Sajad Sayadi

@sajadsayadi.bsky.social

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M.Sc. Graduate, KNT University Remote Sensing | Photogrammetry ---→ Environmental Monitoring, Forest Ecology, Wildfire, UAV Photogrammetry, Bundle Adjustment, Canopy Cover #RemoteSensing #Photogrammetry #UAV #Drone #DeepLearning #GIS

The 8th ISPRS Geospatial Conference 2025 at the University of Tehran, Iran, December 16, 2025. A research poster titled "Detection and Attribution of Thermal Anomalies in Urban Blocks of Qom Using Time-Series Analysis of TIR Imagery". The visual content includes spatial distribution maps of 22 identified thermal anomalies and LST time-series graphs. The methodology highlights Median Absolute Deviation (MAD) for outlier removal and noise filtering and the Reed-Xiaoli (RX) algorithm for anomaly detection and identifying deviated thermal behaviors.

Comparison of Global Shutter (full sensor exposure) vs. Rolling Shutter (sequential line-by-line exposure).

Flowchart for moving beyond NDVI: Sentinel-2 multispectral data feeds two paths: (a) Generation of NDVI; (b) Calculate EVI coefficients with PSO → Classification with EVI. In parallel, Google Earth imagery → Manual classification (veg/non-veg).

Red: vegetation by tuned EVI but non-vegetation by traditional EVI; Blue: the opposite

NDVI (left) vs PSO-tuned EVI (right) in semi-arid mountains; the optimized EVI produced a wider vegetation value range, higher variance, and mapped more vegetation pixels than NDVI and the conventional EVI.