This study was conducted to precisely map burned areas in fire-prone forest regions of İzmir and analyze the spatial distribution of wildfires. Using Sentinel-2 satellite imagery, burn severity was first classified using the dNBR and dNDVI indices. Subsequently, machine learning (ML) algorithms—RF, XGBoost, LightGBM, and AdaBoost—were employed to classify burned and unburned areas. To enhance model performance, hyperparameter optimization was applied, and the results were evaluated using multiple accuracy metrics. This study found that the RF model achieved the highest performance, with an overall accuracy of 98.0% and a Kappa coefficient of 0.960. In comparison, classification based solely on spectral indices resulted in overall accuracies of 86.6% (dNBR) and 81.7% (dNDVI). A key contribution of this study is the integration of Explainable Artificial Intelligence (XAI) through SHapley Additive exPlanations (SHAP) analysis, which was used to interpret the influence of key spectral and environmental variables in burned area classification. SHAP analysis made the model decision processes transparent and identified dNBR, dNDVI, and SWIR/NIR bands as the most influential variables. Furthermore, spatial analyses confirmed that variations in spectral reflectance across fire-affected regions are critical for accurate burned area delineation, particularly in heterogeneous landscapes. This study provides a scientific framework for post-fire ecosystem restoration, fire management, and disaster strategies, offering decision-makers data-driven and effective intervention strategies.

Digital elevation models (DEM) are indispensable elements of sensitive earth science studies. It is important that production and usage of DEMs. The science of remote sensing offers scientists an important source of data on this subject. Radar data, which is an active remote sensing system, has an important capacity in this regard. DEM production using InSAR data has been widely used in the literature in the last decade. The temporal baseline parameter, which is an important factor in data generation from InSAR pairs, also affects the final products. In this study, it is aimed to examine the usability of these data by producing short (4days), medium (84 days) and long (440 days) baseline DEMs using InSAR pairs of Cosmo Sky-Med satellite. At the same time, photogrammetric DEMs were produced with unmanned aerial vehicles in selected pilot areas. The DEMs produced were evaluated in 4 land surface types, namely plain-bare, agricultural, urban and rugged area. In addition, by performing statistical analyzes such as RMSE, MAE, the accuracy of the produced DEMs compared to the DEMs produced with UAV was examined. The results showed that short and medium baseline data give more accurate results than long baseline InSAR pairs. Increasing the temporal baseline, increases the amount of error in the DEMs produced. Also, the effect of land surface types on the produced DEMs was revealed in the results of the study.

The Israeli-Palestinian conflict, which dates back many years, involves more than just territorial acquisition or military confrontation; it also has theological foundations in addition to political, socio-cultural, and psychological dynamics. Following Hamas's preemptive attacks on Israel in October 2023, the destruction caused by Israel’s airstrikes and systematically implemented policies particularly targeting Gaza has qualities that go beyond the typical damage a city suffers during wartime. The ceasefire declared on January 19, 2025, was violated by Israel with airstrikes on Gaza on the morning of March 18, which specifically targeted civilians. In the October 7 Hamas attack, approximately 1,200 people lost their lives, and 251 individuals were taken hostage by Hamas. As of today, more than 70,000 Palestinians mostly women and children and 850 Israeli soldiers have lost their lives in the ongoing conflict. In addition to the human toll, the destruction in Gaza is of a scale and severity that cannot be overlooked. Given the extent and nature of this destruction, the core objective of this study is to evaluate whether it can be interpreted through the concept of "urbicide," which is understood in the literature as the spatial/urban manifestation of genocide. While the attacks carried out by Israel in Gaza are generally regarded by the public as acts of genocide, from a legal standpoint it is crucial to substantiate such a characterization by demonstrating the nature of these attacks with the support of scientific evidence. To this end, the historical development of the Israeli-Palestinian conflict was reviewed, and the situation in Gaza was assessed using remote sensing and GIS techniques to determine whether it meets the commonly accepted characteristics of urbicide. Based on analyses conducted with remote sensing data provided by the United Nations Satellite Center (UNOSAT), it was found that between October 15, 2023, and February 25, 2025 a total of 11 analyzed time periods 68,154 general buildings, 207 places of worship, 225 educational institutions, and 58 hospitals were completely destroyed. In light of these findings, the study engages in an in depth discussion of whether the policies implemented by Israel in Gaza constitute an act of "urbicide."

Sayısal Yükseklik Modeli (SYM) verisi birçok mühendislik disiplini için arazi yükseklik bilgileri içermesinden dolayı oldukça önemlidir. Uzaktan algılamada mikrodalga görüntüler yardımı ile SYM üretiminde, stereoskopik ve interferometrik yöntemler kullanılmaktadır. Mikrodalga görüntülerin bu alanda kullanılmasındaki en büyük etken ise gece-gündüz alım yapabilmeleri ve kar, yağmur gibi hava koşulundan etkilenmemeleridir. Mikrodalga algılayıcı sistemler, yörünge etrafında alçalan veya yükselen yönde hareket ederek algılama yaparlar. Bu çalışmada TerraSAR-X verileri ile Erciyes Dağı’nda seçilen bir pilot bölgede SYM üretimi gerçekleştirilmiştir. Aynı zamanda SAR görüntülerinin uyumluluk verileri kullanılarak iki yörüngeye ait veriler füzyon edilmiştir. Alçalan, yükselen yörünge ve füzyon görüntüler için ayrı ayrı üretilen SYM’ler arazi ölçmelerinden elde edilen yükseklik bilgileri ile karşılaştırılmıştır. Karşılaştırma işlemlerinde istatistiksel analizler uygulanmıştır. İstatistiksel analizler sonucunda sırasıyla yükselen yörünge, alçalan yörünge ve füzyon korelasyon katsayısı değerleri 0.892, 0.894 ve 0.934 bulunmuştur. Elde edilen sonuçlar incelendiğinde, kullanılan füzyon yönteminin sonuçları pozitif yönde iyileştirdiği görülmüştür.