites are used to identify poor GPS orbits. By excluding or down weighting the measurements related to those poor satellites, the accuracy of PWV estimation can be significantly improved.

A new method of using GPS for monitoring local area deformations such as landslides is presented. Unlike the standard method of using GPS for deformation monitoring where a GPS receiver is required for each point to be monitored, the new method allows multiple points to be monitored with one receiver. A system that implements the concept has been developed. It uses a specially designed electronic component that allows a number of GPS antennas to be linked to a single GPS receiver. The receiver takes data sequentially from each of the antennas attached to the receiver. A distinctive advantage of the approach is that one GPS receiver can be used to monitor more than one point. The cost per monitored point is therefore significantly reduced. The design of the system, as well as the data management and processing strategies will be introduced in detail. Results from some preliminary tests will also be given.

Coastal wetlands are considered the most biologically diverse of all ecosystems. Understanding their structures and functions is important for coastal environmental management and development. Airborne LiDAR (Light Detection and Ranging) has emerged as an effective tool for creating high-resolution digital surface models (DSM, highest elevation points) and digital terrain models (DTM, ground only points), which are vital geographic information sources for various applications in coastal areas, and investigating spatial patterns of vegetation in areas that are difficult to access. This paper investigates LiDAR’s capability for mapping marine wetlands, extracting vegetation and channel networks, and identifying intertidal zones. The Yellow River Delta, China, was selected as a study site to conduct experiments. With only a 4.5-h flight, an area of more than 670 km2 was surveyed with great detail. High-resolution DSMs and DTMs were generated, the vegetation coverage and heights were extracted using methods based on height and multi-return and the results were compared, and the water and tidal channels, which reflect the complete water transport system in the area, were mapped and measured. By combining LiDAR data and local tidal observations, the intertidal zone, which is a significant part of coastal wetlands, is clearly identified.

It is well-known that interferometric SAR (INSAR) is a technology for the generation of high-precision digital elevation models (DEM) and the precise measurement of terrain surface deformation. The accuracy of DEM and deformation measurement is highly dependent on the quality of the interferogram generated. Such an interferogram is constructed by a pointwise complex multiplication of corresponding pixels in both datasets, which are respectively contained in master image and registered image. An exanimation of existing literature reveals that there is no, good, quantitative measure for the quality of interferograms, and visual inspection is still the best solutions available so far. By visual inspection, one recognizes those interferograms with continuous fringes as good ones and regards those with many discontinuous interferograms and speckles as being not good. As the pixels in the interferogram represent the phase value values, it is natural to think that, if the quality is good, the phase differences between neighbor pixels should be small, and thus the sum of all phase differences will still be small. This leads to the proposal of “sum of phase differences” (SPD) as a quantitative measure for the quality of interferogram. Two simulation tests have been conducted, and the results show that the SPD is a reliable measure.