Tsunami damage assessment using high resolution satellite imagery: a case study of Aceh, Indonesia

2005 ◽  
Author(s):  
P. Chen ◽  
S.C. Liew ◽  
L.K. Kwoh
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Damage Assessment ◽  
Tsunami Damage ◽  
High Resolution Satellite Imagery

scholarly journals A fuzzy decision making system for building damage map creation using high resolution satellite imagery

2013 ◽  
Vol 13 (2) ◽  
pp. 455-472 ◽  
Author(s):  
H. Rastiveis ◽  
F. Samadzadegan ◽  
P. Reinartz
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Damage Assessment ◽  
Fuzzy Inference ◽  
Earthquake Damage ◽  
Fuzzy Decision Making ◽  
Inference System ◽  
High Resolution Satellite Imagery ◽  
Roof Part ◽  
Earthquake Damage Assessment

Abstract. Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

scholarly journals Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
Caroline W. Kabaria ◽  
Fabrizio Molteni ◽  
Renata Mandike ◽  
Frank Chacky ◽  
Abdisalan M. Noor ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Dar Es Salaam ◽  
Malaria Risk ◽  
Urban Malaria ◽  
High Resolution Satellite Imagery

scholarly journals Analysis of Rice Field Area Conversion in Sleman Regency from 2000 to 2015, Using High-Resolution Satellite Imagery (Case Study: Ngaglik, Mlati and Depok Sub-District)

2019 ◽  
Vol 3 (1) ◽  
pp. 195-203
Author(s):  
Prelin Leunupun ◽  
Frederik Samuel Papilaya
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Rice Field ◽  
Research Area ◽  
Visual Interpretation ◽  
High Resolution Satellite Imagery ◽  
Interpretation Method ◽  
Field Area ◽  
Yogyakarta City

The purpose of this research is to find out how much area of rice fields which is reduced due to being converted into built-up land in Sleman Regency, especially in sub-districts which adjacent to Yogyakarta City, such as Depok Sub-district, Mlati Sub-district and Ngaglik Sub-district, from 2000 to 2015. Classification method used in this research is visual interpretation method which utilized on-screen digitization. The output of this research is a Map of Rice Field Conversion into Built-up Land at Depok, Mlati and Ngaglik Sub-district in Sleman Regency from 2000 to 2015. The results of this research prove that GIS can be used to determine the extent of changes in a rice field at Ngaglik, Depok and Mlati sub-districts. The area of rice field that was converted into built-up land in the research area is 864.45 ha.

scholarly journals Large-scale monitoring of coppice forest clearcuts by multitemporal very high resolution satellite imagery. A case study from central Italy

2011 ◽  
Vol 115 (4) ◽  
pp. 1025-1033 ◽  
Author(s):  
Gherardo Chirici ◽  
Diego Giuliarelli ◽  
Daniele Biscontini ◽  
Daniela Tonti ◽  
Walter Mattioli ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Central Italy ◽  
High Resolution Satellite Imagery ◽  
Coppice Forest ◽  
Very High
Sign in / Sign up

Export Citation Format

Share Document