From Signal to Destruction
For nearly six weeks, Israel and the United States waged war against Iran in the spring of 2026. More than 700 attacks struck the capital of Tehran alone, where the country's military and political leadership is concentrated. Targets ranged from military installations to nuclear, research, and industrial facilities, and from oil and gas fields to logistics hubs and ports. During this time, access for journalists was practically impossible. What remained was reporting from space.
In this context, we at Vertical 52 developed an analysis of the potential destruction in the Iranian capital — based on radar data from the European Earth observation satellite Sentinel-1. We made our analysis available to the Süddeutsche Zeitung, which combined it with data from the U.S.-based Institute for the Study of War (ISW). The ISW data draws on reported attacks, verified eyewitness videos, and field reports, and documents airstrikes across Iran from February 28 onward. The Neue Zürcher Zeitung also drew on our analysis for its reporting.
Our method is based on so-called SAR coherence: a measure of how stable the received phase remains between two SAR acquisitions of the same area at different points in time. Unlike classical backscatter, which primarily captures the amplitude or intensity of the reflected radar signal, coherence evaluates phase stability — that is, how similar the microstructure of a surface is between two acquisitions. Intact buildings and stable urban structures produce consistent phase patterns over time — coherence remains high. Even small changes in surface structure — caused by destruction, displacement, or debris accumulation — produce phase changes; the signals lose their coherence between the two points in time. We harness this effect through the LT-CCD approach (Long-Term Coherence Change Detection): instead of comparing individual image pairs, we first compute a stable reference state from multiple acquisitions taken before the event. Anything that subsequently deviates significantly and unusually, we flag as a potential damage indicator. For Tehran, we set the reference date roughly one year before the attacks began; from 25 coherent image pairs, we built a baseline that describes the typical dynamics of the urban area. Our destruction analysis then covered several time steps between February 28 and April 8 — making not only the extent of the damage but also its temporal sequence visible. On our maps, larger circles indicate particularly extensive destruction.
The types of targets Israel and the United States struck most often during these weeks can be read from the combined evaluation of the ISW data and our radar analysis: in Tehran, the attacks centered on military targets, security apparatus facilities, and civilian and political institutions. As already seen in the Twelve-Day War of June 2025, both armed forces also targeted Iran's nuclear program — and not only uranium enrichment plants, but also research centers and the researchers themselves. Both Sharif University and Shahid Beheshti University, which conduct research for the Islamic Republic's nuclear program, appear on the EU sanctions list.
Methodology in comparison: Scher, Bellingcat, and Vertical 52
In parallel with our analysis, the researcher Corey Scher and the investigative platform Bellingcat published their own assessments of the damage in Tehran — likewise based on SAR data, but with different methodological emphases. What all three approaches share is their radar-based starting point: they operate independently of lighting conditions and cloud cover — where optical sensors go blind in clouds or darkness, SAR satellites keep delivering data. Methodologically, however, the approaches differ markedly. Scher's approach is very similar to ours: he too works with coherence analysis; the differences lie primarily in the interpretation of results, in the thresholds used, and in the selection of baseline and comparison images. Bellingcat, by contrast, relies more heavily on SAR backscatter — measuring changes in the amplitude of the reflected signal rather than in its phase stability.
From this, different strengths emerge: backscatter analyses respond sensitively to large, high-energy scattering changes — such as exposed debris fields or craters — and deliver particularly clear signals in those cases. Coherence analyses also capture more subtle changes in surface structure, but in return are more sensitive to vegetation, weather, and temporary effects. Regardless of the specific SAR method, the same caveat applies: we do not deliver images of destroyed buildings, but statistical anomalies in the radar signal — indicators, not proof. We see this difference not as a weakness, but as a methodological characteristic that enables a different kind of statement: not the individual documented impact image, but the spatial pattern across an entire urban area. Combined with high-resolution optical satellite data and OSINT verification, this produces a more robust overall picture than any single method could deliver on its own.
Lebanon: the same method, adjusted parameters
For our analysis of the destruction in southern Lebanon, which we carried out on behalf of the Süddeutsche Zeitung, we used the same LT-CCD workflow — with one central adjustment. In Tehran, we placed the reference date roughly one year before the attacks because no relevant prior damage was known for that period. In Lebanon, however, shelling incidents had already occurred before February 28. A reference date set far in the past would have classified this early damage as a "normal" state and thereby excluded it from the analysis. Instead, we chose February 18 as the baseline date — ten days before the war began and thus the last point in time directly before the documented escalation. From this starting point, we formed 25 coherent image pairs; our destruction analysis then covered the period from February 28 to April 25.
Technically, we followed the established workflow: we first calculated the baseline coherence, then compared it with the post-event acquisitions, and identified significant coherence losses as potential damage indicators. We then performed a statistical threshold analysis, generated damage proxy layers from it, and vectorized the results to make them usable for mapping. For the period of the attacks as well, we layered multiple analyses of the same area on top of one another — this minimizes the risk of misinterpreting temporary changes such as shadows, vegetation, or construction work as damage.
The temporal resolution of our analysis makes the dynamics of the escalation visible: compared with February 18, relatively few damage indicators are added by March 14 — the radar signals show only a handful of conspicuous points along the eastern border. After that, the damage increases significantly. By April 13, one month later, dozens of locations in the country's interior and along the coast are also affected; by the end of April, the clusters south of the Litani River continue to grow. The spatial pattern of our evaluation aligns with the military approach described by the SZ in its report: Israel is not only conducting airstrikes, but is also operating with ground troops in the country and has declared a roughly ten-kilometer-wide zone along the border in which, according to the Israel Defense Forces (IDF), no one is to remain. The IDF call this the "Forward Defense Line"; on several occasions, the Israeli government has also spoken of wanting to control the entire area south of the Litani.
According to the SZ's reporting, the rationale behind this operation is the desire to put a definitive end to the attacks of the Hezbollah militia. After Hamas's October 7, 2023 attack on Israel, which killed more than 1,200 people, Hezbollah positioned itself as an ally of Hamas and fired rockets into northern Israel. Following the Israeli and U.S. strikes on Iran, the Tehran-financed militia — designated as a terrorist organization by Germany and the United States, among others — sided with the Iranian regime and intensified its attacks. This context matters for reading our maps: they show no isolated individual strikes, but a broad, expanding pattern of damage that traces the geography of a military strategy.
Combined with data from the Institute for the Study of War (ISW) — which is compiled from eyewitness accounts, reported incidents, and the analysis of photo and video material from the ground — together with the SZ's own OSINT research and an on-site visit by the editorial team, this produces a comprehensive picture of the conflict. According to Lebanese authorities, the Israeli army has so far destroyed more than 62,000 housing units in southern Lebanon and in the southern suburbs of Beirut, around 21,700 of them completely.
