Urban road extraction from high-resolution optical satellite images

2005 ◽  
Vol 26 (22) ◽  
pp. 4907-4921 ◽  
Author(s):  
Hui Long ◽  
Zhongming Zhao
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Road Extraction ◽  
Urban Road ◽  
Optical Satellite Images

scholarly journals Lane-Level Road Extraction from High-Resolution Optical Satellite Images

2019 ◽  
Vol 11 (22) ◽  
pp. 2672
Author(s):  
Jiguang Dai ◽  
Tingting Zhu ◽  
Yilei Zhang ◽  
Rongchen Ma ◽  
Wantong Li
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Template Matching ◽  
City Planning ◽  
Urban Expansion ◽  
Satellite Image ◽  
Road Extraction ◽  
Urban And Rural Areas ◽  
Optical Satellite Images ◽  
Vehicle Management

High-quality updates of road information play an important role in smart city planning, sustainable urban expansion, vehicle management, urban planning, traffic navigation, public health and other fields. However, due to interference from road geometry and texture noise, it is difficult to avoid the decline of automation while accurately extracting roads. Therefore, we propose a high-resolution optical satellite image lane-level road extraction method. First, from the perspective of template matching and considering road characteristics and relevant semantic relations, an adaptive correction model, an MLSOH (multi-scale line segment orientation histogram) descriptor, a sector descriptor, and a multiangle beamlet descriptor are proposed to solve the interference from geometry and texture noise in road template matching and tracking. Second, based on refined lane-level tracking, single-lane and double-lane road-tracking modes are designed to extract single-lane and double-lane roads, respectively. In this paper, Pleiades satellite and GF-2 images are selected to set up different scenarios for urban and rural areas. Experiments are carried out on the phenomena that restrict road extraction, such as tree occlusion, building shadow occlusion, road bending, and road boundary blurring. Compared with other methods, the proposed method not only ensures the accuracy of lane-level road extraction but also greatly improves the automation of road extraction.

Toward a general tropical forest biomass prediction model from very high resolution optical satellite images

2017 ◽  
Vol 200 ◽  
pp. 140-153 ◽  
Author(s):  
P. Ploton ◽  
N. Barbier ◽  
P. Couteron ◽  
C.M. Antin ◽  
N. Ayyappan ◽  
...  
Keyword(s):  
High Resolution ◽  
Prediction Model ◽  
Tropical Forest ◽  
Satellite Images ◽  
Forest Biomass ◽  
Optical Satellite Images ◽  
Very High
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