Jenerowicz M., Wawrzaszek A., Drzewiecki W., Krupiński M., Aleksandrowicz S. (2019), Multifractality in Humanitarian Applications: A Case Study of Internally Displaced Persons/Refugee Camps, IEEE Journal of Selected Topics in Applied Earth Observations and Remote

The coordination of humanitarian relief is always difficult due to a lack of data required for management and planning. Remote sensing imagery can be an important source of information about the in-situ situation, notably,

Woźniak E., Aleksandrowicz S. (2019), Self-Adjusting Thresholding for Burnt Area Detection Based on Optical Images, Remote Sensing

Mapping of regional fires would make it possible to analyse their environmental, social and economic impact, as well as to develop better fire management systems. However, automatic mapping of burnt areas has proved to

Krupiński M., Wawrzaszek A., Drzewiecki W., Aleksandrowicz S., Jenerowicz M. (2019), Multifractal Parameters for Spectral Profile Description, IGARSS 2019

Hyperspectral data provides huge amount of detailed information about spectral properties of the objects. In the era of fast data volume enlargement, it is necessary to develop methods and algorithms which are capable for

Aleksandrowicz S., Wawrzaszek A., Jenerowicz M., Drzewiecki W. and Krupiński M. (2019), Local Multifractal Description of Bi-Temporal VHR Images, 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), Shanghai, China, 2019, pp. 1-3. doi: 10.1109/Multi-Temp.2019.8866963

In this work we apply local multifractal formalism to spectral bands of bi-temporal Very High Resolution (VHR) images. Analysis of the local multifractal description and its changes between images acquired in two points in

Jenerowicz M., Wawrzaszek A., Krupiński M., Drzewiecki W., Aleksandrowicz S. (2019), Aplicability of Multifractal Features as Descriptors of the Complex Terrain Situation in IDP/Refugee Camps, IGARSS 2019

This paper presents the preliminary results of the complex terrain situation description with the utility of multifractal features. The analysis was done for two samples of Internally Displaced Person/Refugee camps (Ifo, Daadab in Kenya/Al

Gromny E., Lewiński S., Rybicki M., Malinowski R., Krupiński M., Nowakowski A., and Jenerowicz M. (2019), Creation of training dataset for Sentinel-2 land cover classification, Proc. SPIE

Supervised classification of satellite images is performed based on utilization of reference training data. Therefore, the availability and quality of reference data highly influences the results and the course of the entire classification process.

Jenerowicz M., Wawrzaszek A., Krupiński M., Aleksandrowicz S., and Drzewiecki W. (2019), Comparison of mathematical morphology with the local multifractal description applied to the image samples processing, Proc. SPIE

This paper presents the results of a preliminary comparison of two methods which are based on the mathematical approach, Mathematical Morphology and the Local Multifractal Description. Both methods are characterized by the need for

Gromny E., Lewiński S., Rybicki M., Malinowski R., Krupiński M., and Nowakowski A. (2019), Post-processing tools for land cover classification of Sentinel-2, Proc. SPIE

Post-processing is the last and often optional stage of land cover (LC) classification from satellite images. In the traditional approach, it is usually applied to remove the effect of “salt and pepper” from the

Krupiński M., Lewiński S., Malinowski R. (2019), One class SVM for building detection on Sentinel-2 images, Proc. SPIE

Human population has reached 7.7 billion in year 2019. According to the forecasts of world population projections it may reach 8 billion in 2023. This growth indicates inter alia increased demand for housing. Monitoring

Derek M., Woźniak E., Kulczyk S. (2019), Clustering nature-based tourists by activity. Social, economic and spatial dimensions, Tourism Management

This study develops a typology of tourists visiting a nature-based destination as a function of outdoor activities. It then identifies social, economic and spatial differences between them. A cluster analysis is applied to survey