Unmanned Aerial Vehicle for Remote Sensing Applications—A Review

TLDR

UAV sensors are widely used in agriculture, forestry, mining, and other fields, yet remote‑sensing data processing remains largely ad‑hoc, and the high spatial resolution and 3D capabilities of UAV imagery introduce challenges such as unwanted object classes and the need for advanced geometric and spectral analysis. This paper critically reviews remote‑sensing tasks that rely on UAV data and their derived products, including raw perspective images, digital surface models, and orthophotos. The review focuses on solutions that address the new aspects of UAV data—ultra‑high resolution, coherent geometric and spectral information, and simultaneous multi‑sensor fusion. We summarize existing UAV‑based remote‑sensing applications in agriculture, environment, urban, and hazard assessment, discuss their practical potentials, and outline future research directions.

Abstract

The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in almost every application (e.g., agriculture, forestry, and mining) that needs observed information from the top or oblique views. While they intend to be a general remote sensing (RS) tool, the relevant RS data processing and analysis methods are still largely ad-hoc to applications. Although the obvious advantages of UAV data are their high spatial resolution and flexibility in acquisition and sensor integration, there is in general a lack of systematic analysis on how these characteristics alter solutions for typical RS tasks such as land-cover classification, change detection, and thematic mapping. For instance, the ultra-high-resolution data (less than 10 cm of Ground Sampling Distance (GSD)) bring more unwanted classes of objects (e.g., pedestrian and cars) in land-cover classification; the often available 3D data generated from photogrammetric images call for more advanced techniques for geometric and spectral analysis. In this paper, we perform a critical review on RS tasks that involve UAV data and their derived products as their main sources including raw perspective images, digital surface models, and orthophotos. In particular, we focus on solutions that address the “new” aspects of the UAV data including (1) ultra-high resolution; (2) availability of coherent geometric and spectral data; and (3) capability of simultaneously using multi-sensor data for fusion. Based on these solutions, we provide a brief summary of existing examples of UAV-based RS in agricultural, environmental, urban, and hazards assessment applications, etc., and by discussing their practical potentials, we share our views in their future research directions and draw conclusive remarks.