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The inventory of economic forest planting on mountainous area is of great interest for the shareholders, ecologists, and governors. This study presents a novel object-based remote sensing image texture extraction method to aid the classification of mountain economic forest. Whereas the texture pattern of man-planted forest on mountainous area are similar with human fingerprint on remote sensing images,...
Change Vector Analysis (CVA) is an important change detection method for remote sensing imagery with medium and low resolution. Traditional CVA is a pixel-based method, which is insufficient for high-resolution (HR) imagery. An object-oriented change vector analysis method (OCVA) is proposed in the paper. Image segmentation method was used to get image objects. The object histogtam was extracted as...
The recent development in sensor technology shows the unprecedented growth of Remote Sensing (RS) data archives-Big Data. However, this growth in RS archives has resulted in many processing challenges. The three V's of big data- Volume, Velocity and Variety is highly relevant in situations such as flood, earthquake disaster, where real/near real time processing of data from different RS data sources...
The classification procedure to identify remote sensing signatures from a particular geographical region can be achieved using an accurate image classification approach which is based on multispectral sets and uses pixel statistics for the class description, and it is referred to as the Multispectral Pixel Classification method. This paper presents a study of the performance that this approach provides...
Land cover change detection has long been a hot field in polarimetric synthetic aperture radar (SAR) applications. In certain cases, we care not only the changed areas but also from which type to another. This paper presents a supervised urban land cover change types identification method using a series of polarimetric descriptors from SAR observables and polarimetric decomposition. The normalized...
Coastline extraction in Synthetic aperture radar (SAR) images is a fundamental and challenging task due to the speckle noise. In this paper, we propose a new method for automatic coastline extraction in SAR images. In our method, we combine K-means and speckle noise removal methods together to increase the dissimilarity between sea and land. To enhance the robustness to speckle noise, and preserve...
Earthquake is one of the most serious natural disasters in the world. With the continuous improvement of the spatial resolution of remote sensing image, it contains more abundant information, which can better reflect the features of geometric structure and texture information. The operation of the image is not only rely on the image element, but also use the object to carry on the operation. This...
In remote sensing, temporal sequence of images called Satellite Image Time Series (SITS) covering the same scene allows land cover observation, understanding, analysis and monitoring. Nowadays, STIS are accessible with higher spatial and temporal resolution which hampers their interpretation. This paper presents a spatio-temporal regions' similarity framework using a novel matrix based on Kullback-Leibler...
As the development of marine economy and population explosion, coastal areas is suffering great pressure - because of the immigration from inland to the developed cities along east China. Island coastal zones, which is a specific ecosystem surrounded by the sea, is more sensitive to human activities, e.g. reclamations. It is essential to monitor the dynamic changes of the island coastal areas to retrieve...
Due to the different imaging modalities and acquisition time, keypoint-based registration methods often suffer from false matches of keypoints while utilizing to register the optical remote sensing images from multi-sensors. In this paper, we proposed a novel method based on Line-Point Invariant for the multi-sensor image registration. First, the line segments of the images are extracted, and then...
The leaked heat pipeline can be detected as temperature anomalies from the air-borne thermal image. Existing methods of thermal anomaly detection are prone to generate a large quantity of false alarms. Although supervised classification can reduce the false positive rate, it requires years of accumulated training data. In this paper, we use human visual system to improve the detection capabilities...
It is significant for geological disasters detection from remote sensing image in emergency rescue. However, the automatic detection methods for geological disasters, depending only on low-level imagery features, generally result in low recognition precision. In practice, the most current extraction approaches of geological disasters are manual visual interpretation with the aid of experts' knowledge...
Remote sensing has been widely applied for environmental monitoring by means of change detection techniques, commonly for identifying deforestation signs which is the gateway for illegal activities such as uncontrolled urban growth and grazing pasture. Monthly acquired X-Band images from airborne Synthetic Aperture Radar (SAR) provided multi-temporal scenes employed in this work resulting in environmental...
Converting probability maps derived from indicator cokriging (ICK) to a specific land cover classification map is the second step of super-resolution mapping (SRM) under the geostatistical framework. In this study, two image segmentation strategies, namely mathematical morphology and region growing, were applied on the ICK-derived probability maps in order to take into account spatial characteristics...
Typical tiling approaches to segmentation of large images perform separated runs of a specific segmentation algorithm on tiles and then merge the results. However, specific post-processing is often required to remove possible artifacts on tiles junctions. In this paper, we aim at showing that a simple tiling strategy with partially overlapping tiles can be applied to a 2-nd order variational segmentation...
In this paper, a novel threshold segmentation method for remote sensing images is proposed. The proposed method is based on Wilcoxon rank sum test and mean absolute deviation (MAD) model with color feature and can segment roads and residential areas from vegetation more accurately. Three steps are used to realize the new method. First, we use blue and green color components as paired sample on Wilcoxon...
Earthquake is one of the most destructive natural disasters. Lushan Ya'an earthquake occurred in April 20, 2013 caused a wide range of road damage. The earthquake made Baoxing country become an island and rescue was difficult to carry out. The secondary disaster caused by earthquakes is one of the main causes of road damage. According to the present situation of damaged road extraction, a new method...
In this paper, we investigate the role of polarimetric features to improve flood mapping in agricultural areas. Considering that the double bounce enhancement due to standing water can increase the backscatter from flooded agricultural fields, polarimetry can potentially detect this mechanism and mitigate the misdetection of algorithms based on the identification of dark areas in the image. The investigation...
Sea ice charts are provided operationally by the Canadian Ice Service (CIS) for the convenience of people in high-latitude regions. Hence, approaches to ice-water discrimination are in demand. An approach is proposed in this paper, in which no manual interpretation is involved in the selection of training data. It is done based on the discrepancy of incidence angle dependence between sea ice and open...
Road traffic volume monitoring plays an important role in transportation planning and spatial development, particularly in urban areas. The high-resolution satellite imagery provides a new data source to detect vehicles. Meanwhile, Satellite image covers large areas instantaneously, providing a possibility for snapshotting road traffic conditions. In this paper, we proposed an approach based on watershed...
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