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Городские территории постоянно расширяются на фоне ускоряющейся урбанизации, и их правильное выявление может оказаться полезным в широком спектре приложений в градостроительстве и экологических исследованиях. Определение городских границ представляет значительный исследовательский интерес. Возможность отслеживать рост и изменения облегчается простотой и точностью определения границ. В этом исследовании предлагается метод данных Sentinel-1 с открытым исходным кодом для обнаружения и определения границ между городом и деревней. Предварительная обработка изображения и матрица совпадений в оттенках серого были созданы в SNAP с использованием данных SAR Sentinel-1a для Кабула, Афганистан, а также сочетания текстуры и классификаций k-mean. К продуктам GLCM был применен классификатор k-mean с 3 категориями, а полученное изображение было экспортировано в формате GeoTIFF и импортировано в ArcGIS Pro. После постобработки в ArcGIS Pro была извлечена застроенная городская территория Кабула. Наконец, сгенерированная застроенная территория границы города Кабул была наложена на изображение Sentinel-2A в естественных цветах для оценки эффективности предложенного метода.

Urban areas are continuously expanding, against the background of accelerating urbaniza-tion, while their correct detection might be useful in a wide range of applications in urban plan-ning and environmental studies. Identifying urban boundaries is an area of considerable research interest. The ability to monitor growth and change is facilitated by the ease and accuracy of boundary delineation. This research proposes an open-source sentinel-1 data method for detecting and delineating the urban-rural boundary. The image pre-processing and grey-level co-occurrence matrix were created in SNAP using Sentinel-1a SAR data for Kabul, Afghanistan, and a combi-nation of texture and K-means classifications. A 3-category K-Means classifier was applied to the GLCM products, and the resulting image was exported as a GeoTIFF and imported into ArcGIS Pro, After the post-processing in ArcGIS Pro, the built-up urban area of Kabul was extracted. Fi-nally, the generated built-up area of the Kabul city boundary was overlaid onto the Sentinel-2A natural color image to assess the effectiveness of the proposed method.

аспирант, Московский государственный университет геодезии и картографии

доктор географических наук, профессор, заведующий кафедрой географии Московского государственного университета геодезии и картографии, 105064, Москва, Россия

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