UNOSAT Gaza Strip Comprehensive Damage Assessment - 08 July 2025
The Centre for Humanitarian Data
·
2025
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Full Details
Title
UNOSAT Gaza Strip Comprehensive Damage Assessment - 08 July 2025
Description
**UNOSAT code: CE20231007PSE** This map illustrates a satellite imagery-based comprehensive assessment of damage and destruction to structures within the area of interest in the Gaza Strip, Occupied Palestinian Territory, based on images collected on 8 July 2025 when compared to images collected on 1 May 2023, 10 May 2023, 18 September 2023, 15 October 2023, 7 November 2023, 26 November 2023, 6-7 January 2024, 29 February 2024, 31 March - 1 April 2024, 3 May 2024, 6 July 2024, 3-6 September 2024, 1 December 2024, 25 February 2025, and 4 April 2025. According to satellite imagery analysis, UNOSAT identified 102,067 destroyed structures, 17,421 severely damaged structures, 41,895 moderately damaged structures, and 31,429 possibly damaged structures for a total of 192,812 structures. These correspond to around 78% of the total structures in the Gaza Strip and a total of 282,904 estimated damaged housing units. The governorates of Khan Yunis and Rafah have experienced the highest rise in damage compared to the 4 April 2025 analysis, with around 8,681 new structures damaged in Khan Yunis and around 7,112 in Rafah. Within Khan Yunis, Khan Yunis City municipality had the highest number of newly damaged structures, totalling 5,865. This is a preliminary analysis and has not yet been validated in the field.
Creator
UN Operational Satellite Applications Programme (UNOSAT)
Publisher
The Centre for Humanitarian Data
Temporal Coverage
2025-08-05
Date Issued
2025-08-06
License
http://www.opendefinition.org/licenses/cc-by-sa
Access Rights
Public
Date Added
August 23, 2025
Provenance Statement
The metadata for this resource was last retrieved from Humanitarian Data Exchange on 2025-08-23.
UN Operational Satellite Applications Programme (UNOSAT) (2025). UNOSAT Gaza Strip Comprehensive Damage Assessment - 08 July 2025. The Centre for Humanitarian Data. https://data.humdata.org/dataset/66105a96-0c4c-46ce-9443-92cb199d32b0 (dataset)