In this study, the damage caused by the 2022 flood in the Sindh Province is assessed using GIS (Geographical Information System) and RS (Remote Sensing) techniques, employing satellite data and a questionnaire survey. The flood that occurred in 2022 significantly impacted the Sindh province, making it the most affected region in Pakistan. To evaluate the extent of flood damage across various sectors, both primary and secondary sources and methods were utilized. Primary data was gathered through a questionnaire survey, while secondary data was sourced from NASA’s Worldview website using the Flood (2-Day Window) data from the MODIS Near Real-Time Global Flood Product. The questionnaire survey involved collecting responses from the affected community through questionnaires, personal observations, and Geo-tagging via Google Forms. For the analysis of the pre-flood and post-flood situations in Sindh, two satellite images were examined: one from July 30, 2022, representing the pre-flood state, and the other from September 30, 2022, representing the post-flood state. Spatio-temporal analysis was conducted in three phases at intervals of 10 days (on the first, 10, 20, and 30 of September, 2022) to track the gradual rise in the inundated area. The results indicated a consistent increase in the inundated area with each interval. The inundated area on the first and tenth of September measured 17,332.42 km2 and 19,023.39 km2, respectively, while on the 20 and 30 of September, it expanded to 21,559.84 km2 and 25,223.60 km2, respectively. The study results revealed an estimated 1.94 million damaged houses, 4.3 million affected acres of agricultural land, and 0.45 million affected livestock. The rehabilitation cost for house damage, agricultural land, and livestock was estimated at 192.54 billion, 395.43 billion, and 46.17 billion, respectively. This study serves as a valuable resource for assessing district-wise damage and estimating rehabilitation costs in the Sindh province. It provides insights into the extent of the damage caused by the 2022 flood, offering critical information for planning and resource allocation for rehabilitation efforts.