In environmental management, it can be difficult to understand what is happening throughout a given landscape from a boots-on-the-ground perspective. Are invasive species encroaching on native plant life? Are fenceline emissions posing a hazard? Is soil drier than usual? The human eye can only capture so much detail at any one moment and, when compared with today's technology, our eyes may not be the best tool for the job.
Organizations are increasingly realizing the benefits of remote sensing in environmental management – but generally, these benefits are reserved for those who understand available remote sensing options and approaches that will support their project goals. In this article, we provide a foundational overview of remote sensing and offer a sensor + application matrix to help guide project decisions related to remote sensing.
What is remote sensing?
The official definition of remote sensing from the United States Geological Survey (USGS) is “the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance (typically from satellite or aircraft).” In practice, remote sensing involves attaching a sensor or camera to a piece of equipment (i.e. platform) to capture information about a landscape.
Who uses remote sensing?
General fields of study that use and benefit from remote sensing applications include geology, hydrology, engineering, marine sciences/oceanography, ecology, forestry, and agriculture – to name a few. Ecology and agricultural applications have seen tremendous growth as organizations are able to use spectral analysis to measure the reflectance properties of vegetation, determining a range of useful information about the overall vegetation health or distinguishing different types of plant species using vegetation indices. As more remote sensing options become available, remote sensing applications can be expected to grow in tandem.
Remote sensing options
Understanding available remote sensing options can be the most challenging aspect of incorporating the technology into a project. There are many combinations of project applications, sensors, and platforms, making it worthwhile to consider which combination offers outcomes aligned with goals.
Key remote sensing application categories
- Surveying & Mapping
- Vegetation/Exploration Surveys
- Inspection & Asset Management
- Water Resources
- Specialized Services – Media Sampling & Geophysics
Types of remote sensing technologies
- Visual sensors include basic high-resolution cameras for video recordings and/or photographs. Photogrammetric analysis can be performed if an adequate number of photographs are collected with sufficient overlap that can create a point cloud and digital elevation model of the top surface, whether that is the ground, a structure, or vegetation.
- Spectral analysis, either multispectral or hyperspectral, analyzes reflective spectral data directly – or, data can be incorporated into one of many indices that can provide additional information. For example, vegetative indices provide insights into a plant’s water content, cell structure, stress/health condition, and biochemical content. Spectral signatures of different objects are considered similar to “spectral fingerprints” that can identify distinctions (e.g. invasive species when analyzing plant species).
- Multispectral analysis divides a portion of the spectral wave into several (4-10) distinct bands yielding data for subsequent analyses.
- Hyperspectral analysis divides a portion of the spectral wave into hundreds to thousands of distinct bands, in some cases producing a near continuous dataset (10-100 times more data than multispectral analysis).
- Light detection and ranging (LiDAR) measures the reflective signal from a laser off of a surface and is commonly used to measure topographic elevations of different surfaces. Basic LiDAR can penetrate vegetative cover to detect the underlying ground surface elevation and even shallow bathymetry, whereas specialized LiDAR can penetrate tens of feet into a freshwater feature. These data generate a point cloud that can create a digital elevation model for the surface of interest.
- Thermal infrared (TIR) typically measures the mid-wave and long-wave infrared portions of the spectral wave that are outside the capabilities of human vision. TIR can measure the temperature of a targeted surface. TIR sensors have multiple engineering and environmental purposes, such as energy efficiency, spring/dam leak detection, crop water use (evapotranspiration), and wildlife location.
Remote sensing platforms
Common remote sensing platforms include Unmanned Aerial Systems (UAS/Drones), manned aircraft, and satellites (including microsatellites). A few of the major differences between these platforms are the pixel scale resolution of the sensors (UAS has the smallest scale and highest resolution), schedule flexibility and temporal resolution, image obstructions/interference (e.g., cloud cover or wildfire smoke), and daily area coverage capabilities. In some cases, a project may benefit from performing a screening level survey at a coarse resolution to identify targeted locations for more detailed, higher resolution surveys. Based on recent improvements in and deployments of numerous microsatellite constellations, the cost for routine satellite imagery is becoming more competitive. Moreover, UASs are also increasingly economical and able to cover greater areas.
Key questions in successfully incorporating remote sensing into your project
Answering these foundational questions can help guide your remote sensing project decisions.
- What types of data do I need to collect (physical, spectral, other)?
- What final information do I want to be able to report?
- How large of an area do I need to cover?
- What is the smallest object (or area) of interest for data collection?
- What time(s) of year will provide the best data?
- Will any distinguishing traits vary over time or across locations?
- What level of accuracy is acceptable/required?
Key steps to include in your data collection plan and report
- Design Remote Sensing Data Collection Survey – coordinate with the flight crew and data analysts
- Pre-Survey Field Work and Available GIS Data – if data is not available, it will need to be obtained
- Remote Sensing Data Acquisition – select preferred platform, follow safety/Federal Aviation Administration (FAA) protocols, follow local permitting requirements
- Data Processing and Analysis – gain support from Ph.D. scientists, statisticians, engineers, and/or artificial intelligence (AI)
- Accuracy Assessment – part of data validation and an effective data quality objectives (DQO) program
- Final Report and Data Imagery Product
Sensor and application matrix: making sense of it all
Click here to download a detailed version of the below matrix, which displays additional applications.
Interested in more?
Trihydro’s remote sensing subject matter experts help organizations across multiple industries enjoy the project benefits that come with remote sensing data collection and object classification. Contact us to discuss your site-specific questions.