# Finding a Landing Site on an Urban Area: A Multi-Resolution Probabilistic Approach Source: [Finding a Landing Site on an Urban Area: A Multi-Resolution Probabilistic Approach]() Collection index: [llms.txt]() Data updated: 2025-10-26T00:53:04.613Z Authors: Barak Pinkovich, Boaz Matalon, Ehud Rivlin, Hector Rotstein Published: 2022-04-26T21:02:00.000Z ## Abstract This paper considers the problem of finding a landing spot for a drone in a dense urban environment. The conflicting requirement of fast exploration and high resolution is solved using a multi-resolution approach, by which visual information is collected by the drone at decreasing altitudes so that spatial resolution of the acquired images increases monotonically. A probability distribution is used to capture the uncertainty of the decision process for each terrain patch. The distributions are updated as information from different altitudes is collected. When the confidence level for one of the patches becomes larger than a pre-specified threshold, suitability for landing is declared. One of the main building blocks of the approach is a semantic segmentation algorithm that attaches probabilities to each pixel of a single view. The decision algorithm combines these probabilities with a priori data and previous measurements to obtain the best estimates. Feasibility is illustrated by presenting a number of examples generated by a realistic closed-loop simulator. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()