Oblique photogrammetry with multiple cameras onboard unmanned aerial vehicle (UAV) has been widely applied in the construction of photorealistic three-dimensional (3-D) urban models, but how to obtain the optimal building facade texture images (BFTIs) from the abundant oblique images has been a challenging problem. This article presents an optimization method for selection of BFTIs from the image flows acquired by five oblique cameras onboard UAV. The proposed method uses multiobjective functions, which consists of the smallest occlusion of the BFTI and the largest façade texture area, to select the optimal BFTIs. Geometric correction, color equalization, and texture repairment are also considered for correction of BFTI's distortions, uneven color, and occlusion by other objects such as trees. Visual C++ and OpenGL under the Windows Operating System are used to implement the proposed methods and algorithms. The proposed method is verified using 49 800 oblique images collected by five cameras onboard the Matrice 600 Pro (M600 Pro) UAV system over Dongguan Street, in the City of Ji'nan, Shandong, China. To restore the partially occluded textures, different thresholds and different sizes of windows are experimented, and a template window of $200\times200$ pixels2is recommended. With the proposed method, 2740 BFTIs are extracted from 49 800 oblique images. As compared with the Pix4Dmapper and Smart 3-D method, it can be concluded that the optimal texture can be selected from the image flow acquired by multiple cameras onboard UAV and the approximately 95% memory occupied by the original BFTIs is reduced.

Surface broadband albedo is a critical parameter in surface radiation budget (SRB), which controls the input, separation, and allocation of the Earth's surface energy. Recently, a Global LAnd Surface Satellite (GLASS) phase-2 surface broadband albedo product has been generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) data. In this study, we present a preliminary validation of the GLASS phase-2 surface broadband albedo with the FLUXNET 2015 dataset. The results show that the GLASS phase-2 surface broadband albedo product has a reasonable good accuracy compared with the currently widely used surface albedo dataset, and can provides more reliable estimations of surface albedo at the seasonal snowfall and snowmelt regions. In addition, the GLASS phase- 2 surface albedo product is along-term, global covered (including land and ocean surfaces) dataset, which can be applied in various scenarios of SRB and climate change studies.

The karst collapse is one of the six major geological disasters in China, the karst region is also the main geological disasters, to the integration of subsidence data management and evaluation is particularly important. In this paper, Lai bin, Jili of Guangxi province is taken as an example, combining RS and GIS technology for thematic information extraction and data management, extracted from remote sensing image subsided land use types; Use of GIS software ArcGIS for platform, combining with subsidence history text, drawings, and on-the-spot field to get the data, established the perfect combination of spatial database, graphic data of subsidence geological environment evaluation and spatial analysis provides a scientific and effective management; The last, The use of GIS space analysis function to completed accurate sensitivity assessment collapse rapid.

This paper develops an ecological index (EI) model to assess ecological environment, which is more suitable for Guilin Karst Scenery, because of highlight a greater weight in land degradation, and a lower weight in biological abundance. The EI model considers the biological abundance index, vegetation coverage index, water density index, land degradation index, and environmental quality index, and these indexes are 55.7, 62.7, 69.8, 25.7, and 93, respectively. These indexes are taken into the EI model, and the ecological index is 60.3, which means that the karst ecological environment reaches a “Good” level, but not reaches an “Excellent” level. The results show that the City of Guilin, China presents a higher coverage of the vegetation, a richer biological diversity, and a suitable environment for human being survival. However, the results also indicate that the environmental problems have been arisen at the same time.

This article extracts and analyzes disaster information by using GIS and RS technology. It determines the weights by using the Analytic Hierarchy Process (AHP), and it constructs risk evaluation model to do risk evaluation of geological disasters. In this paper, Lai bin, Jili of Guangxi Province is selected as an example to evaluate the risk of Karst collapse because of its strong karst landform. This paper obtains karst collapse geological hazards risk zoning by using GIS and RS technology for the first time. Through analyzing the geological environment in the study area, it selects 10 evaluation factors to evaluate the risk of Karst collapse. At last, it gets the zoning evaluation map. The evaluation result is consistent with the actual situation in the study area, and it provides reference data to the economic development as well as for the prevention of karst collapse.

A new decision tree induction method, called co-location-based decision tree (CL-DT), is presented in this paper to extract exposed carbonatite in karst rocky desertification area. The proposed algorithm utilizes co-location characteristics of spatial attribute. This paper first presented the co-location mining algorithm, including neighbor graph construction, determination of distinct event-type, pruning non-prevalent co-locations, and inducing co-location rules, and then focused on developing the algorithm of co-location decision tree, which including non-spatial attributes data and spatial data selection, co-location modeling, node merging criteria, and co-location decision tree induction. This paper uses Landsat-5 TM images covering the whole Du'an city in China as the data to verify the proposed method. The experimental results demonstrated that (1) Compared to traditional decision tree, the proposed co-location decision tree has higher accuracy and can make better decision; (2) The training data can be fully played roles in contribution to decision tree induction.

To provide new and/or higher rate wireless services with limited spectrum resources, frequency overlay has been naturally proposed to accommodate the new and legacy systems in a common band. We address the multiuser detection problem for overlaid code-division multiple-access (CDMA) scenarios. However, in contrast to the well-studied conventional single-rate CDMA, miscellaneous systems overlay almost always indicates the presence of multirate traffic that introduces an additional degree of freedom in receiver design-i.e., differences in the symbol rates. We concentrate on receiver design for multirate traffic, while assuming a lack of information exchange between the constituent (new and legacy) systems, as is commonplace in practice. We propose a receiver architecture based on linear parallel interference cancellation where the out-of-rate intersystem interference is estimated and subtracted by means of its characteristic subspace, thereby avoiding the need for the exact knowledge of signature waveforms of the interfering system. Simulation results validate our solution and show that the proposed receiver has better performance in various aspects than several other solutions for the same purpose.

A new subspace method based on autocorrelation decomposition is developed for channel estimation. It is shown that under suitable conditions, identifiability can be guaranteed in the presence of channel order overestimates, in a clear contrast to most subspace methods such as [E. Moulines et al., Feb. 1995]. Moreover, simulations show that the proposed scheme is very robust against channel order overestimates, thereby de-emphasizing the need for complex order estimation procedures, i.e., a conservative order (over)estimate based on empirical knowledge such as maximum delay spread can be used in practice.

To provide new and/or higher rate wireless services with limited bandwidth resources, frequency overlay has been proposed to host heterogeneous traffic in common band, where one CDMA system is involved due to its noise-like nature. In the paper, we address multiuser detection problem for overlay scenarios where there exist multiple CDMA systems. We propose a linear parallel interference cancellation (PIC) structure where interference due to overlaid systems is captured and subtracted by means of its subspace. Simulation results validated our solution and show that the proposed receiver has better performance in various aspects than the conventional MMSE receiver.

Multi-rate CDMA is a potentially attractive multiple access method for future broad-band multimedia wireless networks that must support integrated voice/data traffic. The primary impairment for such multi-rate systems is the multipath nature of radio channels that results in intra-user inter-chip interference (ICI) and multi-user interference (MUI) between different users' symbols. Explicit knowledge of the channel is typically needed for high performance detectors (such as coherent demodulation). We propose a subspace method for channel estimation in multi-rate CDMA systems. A unified signal model that applies to three multi-rate CDMA schemes proposed in the literature is developed. The computational complexity for multi-rate scenarios is large and variable-accordingly, a modified approach is devised that offers performance/complexity trade-offs. Performance analysis is conducted based on a close-form expression for the mean square error of the estimator, supported by simulation results that investigate the effectiveness of our method.

A new frequency domain approach towards blind channel identification for multirate communication systems is described. Users are first separated based on different cyclic frequencies corresponding to their respective symbol rates, thereby resulting in a single-user (blind) identification scenario. The algorithm proposed by L. Tong et al. (see IEEE Trans. Inform. Theory, vol.41, no.1 p.329-34, 1995) is then used to estimate the channels for each rate. Computer simulations demonstrate the effectiveness of our method.

The problem of blind channel identification for multirate, multiuser communication systems is addressed. By exploiting symbol rate differences, it is shown that users can be separated based on the autocorrelation of the received signal, thus reducing the problem to the familiar single rate setting. A subspace method is then developed to identify the channel associated with each user. Simulations are used to explore algorithm performance as a function of key factors such as signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR).

In this paper, we propose a unified approach to blindly identify channels for multirate CDMA systems-both multiple code (MC) and variable processing gain (VPG) systems are considered. A time-domain subspace approach to blind channel estimation introduced in Torlak and Xu (1997) is generalized to the multi-rate case. Performance evaluation is conducted based on the normalized root mean square error (NRMSE) with an appropriate single-rate as a baseline for comparison.