Xiaoxia Huang

Monitoring land-use change in the Pearl River Delta using Landsat TM

The Pearl River Delta in the Peoples Republic of China is experiencing rapid rates of economic growth. Government directives in the late 1970s and early 1980s spurred economic development that has led to widespread land conversion. In this study, we monitor land-use through a nested hierarchy of land-cover. Change vectors of Tasseled Cap brightness, greenness and wetness of Landsat Thematic Mapper (TM) images are combined with the brightness, greenness, wetness values from the initial date of imagery to map four stable classes and five changes classes. Most of the land-use change is conversion from agricultural land to urban areas. Results indicate that urban areas have increased by more than 300% between 1988 and 1996. Field assessments confirm a high overall accuracy of the land-use change map (93.5%) and support the use of change vectors and multidate Landsat TM imagery to monitor land-use change. Results confirm the importance of field-based accuracy assessment to identify problems in a land-use map and to improve area estimates for each class.

A level set filter for speckle reduction in SAR images

Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

A Fast Level Set Method for Synthetic Aperture Radar Ocean Image Segmentation

Segmentation of high noise imagery like Synthetic Aperture Radar (SAR) images is still one of the most challenging tasks in image processing. While level set, a novel approach based on the analysis of the motion of an interface, can be used to address this challenge, the cell-based iterations may make the process of image segmentation remarkably slow, especially for large-size images. For this reason fast level set algorithms such as narrow band and fast marching have been attempted. Built upon these, this paper presents an improved fast level set method for SAR ocean image segmentation. This competent method is dependent on both the intensity driven speed and curvature flow that result in a stable and smooth boundary. Notably, it is optimized to track moving interfaces for keeping up with the point-wise boundary propagation using a single list and a method of fast up-wind scheme iteration. The list facilitates efficient insertion and deletion of pixels on the propagation front. Meanwhile, the local up-wind scheme is used to update the motion of the curvature front instead of solving partial differential equations. Experiments have been carried out on extraction of surface slick features from ERS-2 SAR images to substantiate the efficacy of the proposed fast level set method.

Oil spill detection from thermal anomaly using ASTER data in Yinggehai of Hainan, China

The detection of oil spill is very important for the oil exploration. Remote sensing technology is one of the methods to detect the potential oil basin, especially in a large region. High resolution satellite images can be used as an approach of early oil exploration because its visualized, continuous and macroscopical characteristics. In this paper, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to detect the possible oil regions in the Yinggehai area of Hainan Province, China from thermal anomaly including sea surface temperature and apparent thermal inertia. By comparing with the drilling materials, our results show that the area with oil spill has a lower temperature and higher thermal inertia values than the surrounding areas. It indicates that our derived sea surface temperature and apparent thermal inertia anomaly just reflect the above mentioned status and the method can be used to detect the potential oil basin.

Remote sensing analysis of the distribution and genetic mechanisms of transportation network damage caused by the Wenchuan earthquake

Transportation networks are among the most important lifelines for post-seismic relief and reconstruction. It is imperative to investigate, monitor, and analyze transportation network damage caused by earthquake disasters in near real-time. Herein, we present a method for the analysis of seismic hazards and the subsequent assessment of the impact of the Wenchuan earthquake on transportation networks employing remote sensing and geographical information systems. In this method, the locations, shapes, lengths, and areas of the main damaged segments of state and provincial highways are interpreted and surveyed based on airborne ADS40 data and diverse remotely sensed satellite images of varying resolutions before and after the disaster. Next, the spatial distributions of geological disasters such as landslides, land-collapses, mud-rock flows, bank-collapses, earthquake rifts, and faults, as well as barrier lakes, were analyzed. These types of geological disasters commonly cause transportation network blockage and damage. Finally, geographical factors, including geological structures, topography, and landscapes, were collected and integrated with the disaster statistics to quantitatively analyze the primary transportation seismic disaster indices, and evaluate the geographical characteristics and genetic mechanisms of seismic disasters. Our results indicate that transportation network blockage and damage occurred in 808 segments, with a total length of 170.2 km, and occupied 29.66% of the total length of the state and provincial highways in the core disaster regions. The distribution of transportation network blockage and damage has obvious geographical characteristics. It is concentrated in regions near geological faults, folds, rock crushes, and breaks, especially near the Longmenshan-controlling fault, which played a decisive role in the Wenchuan earthquake. The remotely sensed images, maps, and analytical results on the geographical distribution and genetic mechanisms of the transportation network blockage and damage effectively guided the national department of transportation repair and reconstruction planning for the disaster areas.

Optimizing expressway maintenance planning by coupling ant algorithm and geography information system transportation in Hubei province, China

Highway maintenance scheduling is a complex optimization problem and imposes a challenge for GIS-T research. In this paper, a new approach was put forward to determining the optimal set of alternatives for highway infrastructure facilities by using ant colony algorithm and GIS. In the proposed approach, GIS was used to analyze traffic flux, toll and maintenance time of each highway segment. Meanwhile, an ant colony algorithm was applied to resolve the computational complexity of multi-objective large-size scheduling optimization problems. Experiments were performed in national highways in the Hubei province by the proposed method. The application illustrated the feasibility, efficiency, and capability of coupling ant algorithm and geography information system transportation for multi-objective expressway maintenance planning optimization.

Prediction of urban land use evolution using temporal remote sensing data analysis and a spatial logistic model

Urban land use systems are complex systems with components, factors and agents from natural, environmental, social and economic systems. In this paper, we developed a remote sensing and GIS-based integrated approach to modeling and predicting spatially-explicit urban land use changes. The model was built using temporal remote sensing data land use analysis coupled with a Markov model and a spatial multinomial logistic regression framework. Experiments were performed in the Shenzhen Special Zone to substantiate the accuracy of the proposed method. We show that integration of a Markov model and a spatial logistic model is an effective method to describe urban land use evolution and meet the needs of land use early warning and annual land supply planning.

Remote sensing applications for petroleum resource exploration in offshore basins of China

In this paper, a new approach for detecting and analyzing sea surface slicks caused by hydrocarbon seepage of offshore petroleum accumulations has been developed. This approach uses remote sensing radar technology and geophysical exploration techniques and has been developed based on hydrocarbon seepage theory. In this study, Synthetic Aperture Radar (SAR) data were used as the main data source. These data were integrated with gravity data inversed from satellite altimeter data, geophysical abnormal data from airborne magnetic data, and geological data of oil-and gas-bearing basins. Using the geographical information system, the oil and gas accumulating areas were outlined by the prospect models. This approach for the exploration and evaluation for offshore petroleum accumulations has been applied to two study areas in offshore petroleum basins in China: the Bohai Sea and Pearl River Mouth basins. By comparing the drilling outcomes and relative materials, our results show that the application of this integrated method is very effective.

Detection of natural oil seeps signature from SST and ATI in South Yellow Sea combining ASTER and MODIS data

Daytime Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) data and the consequent nighttime Moderate Resolution Imaging Spectroradiometer (MODIS) data have been utilized to retrieve the sea surface temperature (SST) and apparent thermal inertia (ATI). They were used to detect the signature of natural oil seepage in Yingge Sea Basin (YSB) and South Yellow Sea (SYS). In this paper, ATI was used for the first time to detect the signature of natural oil seepage. ATI is an approximation of the real thermal inertia and can be expressed as a function of surface albedo and temperature difference between day and night. Surface albedo can be calculated by weighting spectral reflectivities in visible and near-infrared bands from ASTER data. The spectral reflectivities can be obtained after performing atmospheric correction using the 6S model. An iterative self-consistent split-window algorithm was employed to retrieve the daytime SSTs from ASTER data and nighttime SSTs from MODIS data. Because of the spatial resolution difference between ASTER and MODIS data, the nighttime SST derived from MODIS data was downscaled from 1 km to 90 m using the pixel block intensity modulation (PBIM) method. Two study areas, YSB and SYS, were selected to detect the possible signature of the natural oil seepage. The approximate SST and ATI values in the YSB where natural oil seepage actually developed were derived in advance. A look-up table of albedo, temperature difference and ATI for different sea waters with or without natural oil seepage was constructed. These were then used as prior knowledge to enclose the possible signatures of natural oil seepage in SYS. Our results show that there are some signatures of natural oil seepage in the study area in SYS. Compared with SST, ATI was more sensitive to the signature of natural oil seepage. The reason for this might be that the temperature difference was used in the calculation of the ATI, which decreased the influence of the SST accuracy on ATI values.

A new method to calibrate Lagrangian model with ASAR images for oil slick trajectory

Since Lagrangian model coefficients vary with different conditions, it is necessary to calibrate the model to obtain optimal coefficient combination for special oil spill accident. This paper focuses on proposing a new method to calibrate Lagrangian model with time series of Envisat ASAR images. Oil slicks extracted from time series images form a detected trajectory of special oil slick. Lagrangian model is calibrated by minimizing the difference between simulated trajectory and detected trajectory. mean center position distance difference (MCPD) and rotation difference (RD) of Oil slicks or particles standard deviational ellipses (SDEs) are calculated as two evaluations. The two parameters are taken to evaluate the performance of Lagrangian transport model with different coefficient combinations. This method is applied to Penglai 19-3 oil spill accident. The simulation result with calibrated model agrees well with related satellite observations. It is suggested the new method is effective to calibrate Lagrangian model.