By John Oncea, Editor
The fusion of hyperspectral imaging and environmental monitoring offers comprehensive insights into our environment, enabling better decision-making for sustainable practices and safeguarding the planet's health.
You can’t possibly get more early-1980s than this fantastic Reese’s Peanut Butter Cups commercial. The good news is I never owned a shirt like the guy is wearing. The bad news is I was shot down dozens of times by girls dressed like the one in the commercial.
Anyway, this is my “go-to” thought anytime two disparate things are being combined. Like:
Hey! You got your hyperspectral imaging in my environmental monitoring!
You got your environmental monitoring in my hyperspectral imaging!
(Takes a look at what the two can do when used together)
Two great technologies that go great together!
Now that you know more than you need to know about ‘80s style, my pathetic dating history, and Reese’s Peanut Butter Cups, let’s look at how hyperspectral imaging and environmental monitoring are being used together.
Hyperspectral Imaging – The Chocolate Of Our Story
Hyperspectral imaging (HSI) is a technique that analyzes a wide spectrum of light instead of just assigning primary colors to each pixel, according to ScienceDirect.
HSI technology breaks down the light that falls on each pixel of an image into many different spectral bands. This provides more detailed information about the imaged object. Originally developed for military purposes, the algorithms and image-processing methodologies of HSI were used to identify targets and objects within complex backgrounds. In recent years, HSI has found a range of civil applications, especially in satellite technology.
HSI technology can detect the distinctive color signature of an object. Unlike other optical technologies that can only recognize a single color, HSI can distinguish the complete color spectrum in each pixel. As a result, it provides both spatial images and spectral information.
And Here’s The Peanut Butter, Environmental Monitoring
Environmental monitoring, according to Optica, “Involves those tools and processing techniques used to characterize the environment, including DIAL and LiDAR, hyperspectral monitoring, detection, processing and characterization, surveying applications, atmospheric propagation, pollution monitoring, and remote imaging. Also included in this area is remote sensing for military and commercial applications, such as land management, target detection, and disaster monitoring.”
Environmental monitoring uses optics to monitor the environment from point sources to global scales. This is accomplished through techniques such as drone surveys and in-situ soil and water analysis using sensors measuring temperature, humidity, air quality, noise, and more.
Let’s Bite Into The Peanut Buttery/Chocolate Goodness
HSI can be used for environmental monitoring to detect changes in land use and vegetation health, evaluate air and water quality, pinpoint potential pollution outbreaks, and more. “Data obtained from environmental monitoring can be used to draw trends for future complications,” notes Perfect Pollucon Services. It also helps identify natural calamities before time, allowing time for precautionary measures to be taken to soften the impact.
Remote sensing, which includes HSI, plays a vital role in environmental monitoring and analysis, writes Frontiers in Environmental Science. “Among modern remote sensing techniques, HSI is a prominent tool in environmental science application areas.
HIS “can acquire spectrally rich information from the scene that helps identify different materials effectively. Providing precise, high-resolution datasets of hyperspectral images along with data fusion strategies can fill the gap between sparse field observations and coarse resolution spaceborne images.”
It also facilitates real-time analysis and decision-making in a wide range of environmental mapping and monitoring contexts. It allows for optimal band selection, classification, segmentation, spectral unmixing, target detection, and anomaly and change detection, which are common tasks in HIS applications. The combination of deep learning models and large-scale hyperspectral images is expected to yield significant advances in Earth observation.
“With the rapid development of imaging sensors, hyperspectral data has been successfully applied to a plethora of applications, e.g., environmental monitoring, precision agriculture, and climate change,” Frontiers in Environmental Science writes. “Recently, different airborne and spaceborne hyperspectral sensors have been developed such as already launched or planned to launch PRISMA, EnMAP, HyspIRI, Hyperion (EO-1), and Copernicus Hyperspectral Imaging Mission for The Environment (CHIME). The key goal of this Research Topic is to advance sophisticated HSI methodologies to ensure sustainable development of the economy and society.”
To achieve success in applications such as ecological parameter analysis, it is important to address some major challenges. These challenges include developing robust and low-cost hyperspectral sensor technology, integrating and fusing various remote sensing datasets like hyperspectral and microwave remote sensing, and managing uncertainty in ecological parameters. To overcome these challenges, it is necessary to conduct studies on processing hyperspectral data using multivariate statistics, as well as artificial intelligence techniques like machine learning and deep learning.
Environmental monitoring plays a pivotal role in ensuring compliance, conservation, and sustainable management of natural resources. By utilizing the latest information systems, researchers can better assess the impact of human activities on ecosystems, air, water, and soil quality. This allows them to identify potential risks, develop mitigation strategies, and ensure that industries and communities adhere to environmental regulations. In the long run, this will prove to be crucial in safeguarding the planet's health and promoting responsible practices for a more sustainable future.