Feature selection for remote-sensing data classification

1994 ◽  
Author(s):  
Sebastiano B. Serpico ◽  
Paolo Pellegretti ◽  
Lorenzo Bruzzone
Keyword(s):  
Remote Sensing ◽  
Feature Selection ◽  
Remote Sensing Data ◽  
Data Classification ◽  
Sensing Data ◽  
Selection For

scholarly journals The Determination of Rainfall Threshold Triggering Landslides Using Remote Sensing

2021 ◽  
Vol 893 (1) ◽  
pp. 012011
Author(s):  
L Agustina ◽  
A Safril
Keyword(s):  
Remote Sensing ◽  
Rainfall Intensity ◽  
Nearest Neighbor ◽  
Remote Sensing Data ◽  
Rainfall Threshold ◽  
Rainfall Data ◽  
Bilinear Method ◽  
Sensing Data ◽  
Central Java ◽  
Hourly Rainfall

Abstract Landslide is one of the natural disasters that can cause a lot of loss, both material and fatalities. Banjarnegara Regency is one of Central Java Province regencies where landslides often occur due to the region's topography and high intensity rainfall.. Therefore, it is necessary to determine the threshold of rainfall that can trigger landslides to be used as an early warning for landslides. The rainfall data used for the threshold is daily and hourly rainfall intensity from remote sensing data that provides complete data but relatively rough resolution. So that remote sensing data need to be re-sampled. The remote sensing data used is CMORPH satellite data that has been re-sampled for detailing existing information of rainfall data. The resampling method used is the bilinear method and nearest neighbor by choosing between the two based on the highest correlation. Threshold calculation using Cumulative Threshold (CT) method resulted equation P3 = 7.0354 - 1.0195P15 and Intensity Duration (ID) method resulted equation I = 1.785D-0305. The peak rainfall intensity occurs at the threshold of 97-120 hours before a landslide occur.

Sign in / Sign up

Export Citation Format

Share Document