At 3:42 on July 28

1976

a strong earthquake of magnitude Ms7.8 with a focal depth of 12 km and an epicentral intensity of XI degrees occurred in the Tangshan area of Hebei Province. The earthquake caused severe casualties and property losses and the most serious damage in Tangshan

but it also spread to Beijing and Tianjin. Equal intensity maps of the Tangshan earthquake were studied in detail by using relevant preserved data. After the Tangshan earthquake

significant departments conducted aerial photography for the first time and gathered the most valuable information for the earthquake damage distribution.Seismic damage information and sand-water blasting are interpreted and extracted by comparing KH satellite and aerial images before and after the earthquake

respectively. The image features for earthquake damage interpretation are summarized

and the meizoseismal area and damage zone are determined. Change detection in major counties is processed using aerial

KH

and Landsat MSS images before and after the earthquake. A total of 2495 building samples are selected

and the change detection of key villages and town targets is performed through correlation analysis. The damage degree and its trend are studied on the basis of change detection. The earthquake fault is analyzed using aerial images

aftershock distribution

and aeromagnetic images. Then

the intensity zone is determined by interpolating sample points through the method of inverse distance weighted interpolation. The seismic intensity zone of the Tangshan earthquake has been interpreted by combining multi-source remote sensing data. This map has finer details than previous results but with high similarity.This paper comprehensively used multi-source remote sensing data to realize the determination of seismic intensity zones. The results obtained are as follows： (1) The aerial images after the Tangshan earthquake were mosaicked

the characteristics of the earthquake damage in Tangshan were analyzed

and interpretation marks of the aerial images were established. (2) US KH satellite and aerial images before and after the earthquake

respectively

were analyzed comparatively. The damage to buildings in Tangshan City and its surrounding towns and the collapse rate information were extracted by using the change detection method based on object-oriented image processing. The 90.9% collapse rate of Tangshan City and its surrounding towns was calculated through a comprehensive analysis. (3) Landsat

aerial

and KH images of cities and towns before and after the earthquake were obtained

and 2495 building zone samples were clipped from images. Correlation coefficients were determined from pre- and post-earthquake images. The correlation analysis shows that the correlation coefficient is low from towns near the epicenter and high from towns far from the epicenter. This result is consistent with the actual situation. (4) On the basis of typical tectonic interpretation marks in aerial films

the active tectonic map of the Tangshan area was obtained using KH

aerial

and ETM images

which provide the information basis for the direction of intensity distribution. (5) On the basis of these results

with reference to the previous research intensity map

the threshold of correlation points was determined through statistical analysis. The intensity distribution area was identified by interpolating the sample data on the basis of the IDW interpolation method. The trend of intensity maps was simplified using seismogenic faults

historical earthquakes

and other tectonic data. The generated earthquake intensity has changed in detail

but it is similar to the field survey results.Rapid mapping of intensity maps after earthquakes is significant in deploying rescue work and reducing casualties and property losses caused by earthquakes. On the basis of remote sensing data

the intensity map was formulated

and it was revised using numerous methods for further precision and accuracy. With a variety of sensors and the launch of UAV photogrammetry and remote sensing

remote sensing technology will play an increasingly important role in drawing and revising seismic intensity maps. The seismic intensity assessment in this study requires a high level of sample data and a uniform distribution. In the future

additional samples should be selected to improve the accuracy of seismic intensity estimation.