Analysis of Flood Damage Assessment through WorldView-2, Quick Bird and Multispectral Satellite Imagery in Southern Punjab, Pakistan

2019 ◽  
Author(s):  
Muneeb Aamir ◽  
Syed Amer Mahmood ◽  
Farzeen Riaz ◽  
Nida Farooq ◽  
Rabia Rasheed ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Damage Assessment ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Research Area ◽  
Flood Damage ◽  
Flood Mapping ◽  
Gis Techniques ◽  
Rs And Gis ◽  
Multispectral Satellite Imagery

Pakistan has faced numerous natural disasters like floods, earthquakes, landslides and environmental degradation which severely affects the Pakistan’s economy and results in various problems like causalities, diseases, water stress and severe damages (e.g., houses, public infrastructure and agricultural land erosion). There is a lack of systematic approaches to analyze pre and post damage assessment for estimation of exact loses and the total cost for rehabilitation of damaged infrastructure in an efficient way. There exist a variety of mechanisms but GIS based flood mapping is considered the most efficient to manage the flood situation. This study is focused on evaluation of flood affected areas especially in Punjab using WorldView-2, 8-band multi-spectral imagery by applying Remote Sensing (RS) and GIS techniques. The research area is comprised of Kot Addu and Muzaffargarh Districts in Punjab province of Pakistan that faced a catastrophic super flood of 2010. The WorldView-2, Quick Bird and multispectral satellite imagery are capable of making better decisions and assessment of flood effected area accurately. RS and GIS techniques can achieve the objectives and significant analyses through visual interpretations. These techniques are also used to identify the flood affected regions. The study site was examined by applying supervised classification on the basis of the training areas which were obtained during the field surveys in the study site. Supervised classification determines that 16900.96 Hectors of agriculture land was damaged while Sparse Riverine Forest had the area 44.52 hectors. The damaged built-up area was 1805.78 Hectors. RS and GIS techniques are efficient for flood mapping.

scholarly journals PERUBAHAN LUAS TUTUPAN LAHAN PADA AREAL HUTAN LINDUNG GUNUNG SIRIMAU KOTA AMBON

2021 ◽  
Vol 5 (1) ◽  
pp. 68-77
Author(s):  
Ian Komul ◽  
Merlin Renny Sitanala
Keyword(s):  
Satellite Imagery ◽  
Supervised Classification ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Monitoring ◽  
Primary Data ◽  
Digital Analysis ◽  
Analysis Method ◽  
Residential Areas ◽  
Annual Increase

The purpose of this research was to determine changes in forest cover of Mount Sirimau Protected Forest in Ambon City which have been analyzed since 1990, 2000, 2006, 2011 and 2015. This research was conducted using analytical methods where satellite imagery of 5 different years in 1990, 2000 and 2006 recording years, 2011 and 2015 were interpreted digitally through supervised classification. After the interpretation, the mapping was carried out using ArGIS to analyze changes in forest cover. It is supported by the data from the Forest Monitoring Center of Ambon Area IX that had been obtained using ArGIS into primary data. The data were analyzed by using the digital analysis method or the maximum opportunity method. The results showed changes in land cover in 2000, 2006 and 2011 from areas of forest become agricultural land and in 2015 the area of agricultural land was changed into settlements areas. The augmentation of non-forest areas (Settlements) along the Toisapu hamlet and Soya villages up to 2015 for residential areas has reached 16,997 Ha with an average annual increase of 70.59 km2.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

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.

On the modeling of significance for flood damage assessment

2014 ◽  
Vol 10 ◽  
pp. 381-391 ◽  
Author(s):  
D. Molinari ◽  
F. Ballio ◽  
J. Handmer ◽  
S. Menoni
Keyword(s):  
Damage Assessment ◽  
Flood Damage ◽  
Flood Damage Assessment

scholarly journals Ex post damage assessment: an Italian experience

2014 ◽  
Vol 14 (4) ◽  
pp. 901-916 ◽  
Author(s):  
D. Molinari ◽  
S. Menoni ◽  
G. T. Aronica ◽  
F. Ballio ◽  
N. Berni ◽  
...  
Keyword(s):  
Data Collection ◽  
Damage Assessment ◽  
Local Level ◽  
Data Gathering ◽  
Recovery Phase ◽  
Flood Damage ◽  
Local Authorities ◽  
Damage Models ◽  
Ex Post ◽  
And Storage

Abstract. In recent years, awareness of a need for more effective disaster data collection, storage, and sharing of analyses has developed in many parts of the world. In line with this advance, Italian local authorities have expressed the need for enhanced methods and procedures for post-event damage assessment in order to obtain data that can serve numerous purposes: to create a reliable and consistent database on the basis of which damage models can be defined or validated; and to supply a comprehensive scenario of flooding impacts according to which priorities can be identified during the emergency and recovery phase, and the compensation due to citizens from insurers or local authorities can be established. This paper studies this context, and describes ongoing activities in the Umbria and Sicily regions of Italy intended to identifying new tools and procedures for flood damage data surveys and storage in the aftermath of floods. In the first part of the paper, the current procedures for data gathering in Italy are analysed. The analysis shows that the available knowledge does not enable the definition or validation of damage curves, as information is poor, fragmented, and inconsistent. A new procedure for data collection and storage is therefore proposed. The entire analysis was carried out at a local level for the residential and commercial sectors only. The objective of the next steps for the research in the short term will be (i) to extend the procedure to other types of damage, and (ii) to make the procedure operational with the Italian Civil Protection system. The long-term aim is to develop specific depth–damage curves for Italian contexts.

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