ABSTRACT:A dense digital surface model is one of the products generated by using UAV aerial survey data. Today more and more specialized software are supplied with modules for generating such kind of models. The procedure for dense digital model generation can b e completely or partly automated. Due to the lack of reliable criterion of accuracy estimation it is rather complicated to judge the generation validity of such models. One of such criterion can be mobile laser scanning data as a source for the detailed accu racy estimation of the dense digital surface model generation. These data may be also used to estimate the accuracy of digital orthophoto plans created by using UAV aerial survey data. The results of accuracy estimation for both kinds of products are presented in the paper.

Для аэрофотосъемочных работ с использованием беспилотных авиационных систем применяют цифровые неметрические камеры, как правило, профессионального или полупрофессионального классов. Для повышения точности определения элементов внутреннего ориентирования, а также уменьшения систематических искажений снимка, вызванных дисторсией объектива, выполняется фотограмметрическая калибровка. Калибровка съемочного оборудования выполняется на специальном полигоне или с помощью тест-объекта в лабораторных условиях. В Сибирском государственном университете геосистем и технологий функционирует пространственный тест-объект для калибровки съемочного оборудования. Тест-объект активно используется для научных, образовательных и производственных работ.

Presently, the current task is to automate the determination of the characteristics of forest areas ac-cording to remote sensing data. At the same time there is a large number of automated decryption algo-rithms that are actively used and provide an acceptable result in photointerpretation of medium and low spatial resolution multi-zone images. In processing of high and ultra-high resolution data, both new possibilities for determination of tax characteristics and certain difficulties related to efficiency reduction of algorithms using luminance characteristics arise. The aim of the study is to check the efficiency of the trees automated identification method and to determine their breed affiliation from the images ADS40 of the digital aerial camera. Proposed technique is based on a complex use of methods for controlled classification and identification of objects in the image by areal images. The result of the work done has shown, in the opinion of the authors, a significant efficiency of using the considered methodology on test data and the prospects for its further development.

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