Damage assessment of Taipa area in Central Sulawesi

✦ DISCOVERED BY ORIONAIUnited Nations Satellite Centre (UNOSAT)Buildings and infrastructureIndonesia
Indonesia

About this dataset

This map illustrates satellite-detected building damage assessment as of 02 October 2018, over Taipa area northeastern Palu city in Central Sulawesi following the 7.5 magnitude earthquake and subsequent tsunami of the 28th of September 2018. The analysis was conducted using a post-event Worldview-2 satellite image acquired 2 October 2018. UNITAR-UNOSAT identified in the analysed area 399 potentially damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents 10 % of the total number of structures within this analysed zone of Taipa.This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Documentation

UNOSAT datasets and maps are produced using a variety of methods. In general, analysts closely review satellite imagery, often comparing two or more images together, and determine notable changes between the images. For damage assessments, refugee or IDP assessments, and similar analyses, these changes are then manually documented in the vector data by the analyst. For flood extractions, landcover mapping and similar analyses, a variety of automated remote sensing techniques are used to extract the relevant information which is then reviewed and revised as necessary by the analyst. In all cases, resulting data is then loaded into a standardized UNOSAT geodatabase and exported asshapefiles for dissemination. This is a preliminary assessment and has not yet been validated in the field. It is important to consider the characteristics of the source imagery used in the analyses when interpreting results. For damage assessments it should be noted that only significant damage to the structural integrity of the buildings analyzed can be seen in imagery, while minor damage such as cracks or holes may not be visible at all. For flood extractions using radar data it is important to note that urban areas and highly vegetated areas may mask the flood signature and result in underestimation of flood waters. Users with specific questions or concerns should contact unosat@unitar.org to seek clarification.

Related datasets

✦ Suggested by OrionAI
Damage assessment of Tawaeli area in Central Sulawesi

This map illustrates satellite-detected building damage assessment as of 02 October 2018, over Tawaeli area northeastern Palu city in Central Sulawesi following the 7.5 magnitude earthquake and subsequent tsunami of the 28 September 2018. The analysis was conducted using a post event Worldview 2 satellite image acquired 2 October 2018. UNITAR UNOSAT identified in the analysed area 531 potentially damaged structures.Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents 15% of the total number of structures damaged within this analysed zone of Tawaeli. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)
Damage assessment of Pantoloan area in Central Sulawesi

This map illustrates satellite-detected building damage assessment as of 02 October 2018, over Pantoloan area northeastern Palu city in Central Sulawesi following the 7.5 magnitude earthquake and subsequent tsunami of the 28th of September 2018. The analysis was conducted using a post-event Worldview-2 satellite image acquired 2 October 2018. UNITAR-UNOSAT identified in the analysed area 424 potentially damaged structures.Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 10% of the total number of structures damaged within this analysed zone of Pantoloan. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR – UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)
Damage assessment of Tulehu area, Eastern part of Salahutu District, Maluku Tengah Regency, Maluku Province

**UNOSAT code: EQ20191001IDN** This map illustrates satellite based structure damage assessment in the Eastern part of Salahutu District, Indonesia that was affected by the 6.8 magnitude earthquake of the 26th of September 2019 with an epicenter located north of Kamarian in Kairatu District. UNITAR-UNOSAT has identified within the extent of this map 6 potentially damaged structures around Teluhu village in Salahutu District. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap we estimate to less than 1% the total number of structures potentially damaged. Taking into account the type of structural damage and the satellite based damage assessment analysis characteristics and limitations; it is possible that the damage is underestimated. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)
Damage assessment of Waai area, Eastern part of Salahutu District, Maluku Tengah Regency, Maluku Province

**UNOSAT code: EQ20191001IDN** This map illustrates satellite based structure damage assessment in the Eastern part of Salahutu District, Indonesia that was affected by the 6.8 magnitude earthquake of the 26th of September 2019 with an epicenter located north of Kamarian in Kairatu District. UNITAR-UNOSAT has identified within the extent of this map 17 potentially damaged structures around Waai village in Salahutu District. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap we estimate to less than 2% the total number of structures potentially damaged. Taking into account the type of structural damage and the satellite based damage assessment analysis characteristics and limitations; it is possible that the damage is underestimated. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)
Damage Assessment of Eua Island, Tonga

This map illustrates satellite-detected building damage assessment as of 13 February 2018, over the Island of Eua, Tonga, following the passage of the tropical cyclone GITA-18. The analysis was conducted using post-event WorldView-2 images and pre-event GeoEye-1 images as of 28 June 2017. A total of 542 buildings were detected as damaged over the towns of Houma, Ohnoua, Pangai and Tufuvai. According to the pre-building footprints provided by Humanitarian Open Street Map, this represents 47% of the total number of structures in Eua Island. The analysis could have been underestimated due to cloud cover. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)
Damage Assessment in the town of Atzala, Municipality of Atzala, State of Puebla, Mexico

This map illustrates satellite-detected, potentially damaged structures in the town of Atzala, Atzala Municipality, Puebla State, Mexico. The analysed area is located approximately 7 km west of the mainshock epicentre of the 19 September M 7.1 earthquake. UNITAR-UNOSAT identified 91 potentially damaged structures of which 78 are within the town extent. Taking in account the total 559 pre-event structures in Atzala town, 14% of the structures are likely to be damaged. These analyses was performed using a post-event Pleiades satellite image acquired on 22 September 2017 and a pre-event WorldView-2 satellite image acquired on 11 April 2017. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Buildings and infrastructure · United Nations Satellite Centre (UNOSAT)

Indexed by OrionGIS from Humanitarian Data Exchange (HDX). Data is loaded from the publisher's own server when you use it. Permanent link