Continuous technological growth and the corresponding environmental implications are triggering the enhancement of advanced environmental monitoring solutions, such as remote sensing. In this paper, we propose a new method for the spatial point patterns generation by classifying remote sensing images using convolutional neural network. To increase the accuracy, the training samples are extended by the suggested data augmentation scheme based on the similarities of images within the same part of the landscape for a limited observation time. The image patches are classified in accordance with the labels of previously classified images of the manually prepared training and test samples. This approach has improved the accuracy of image classification by 7% compared to current best practices of data augmentation. A set of image patch centers of a particular class is considered as a random point configuration, while the class labels are used as marks for every point. A marked point pattern is regarded as a combination of several subpoint patterns with the same qualitative marks. We analyze the bivariate point pattern to identify the relationships between points of different types using the features of a marked random point pattern.
Today, the geographical interpretation of thermal satellite images, by the number of processing methods and applications, remains one of the least deeply studied areas. Geographic objects are characterized by different thermal and radiation properties. Therefore, they react differently to changes in the intensity of solar radiation, which is recorded in thermal images by differences in image brightness. What this article deals with is the usage of thermal satellite images from TIRS system of Landsat 8 in the monitoring of natural objects. Thermal images are a special source of geographical information that reflects the actual thermal radiation of objects on the earth's surface. It’s been defined that the thermal field of natural territories characterizes by high seasonal spatial-temporal variability. So, seasonal dynamics of the intensity of thermal radiation of natural have characteristic differences. It’s defined that winter characterizes by weak contrasts in the intensity of thermal radiation. Water bodies are best identified during this period. For spring, the increased intensity is observed for open woodless areas, in summer for agricultural lands, and in autumn the highest level of thermal radiation intensity is observed within open ground areas. Also, it was determined that the seasonal variability of thermal radiation intensity of different objects shows regularities related to the features of these objects. In other words, it can be their interpretation feature. The structure of the thermal field of protected areas was defined according to the unsupervised classification of a multitemporal thermal image using the IsoCluster algorithm. The accuracy of the performed classification was proved by the full compatibility of classified elements of thermal structure with natural objects.
Природоохоронні території, як об'єкти природно-заповідного фонду, відіграють одну із ключових ролей у формуванні навколишнього середовища, збереженні стійкості екосистеми та забезпеченні екобезпеки території [1-3], підтримуючи саморегуляцію екологічних процесів, збереження генетичного різноманіття і екологічну стабільність прилеглих територій. Однак у даний час практично для кожного з об'єктів природно-заповідного фонду існує низка проблем, які перешкоджають їх стабільному розвитку. Серед них виділяють активізацію впливу природно-кліматичних та антропотехногенних чинників (ПКЧ/АТЧ), яка зумовлює інтенсифікацію стресових навантажень на природні комплекси при практичній відсутності технологій адаптивного реагування на зміни, зумовлені дією цих чинників, що негативно позначається на сталому розвитку і рівні екобезпеки території [3, 4].
The question of ecological safety level decreasing within the West Polesie protected territories that concern changes in hydrological conditions driven by intensification of the influence of climate changes and anthropogenic loads, has been considered in the paper. Statistical analysis and field instrumental measurements were used for estimation the influence of regional climate on hydrological conditions within the territory. According to bathymetry surveys and geoinformation analysis results, the siltation degree of the deepest hollows of Svitiaz Lake was estimated. Hypotheses concerning the ways of underground water supply as well as the reasons for water level decreasing in the Lake were formulated, taking into account climatic conditions within the West Polesie territory: the lake is filled by infiltration of water from aquifers through permeable rocks; water infiltration occurs not only within the fault of Lake Svityaz, but also in its flatter part; significant intensity of trajectories (water streams) within the fault allows us to conclude that the main filling of the lake occurs within this part due to the opening of permeable rocks, which contributes to a more intensive release of groundwater.
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