Jianhua Gong

UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

Unmanned aerial vehicle (UAV) remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB) images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1) Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2) the inclusion of texture features improved classification accuracy significantly; (3) classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

Design and development of Distributed Virtual Geographic Environment system based on web services

This paper aims to design and develop a Distributed Virtual Geographic Environment (DVGE) system. A DVGE system is an Internet-based virtual 2D and 3D environment that provides users with a shared space and a collaborative platform for publishing multidimensional geo-data, and for simulating and analyzing complex geo-phenomena. Users logging into the system from different clients can share distributed geo-information resources, including geo-data and geo-models, and can complete collaborative tasks. Web service technology provides effective solutions for constructing DVGE systems because of its ability to support multi-platform, multi-architecture, and multi-program-language interoperability on the Internet, but also because of its ability to share programs, data, and software. This paper analyzes the characteristics, relevant technologies, and specifications of web services, such as grid services, Open Geo-data Interoperability Specifications (OpenGIS), and Geography Markup Languages (GML). The architecture and working mechanisms of the DVGE system based on web services are then elaborated. To demonstrate DVGE systems based on web services, we examine a case study of water pollution in Yangzhou City, Jiangsu Province, China, using a prototype DVGE system that is developed with Jbuilder9.0 and Java3D 1.0 packages, and the Weblogic platform 8.1.

Susceptibility assessment of earthquake-induced landslides using Bayesian network: A case study in Beichuan, China

Because of the uncertainties and complexities of the factors involved in causing landslides, it is generally difficult to analyze their influences quantitatively and to predict the probability of landslide occurrence. In this work, a hybrid method based on Bayesian network (BN) is proposed to analyze earthquake-induced landslide-causing factors and assess their effects. Our study area is Beichuan, China, where landslides have occurred in recent years, including mass landslides triggered by the 2008 Wenchuan earthquake. To provide a robust assessment of landslide probability, key techniques from landslide susceptibility assessment (LSA) modeling with BN are explored, including data acquisition and processing, BN modeling, and validation. In the study, eight landslide-causing factors were chosen as the independent variables for BN modeling. And this study shows that lithology and Arias intensity are the major factors affecting landslides in the study area. On the basis of the a posteriori probability distribution, the occurrence of a landslide is highly sensitive to relief amplitudes above 116.5m. Using a 10-fold cross-validation and a receiver operating characteristic (ROC) curve, the resulting accuracy of the BN model was determined to be 93%, which demonstrates that the model achieves a high probability of landslide detection and is a good alternative tool for landslide assessment.

A collaborative virtual geographic environment based on P2P and Grid technologies

Solving a geographic problem usually requires collaborative work among a group of people in different geographic locations. Collaborative virtual geographic environment (CVGE), an integrated technology, offers an intuitive, efficient, and interactive visualization environment through which geographically separated users can explore complicated spatial information and conduct collaborative work. In this paper, two new technologies, Peer-to-Peer (P2P) and Grid computing, are tightly coupled to develop a CVGE system. This paper evaluates the potential contributions of the P2P and Grid technology to CVGE systems. Using a Grid based system architecture efficiently integrates and shares geographically distributed resources as well as modeling procedures built on different platforms. To offer a shared and interactive virtual collaborative geographic environment for resolving geographic problems, we developed several P2P services including a terrain visualization collaboration service and a video collaboration service. Finally, a CVGE prototype system is implemented for collaboration on silt dam planning on the Loess plateau. The experimental results show that the scheme developed in this paper is efficient and feasible.

Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed

Abstract Human-induced land use/cover change has been considered to be one of the most important parts of global environmental changes. In loess hilly and gully regions, to prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades. The main objective of this study is to quantify the spatio-temporal variability of land use/cover change spatial patterns and make preliminary estimation of the role of human activity in the environmental change in Xihe watershed, Gansu Province, China. To achieve this objective, the methodology was developed in two different aspects, that is, (1) analysis of change patterns by binary image of change trajectories overlaid with different natural geographic factors, in which Relative Change Intensity (RCI) metric was established and used to make comparisons, and (2) analysis based on pattern metrics of main trajectories in the study area. Multi-source and multi-temporal Remote Sensing (RS) images (including Landsat ETM+ (30 June 2001), SPOT imagery (21 November 2003 and 5 May 2008) and CBERS02 CCD (5 June 2006)) were used due to the constraints of the availability of remotely sensed data. First, they were used to extract land use/cover types of each time node by object-oriented classification method. Classification results were then utilized in the trajectory analysis of land use/cover changes through the given four time nodes. Trajectories at every pixel were acquired to trace the history of land use/cover change for every location in the study area. Landscape metrics of trajectories were then analyzed to detect the change characteristics in time and space through the given time series. Analysis showed that most land use/cover changes were caused by human activities, most of which, under the direction of local government, had mainly led to virtuous change on the ecological environments. While, on the contrary, about one quarter of human-induced changes were vicious ones. Analysis through overlaying binary image of change trajectories with natural factors can efficiently show the spatio-temporal distribution characteristics of land use/cover change patterns. It is found that in the study area RCI of land use/cover changes is related to the distance to the river line. And there is a certain correlation between RCI and slope grades. However, no obvious correlation exists between RCI and aspect grades.

An open-source 3D solar radiation model integrated with a 3D Geographic Information System

Photovoltaic energy has become a popular renewable energy source for sustainable urban development. As a result, 3D solar radiation models are needed to facilitate the interactive assessment of photovoltaic potential in complex urban environments. SURFSUN3D is a visualization-oriented full 3D solar radiation model that has been shown to achieve efficient computation and visualization for 3D urban models. The present paper introduces a framework to integrate SURFSUN3D into a 3D GIS-based application to interactively assess the photovoltaic potential in urban areas.

A Spatial, Social and Environmental Study of Tuberculosis in China Using Statistical and GIS Technology

Tuberculosis (TB) remains a major public health problem in China, and its incidence shows certain regional disparities. Systematic investigations of the social and environmental factors influencing TB are necessary for the prevention and control of the disease. Data on cases were obtained from the Chinese Center for Disease and Prevention. Social and environmental variables were tabulated to investigate the latent factor structure of the data using exploratory factor analysis (EFA). Partial least square path modeling (PLS-PM) was used to analyze the complex causal relationship and hysteresis effects between the factors and TB prevalence. A geographically weighted regression (GWR) model was used to explore the local association between factors and TB prevalence. EFA and PLS-PM indicated significant associations between TB prevalence and its latent factors. Altitude, longitude, climate, and education burden played an important role; primary industry employment, population density, air quality, and economic level had hysteresis with different lag time; health service and unemployment played a limited role but had limited hysteresis. Additionally, the GWR model showed that each latent factor had different effects on TB prevalence in different areas. It is necessary to formulate regional measures and strategies for TB control and prevention in China according to the local regional effects of specific factors.

A visualization-oriented 3D method for efficient computation of urban solar radiation based on 3D–2D surface mapping

The temporal and spatial distribution of solar energy in urban areas is highly variable because of the complex building structures present. Traditional GIS-based solar radiation models rely on two-dimensional (2D) digital elevation models to calculate insolation, without considering building facades and complicated three-dimensional (3D) shading effects. Inspired by the ‘texture baking’ technique used in computer graphics, we propose a full 3D method for computing and visualizing urban solar radiation based on image-space data representation. First, a surface mapping approach is employed to project each 3D triangular mesh onto a 2D raster surface whose cell size determines the calculation accuracy. Second, the positions and surface normal vectors of each 3D triangular mesh are rasterized onto the associated 2D raster using barycentric interpolation techniques. An efficient compute unified device architecture -accelerated shadow-casting algorithm is presented to accurately capture shading effects for large-scale 3D urban models. Solar radiation is calculated for each raster cell based on the input raster layers containing such information as slope, aspect, and shadow masks. Finally, a resulting insolation raster layer is produced for each triangular mesh and is represented as an RGB texture map using a color ramp. Because a virtual city can be composed of tens of thousands of triangular meshes and texture maps, a texture atlas technique is presented to merge thousands of small images into a single large image to batch draw calls and thereby efficiently render a large number of textured meshes on the graphics processing unit.

Comparative analysis of land use/cover change trajectories and their driving forces in two small watersheds in the western Loess Plateau of China

Abstract To prevent soil loss and achieve better ecological environments, soil conservation measures have been taken during the past decades in the western Loess Plateau of China. In this paper, a case study was taken in Luoyu valley and Lver valley, two sub-watersheds of Xihe watershed and comparison was carried out between them. The main object of this study is to monitor land use/cover changes in the two similar small watersheds utilizing SPOT5 imageries by object-oriented human–computer interactive classification method, further develop the method of spatio-temporal analysis of land use/cover change by using pattern metrics of change trajectories and relative land use suitability index ( R ) in smaller watersheds, and make comparisons between the two similar small watersheds, taking water and soil conservation measures into consideration. Results show that combining GIS and RS, this method can be perfectly applied to make comparisons between different small watersheds with similar geographical backgrounds. And land use/cover spatiotemporal dynamic change characteristics can be preferably expressed by pattern metrics of change trajectories and R values based on topographical data. Different emphases have been laid according to their own geological backgrounds in the two watersheds and human activities have different effects on the landscapes of the two watersheds. The main change pattern is from slope farmland to terrace (322, the largest in Luoyu valley) or to economic fruit forest (344, the largest in Lver valley). R value of every slope grade in both of the two watersheds drops with the rising of slope degree on the whole and it shows that there is still much to do for people in the two watersheds in consideration that all the R values are still lower than 0.7.

Spatiotemporal simulation and risk analysis of dam-break flooding based on cellular automata

Chapinghe Barrier Lake was the largest among the barrier lakes formed in the aftermath of the magnitude 5.12 Wenchuan Earthquake. A rapid quantitative method for the evaluation of potential risk to lives and properties downstream was of the utmost importance for disaster management. The proposed method is based on spatiotemporal simulation using different dam-break scenarios and downstream hazard distribution analyses. This article adopts a cellular automata (CA) model to synthetically integrate multiple sets of geographic layers, including those containing the models needed for routine computation of flood hazards and those needed for vulnerability analysis of the people living downstream. A CA-based simulation and analysis method integrating hydrologic/hydraulic mechanisms is herein introduced, and relevant techniques are investigated. Our prototype experiment demonstrates that the proposed CA-based flood-hazard model can be conveniently integrated into a digital earth system and can further provide real-time simulation analyses of dam-break flood risks.