Yunhao Chen

Shadow information recovery in urban areas from very high resolution satellite imagery

It is usually quite difficult to extract and recover shadow information in the urban environment from remote sensing imagery. This paper describes the study of precisely detected shadow in satellite images and recovering information from the surface covered in shadow from very high resolution (VHR) satellite imagery.

Object-oriented classification for urban land cover mapping with ASTER imagery

This document demonstrates the potential of using an object‐oriented approach to map urban land cover. One objective of this work was to test the ability of the object‐oriented classification in the generation of urban land cover maps. Anotehr was to produce an updated land cover map for the city of Beijing from Advanced Spaceborne Thermal Emission and Reflecton Radiometer (ASTER) data, with an evaluation of its accuracy.

An Object-Oriented Semantic Clustering Algorithm for High-Resolution Remote Sensing Images Using the Aspect Model

In this letter, we present a novel object-oriented semantic clustering algorithm for high-spatial-resolution remote sensing images using the probabilistic latent semantic analysis (PLSA) model coupled with neighborhood spatial information. First of all, an image collection is generated by partitioning a large satellite image into densely overlapped subimages. Then, the PLSA model is employed to model the image collection. Specifically, the image collection is partitioned into two subsets. One is used to learn topic models, where the number of topics is determined using a minimum description length criterion. The other is folded in using the learned topic models. Therefore, every pixel in each subimage has been allocated a topic label. At last, the cluster label of every pixel in the large satellite image is derived from the topic labels of multiple subimages which cover the pixel in the image collection. Experimental results over a QUICKBIRD image show that the clusters of the proposed algorithm are better than K-means and Iterative Self-Organizing Data Analysis Technique Algorithm in terms of object-oriented property.

Validation of MISR land surface broadband albedo

Land surface broadband albedo is a critical variable for many scientific applications. Due to the scarcity of spectral albedo measurements of the Earths surface environments, it is useful to construct broadband albedo from spectral albedo data obtained by multi‐angle satellite observations. The Multi‐angle Imaging SpectroRadiometer (MISR) onboard NASAs Earth Observing System (EOS) Terra satellite provides land surface albedo products from multi‐angular observations; however, the products have not been comprehensively validated. We convert MISR spectral albedos to total shortwave albedos and validate them using ground measurements at different validation sites. For most surface types, a published narrowband to broadband conversion formula was used, but a new conversion formula for snow and ice covered sites is developed in this study where the spectral range of the instrument is different. Several comparisons are made: (1) between MISR directional‐hemispherical reflectance (DHR) or albedo and MODIS (Moderate Resolution Imaging Spectroradiometer) DHR; and (2) between MISR spectral DHR and bi‐hemispherical reflectance (BHR). The results show that: (1) both the value and the temporal trends of the MISR shortwave albedo and the ground measured shortwave albedo are in good agreement, with the exception of the snow and ice sites; (2) the MISR DHR conforms well to MODIS DHR; and (3) the values of MISR DHR and BHR are nearly identical.

Analysis of green space in Chongqing and Nanjing, cities of China with ASTER images using object-oriented image classification and landscape metric analysis

Green space is an important urban land use which can enhance the livability of cities. Chinese cities develop rapidly, and increasingly strong emphasis has been put on the provision of better landscape and more green space. We used an object‐oriented approach to classify different land covers in Chongqing and Nanjing, two historical Chinese cities. Suitable segmentation levels were selected by locating break points along the variation of selected object variables. Three segmentation levels were identified for each city. Object variables with good discriminatory power were selected to identify different land covers by making use of their spectral, textural and shape properties. Decision tree classifiers were formulated for classifying images into eight land cover classes. Accuracy of object‐oriented classification was the highest in Chongqing and ranked second in Nanjing. The result was compared to those of maximum likelihood classification, fuzzy classification and linear unmixing classification. Land covers were then generalized as green space for landscape metric analysis. The fragmented nature of green space was discussed. It was revealed that there existed a general lack of green space in old urban centres. With an increasing distance from city centres, more large patches were found.

Quantifying driving forces of urban wetlands change in Beijing City

The decision tree and the threshold methods have been adopted to delineate boundaries and features of water bodies from LANDSAT images. After a spatial overlay analysis and using a remote sensing technique and the wetland inventory data in Beijing, the water bodies were visually classified into different types of urban wetlands, and data on the urban wetlands of Beijing in 1986, 1991, 1996, 2000, 2002, 2004 and 2007 were obtained. Thirteen driving factors that affect wetland change were selected, and gray correlation analysis was employed to calculate the correlation between each driving factor and the total area of urban wetlands. Then, six major driving factors were selected based on the correlation coefficient, and the contribution rates of these six driving factors to the area change of various urban wetlands were calculated based on canonical correlation analysis. After that, this research analyzed the relationship and mechanism between the main driving factors and various types of wetlands. Five conclusions can be drawn. (1) The total area of surface water bodies in Beijing increased from 1986 to 1996, and gradually decreased from 1996 to 2007. (2) The areas of the river wetlands, water storage areas and pool and culture areas gradually decreased, and its variation tendency is consistent with that of the total area of wetlands. The area of the mining water areas and wastewater treatment plants slightly increased. (3) The six factors of driving forces are the annual rainfall, the evaporation, the quantity of inflow water, the volume of groundwater available, the urbanization rate and the daily average discharge of wastewater are the main factors affecting changes in the wetland areas, and they correlate well with the total area of wetlands. (4) The hydrologic indicators of water resources such as the quantity of inflow water and the volume of groundwater are the most important and direct driving forces that affect the change of the wetland area. These factors have a combined contribution rate of 43.94%. (5) Climate factors such as rainfall and evaporation are external factors that affect the changes in wetland area, and they have a contribution rate of 36.54%. (6) Human activities such as the urbanization rate and the daily average quantity of wastewater are major artificial driving factors. They have an influence rate of 19.52%.

Fractal analysis of the structure and dynamics of a satellite-detected urban heat island

In this Letter, three fractal models—surface, profile and pixel models are developed to analyse the structure and dynamics of an urban heat island (UHI). These three models were tested using data from Shanghai taken in 1990, 1995 and 1998. The surface model is capable of capturing the fractal dimension of the entire study area. The profile model can be used to analyse the structural characteristics of the UHI along certain directions and is capable of revealing changes in the texture characteristics of UHI. The pixel model can describe the changes in thermal characteristics surrounding each pixel in a particular locale and is suitable for analysing the micro‐structure of the UHI.

Detection of coal fire location and change based on multi-temporal thermal remotely sensed data and field measurements

This study focuses on analysis methods for monitoring coal fires, using a combination of multi‐temporal thermal infrared data, high spatial resolution remote sensing data and field measurements. This technical note is prepared as a feasibility study for the detection of coal fire dynamics in the Inner Mongolia Autonomous Region in northern China.

DEM accuracy comparison between different models from different stereo pairs

The digital elevation model (DEM) has served as a very important source of data that is able to provide useful information about land transformations. It has been widely used for various geographic information system (GIS) applications that use elevation as their main parameter. Conventionally, a DEM is generated based on a topographical survey. However, this method is extremely time-consuming and less efficient when applied to an area that is not easily accessible. In recent times, the application of remote sensing technology to the generation of DEMs has been developed, including radargrammetry, which is suited to tropical forest areas due to its ability to work day and night and in all weather conditions. This enables accurate DEMs to be generated with minimal ground survey (Toutin 1999). This paper describes a study of DEM generation using the radargrammetry technique based on different theories, and the accuracy of the DEM is assessed to evaluate the efficiency of different methods in tropical rain forest regions in Malaysia.

Generation of a top-of-canopy Digital Elevation Model (DEM) in tropical rain forest regions using radargrammetry

A feasibility study is prepared for creating a top‐of‐canopy Digital Elevation Model (DEM) based on Radarsat data from the tropical rain forest regions of Malaysia. Through a case study, the accuracy of the generated DEM is verified, showing reasonable accuracy.