Synthetic Aperture Radar Interferometry (InSAR) is a powerful tool for monitoring ground deformation over large areas

with applications in geological disaster monitoring

inversion of groundwater status

building health analysis

earthquake parameter extraction

post-disaster relief

and more. However

existing digital earth platforms

such as Google Earth and ArcGIS

face challenges in supporting the exploration and querying of vast InSAR datasets

including slow processing speeds

unsupported data formats

and difficulties with secondary development. This study examines the challenges associated with online visualization of time-series point clouds and proposes principles for pre-processing

storage

exploration

and querying of such datasets. Challenges include slow graphics rendering on webpages

limited network bandwidth that hinders real-time updates during exploration

and large data sizes that can pose storage challenges. To overcome these challenges

we suggest separating position and colorc information from temporal information

partitioning data using an octree structure

and using various compression techniques. Based on these principles

we utilize Cesium.js

a JavaScript library that enables developers to create 3D globes and maps in a web browser with high performance and precision to develop a platform for the visualization and interpretation of InSAR point clouds

which we call WIMAP. This allows us to easily create interactive visualizations of geospatial data. To test the platform

we processed two SAR datasets covering a plain and a mountainous area

respectively

and obtained corresponding time-series point clouds. We tested the performance of the platform using these point clouds and demonstrated its ability to run smoothly under such conditions. Specifically

on a computer equipped with a mid-range graphics card

it was able to maintain a frame rate of over 30 FPS while browsing time-series point clouds containing tens of millions points. Additionally

compared to the original plain binary format

the size of binary data stored on server could be reduced to approximately one quarter using preprocessing tools provided by the platform. All deformation analysis tools

including single point time-series query

deformation rate along profile line query

and multi-temporal deformation along profile line query

work properly. Spatial profile analysis

which included spatial interpolation with a buffering radius of 200 meters

was performed on time-series point cloud datasets with over 100 epochs and took less than 20 seconds to complete. This performance is comparable to that of locally conducted queries based on Kd-tree on available computers. The WIMAP platform allows users to explore InSAR point clouds in their browser and facilitates the distribution of InSAR results. Individual organizations and research institutions can upload their processed InSAR results to the platform's server

providing geoscientific information for users in various industries. With the visualization and interpretation tools bundled

users can analyze InSAR multi-temporal observations

combined with three-dimensional terrains and optical images

to gain insights into various geological phenomena. This may accelerate the research progress in several areas

such as landslide studies

earthquake monitoring

volcanic deformation analysis

and coastal erosion monitoring.