Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

By Helge Aasen, Eija Honkavaara, Arko Lucieer, Pablo J. Zarco-Tejada. Remote Sensing, 2018

557 citations recorded by the source corpus.

In the last 10 years, development in robotics, computer vision, and sensor technology has provided new spectral remote sensing tools to capture unprecedented ultra-high spatial and high spectral resolution with unmanned aerial vehicles (UAVs). This development has led to a revolution in geospatial data collection in which not only few specialist data providers collect and deliver remotely sensed data, but a whole diverse community is potentially able to gather geospatial data that fit their needs. However, the diversification of sensing systems and user applications challenges the common application of good practice procedures that ensure the quality of the data. This challenge can only be met by establishing and communicating common procedures that have had demonstrated success in scientific experiments and operational demonstrations. In this review, we evaluate the state-of-the-art methods in UAV spectral remote sensing and discuss sensor technology, measurement procedures, geometric processing, and radiometric calibration based on the literature and more than a decade of experimentation. We follow the 'journey' of the reflected energy from the particle in the environment to its representation as a pixel in a 2D or 2.5D map, or 3D spectral point cloud. Additionally, we reflect on the current revolution in remote sensing, and identify trends, potential opportunities, and limitations.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/c5e088609eb7d32e2a6323f5ce258faec33c3bc5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Zhenhai Li
2. Tao Yang
3. Pablo J. Zarco-Tejada
4. Bo Ming
5. Mary Bernadette Stuart
6. Rajeev K. Varshney
7. Chenwei Nie
8. Urs Schmidhalter

In Environmental Engineering

1. Tao Yang
2. Pablo J. Zarco-Tejada
3. Bo Ming
4. Mary Bernadette Stuart
5. Rajeev K. Varshney
6. Chenwei Nie
7. Urs Schmidhalter
8. Jon Raffe Willmott

In Global and Planetary Change

1. Pablo J. Zarco-Tejada
2. Matthew P Reynolds

Citations in the corpus

• High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms (2020, background): “Compared with their multispectral counterparts, hyperspectral cameras have a higher spectral resolution, with continuous or discrete spectral bands in the visible and infrared spectral regions [17], [264].”
• Hyperspectral Imaging in Environmental Monitoring: A Review of Recent Developments and Technological Advances in Compact Field Deployable Systems (2019, methodology): “Typically, sensors are characterized by the arrangement and/or the number of spectral bands involved in the instrumental architecture [10,16], as well as the applied image capture method.”
• Crop Phenomics and High-throughput Phenotyping: Past Decades, Current Challenges and Future Perspectives. (2020, unknown): “There are some reviews available on UAV spectral remote sensing technologies (Aasen et al., 2018; Maes and Steppe, 2019) and UAV-based hyperspectral data processing and applications in agriculture (Adão et al.”