scholarly journals Using Boosted Regression Trees and Remotely Sensed Data to Drive Decision-Making

2017 ◽  
Vol 07 (05) ◽  
pp. 859-875 ◽  
Author(s):  
Brigitte Colin ◽  
Samuel Clifford ◽  
Paul Wu ◽  
Samuel Rathmanner ◽  
Kerrie Mengersen
Keyword(s):  
Decision Making ◽  
Regression Trees ◽  
Remotely Sensed ◽  
Boosted Regression Trees ◽  
Remotely Sensed Data

scholarly journals Niche Modeling of Dengue Fever Using Remotely Sensed Environmental Factors and Boosted Regression Trees

2017 ◽  
Vol 9 (4) ◽  
pp. 328 ◽  
Author(s):  
Jeffrey Ashby ◽  
Max Moreno-Madriñán ◽  
Constantin Yiannoutsos ◽  
Austin Stanforth
Keyword(s):  
Environmental Factors ◽  
Dengue Fever ◽  
Regression Trees ◽  
Remotely Sensed ◽  
Niche Modeling ◽  
Boosted Regression Trees

THE ROLE OF REMOTE SENSING DATA FOR COASTAL ZONE MONITIORING AND MANAGEMENT (CASE STUDY FOR THE EAST PART OF GULF OF FINLAND)

2017 ◽  
Author(s):  
Nikifor Ostanin ◽  
Nikifor Ostanin
Keyword(s):  
Remote Sensing ◽  
Coastal Zone ◽  
Environmental Changes ◽  
Rapid Development ◽  
Water Environment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Gulf Of Finland ◽  
Coastal Protection ◽  
Remotely Sensed Data

Coastal zone of the Eastern Gulf of Finland is subjected to essential natural and anthropogenic impact. The processes of abrasion and accumulation are predominant. While some coastal protection structures are old and ruined the problem of monitoring and coastal management is actual. Remotely sensed data is important component of geospatial information for coastal environment research. Rapid development of modern satellite remote sensing techniques and data processing algorithms made this data essential for monitoring and management. Multispectral imagers of modern high resolution satellites make it possible to produce advanced image processing, such as relative water depths estimation, sea-bottom classification and detection of changes in shallow water environment. In the framework of the project of development of new coast protection plan for the Kurortny District of St.-Petersburg a series of archival and modern satellite images were collected and analyzed. As a result several schemes of underwater parts of coastal zone and schemes of relative bathymetry for the key areas were produced. The comparative analysis of multi-temporal images allow us to reveal trends of environmental changes in the study areas. This information, compared with field observations, shows that remotely sensed data is useful and efficient for geospatial planning and development of new coast protection scheme.

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