High-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...

To successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...

Floods threaten urban infrastructure, especially in residential neighborhoods and fast-growing regions. Flood hydrodynamic modeling helps identify flood-prone locations and improve mitigation plans' resilience. Urban floods pose special issues due to changing land cover and a lack of raw data. Using a GIS-based modeling interface, input files for the hydrodynamic model were developed. The physical basin's properties were identified...

The lack of countries’ statistical income data, comparable across countries and years, seems to be the main reason of controversial conjectures concerning global inequality and its evolution over time. In the databases, which purport to collect income data on a worldwide scale, only some summary statistics (quantile income shares, means, Gini indices) are presented. Therefore, the development of efficient methods of extracting...

Cities are hubs of innovation and wealth creation, and magnets for an increasing urban population. Cities also face unprecedented challenges in terms of food, water and energy scarcity, and governance and management. Urban environmental issues are no longer problems for experts to address but have become issues of public debate, in which knowledge from multiple sectors is needed to support inclusive governance approaches. Consequently,...