scholarly journals Improving Wetland Characterization with Multi-Sensor, Multi-Temporal SAR and Optical/Infrared Data Fusion

10.5772/8327 ◽  
2009 ◽  
Author(s):  
Laura L. ◽  
Kevin Riordan ◽  
Richard B. ◽  
Nicole Miller ◽  
Mitch Nowels
Keyword(s):  
Data Fusion ◽  
Multi Temporal ◽  
Infrared Data

Radar and infrared data fusion algorithm based on fuzzy-neural network

2007 ◽  
Author(s):  
Feng Han ◽  
Wan Hai Yang
Keyword(s):  
Neural Network ◽  
Data Fusion ◽  
Fuzzy Neural Network ◽  
Fusion Algorithm ◽  
Fuzzy Neural ◽  
Infrared Data

scholarly journals Mapping and Quantifying the Human-Environment Interactions in Middle Egypt Using Machine Learning and Satellite Data Fusion Techniques

2020 ◽  
Vol 12 (3) ◽  
pp. 584
Author(s):  
José Manuel Delgado Blasco ◽  
Fabio Cian ◽  
Ramon F. Hanssen ◽  
Gert Verstraeten
Keyword(s):  
Land Cover ◽  
Data Fusion ◽  
Satellite Data ◽  
Rural Areas ◽  
European Space Agency ◽  
Optical Remote Sensing ◽  
Joint Research ◽  
Human Environment ◽  
Multi Temporal ◽  
Agricultural Areas

Population growth in rural areas of Egypt is rapidly transforming the landscape. New cities are appearing in desert areas while existing cities and villages within the Nile floodplain are growing and pushing agricultural areas into the desert. To enable control and planning of the urban transformation, these rapid changes need to be mapped with high precision and frequency. Urban detection in rural areas in optical remote sensing is problematic when urban structures are built using the same materials as their surroundings. To overcome this limitation, we propose a multi-temporal classification approach based on satellite data fusion and artificial neural networks. We applied the proposed methodology to data of the Egyptian regions of El-Minya and part of Asyut governorates collected from 1998 until 2015. The produced multi-temporal land cover maps capture the evolution of the area and improve the urban detection of the European Space Agency (ESA) Climate Change Initiative Sentinel-2 Prototype Land Cover 20 m map of Africa and the Global Human Settlements Layer from the Joint Research Center (JRC). The extension of urban and agricultural areas increased over 65 km2 and 200 km2, respectively, during the entire period, with an accelerated increase analysed during the last period (2010–2015). Finally, we identified the trends in urban population density as well as the relationship between farmed and built-up land.

Two-band Infrared Data Fusion Method Based-on Fractal Dimension

2006 ◽  
Author(s):  
Yuqiu Sun ◽  
Jinwen Tian ◽  
Jian Liu
Keyword(s):  
Fractal Dimension ◽  
Data Fusion ◽  
Fusion Method ◽  
Infrared Data

Data Fusion of Multi-Temporal SAR Remote Sensing with Improved D-S Algorithm and Application to Change Detection of Urban Terrain

2011 ◽  
Vol 30 (8) ◽  
pp. 1897-1900
Author(s):  
Guang-zhen Cao ◽  
Peng Hou ◽  
Ya-qiu Jin ◽  
Xian-qiang Mao
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Change Detection ◽  
Multi Temporal ◽  
Urban Terrain ◽  
Sar Remote Sensing

Multi-Temporal InSAR Data Fusion for Investigating Mining Subsidence

2011 ◽  
Author(s):  
Q. Sun ◽  
Z. W. Li ◽  
X. L. Ding ◽  
J. J. Zhu ◽  
J. Hu
Keyword(s):  
Data Fusion ◽  
Mining Subsidence ◽  
Multi Temporal

Multi-temporal satellite imagery and data fusion for improved land cover information extraction

2011 ◽  
Vol 2 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Sreenivas Kandrika ◽  
T. Ravisankar
Keyword(s):  
Land Cover ◽  
Data Fusion ◽  
Information Extraction ◽  
Satellite Imagery ◽  
Multi Temporal

Visible and Infrared Data Fusion

2016 ◽  
Vol 10 (2) ◽  
pp. 31-44 ◽  
Author(s):  
Gwanggil Jeon
Keyword(s):  
Data Fusion ◽  
Infrared Data
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