Arthropods are the most diverse group of animals on the planet. In recent decades, however, the declining of arthropods is becoming more widespread, emphasizing the need for conservation actions aimed at preserving these organisms. Though, in order to design meaningful conservation strategies, consistent information on the species distribution is required. Overall, however, it is complicated to acquire such information purely on the basis of field assessments. Consequently, the use of remote sensing methods in species distribution studies is gaining more popularity recently. However, the capability of remote sensing techniques to map the distribution of arthropods is rather poorly studied. The main aim of the present research is to study the arthropod distribution in a heterogeneous mire habitat. Overall, the study consisted of the following steps: (1) the collection of data in the field; (2) the calculation of habitat preferences for each arthropod species; (3) the conversion of arthropod quantity data from the point-based representation to the surface-based one; (4) the classification of the mire vegetation with the machine learning algorithm using a very high spatial resolution (25 cm) imagery; (5) combining all the previous data together and estimating the arthropod spatial distribution within the studied mire habitat. The results showed that the arthropod diversity was rather high within the Ap & scaron;uciems mire. Also, it was concluded that there were no distinct "hotspots" of arthropod species richness in the mire territory, and different arthropod species had rather different spatial distributions within the Ap & scaron;uciems mire. We concluded from this study, that when combined with in-situ sampling, remote sensing is a powerful tool for utilization in arthropod distribution studies in heterogeneous mire habitats.
