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In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image wi...
Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolut...
How to derive contour of buildings from VHR images is the essential problem for automatic building extraction in urban area. To solve this problem, OSM data is introduced to offer vector contour infor...
At present, in the inspection and acceptance of high spatial resolution remotly sensed orthophoto image, the horizontal accuracy detection is testing and evaluating the accuracy of images, which mostl...
Topic modeling has been an increasingly mature method to bridge the semantic gap between the low-level features and high-level semantic information. However, with more and more high spatial resolution...
A kernel-based method for very high spatial resolution remote sensing image classification is proposed in this article. The new kernel method is based on spectral-spatial information and structure inf...
With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and an...
Riparian zones maintain water quality, support multiple geomorphic processes, contain significant biodiversity and also maintain the aesthetics of the landscape. Australian state and national governm...
Remote sensing images fusion can not only improve the spatial resolution for the original multispectral image, but also preserve the spectral information to a certain degree. In order to find out the ...
Texture quantization is a useful method for extraction spatial relevance between pixels which is used in humane brain for image interpreting. Beside the spectral bands textural features of high spatia...
In the paper, a novel method for high spatial remote sensing data classification was put forward. The method was based on fuzzy set theory combined with NDVI. The classification experiments were carri...
For the significance of road information to the city management, urban roads are subjects of great concern to be extracted from remotely sensed images. With the availability of high spatial resolution...
Remote sensing techniques have been commonly used to map land cover and land use types. For many applications, users may only be interested in a specific land class in an image such as extracting urba...
Lacunarity based measures can be described as texture recognition approaches that provide a flexible yet theoretically consistent mean of characterizing the morphology of urban spatial patterns across...
The linear spectral mixing model is a widely used technique in remote sensing to estimate the fractions of several individual surface components present in an image pixel and the pure reflectance spe...

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