Summary Reader Response Draft #2

In the article “How Artificial Intelligence, Robots Enhance Forest Sustainability in Finland”, McQueen (2019) showcased Finnish Forest Centre’s implementation of advanced technologies in enhancing forest sustainability. 

Finland is covered in forests to the tune of 75%,, and data can be acquired using aerial mapping technology in conjunction with light detection and ranging technology. With the advent of artificial intelligence, forest management is being simplified, which further maximises the trees' sequestration of carbon, while filling up jobs in forestry.

McQueen describes how the Finns adopted environmental regulations to balance economic progress and forest preservation. The regulations prohibit practices like draining bogs and herbicide use. Under this legislation, landowners are encouraged to be active in the care of their property while the center provides recommendations.

Additionally, one of the benefits of having an intelligence assistant provides forest owners with an online marketplace to engage with professionals, while utilizing data in the geographic information system where it is gathered by laser scanning, aerial photography, sample plot measurements, and site visits.

In conclusion, McQueen concluded that artificial intelligence can assist in obtaining more accurate data. The combined information can enable more precise measurements of forests and a better forecast of forest inventory. Furthermore, enhanced logistics and supply networks are included.

McQueen has shown that society can influence changes in forestry legislation and find new strategies to maximize tree carbon sequestration.

With the advent of unique and advanced artificial intelligence, forest management is being simplified. The implementation of artificial intelligence integrated with algorithms has minimized the amount of fieldwork time, whilst obtaining accurate results. Artificial intelligence has proven useful in solving multiple challenges in forest carbon monitoring, measurement, reporting, and verification, such as pest infestations, forest degradation, deforestation, and forest restoration. For example, the same measures that would require in-person measurement are being extracted using machine learning algorithms.

In another excerpt, Chen (2020) outlines how artificial intelligence incorporates algorithms are employed to automate forestry. The robot whirl through fields extracting data about crops, counting fruit on trees, and supplying accurate statistics to growers.

According to Bakker (2019) In addition to assisting with measurements, artificial intelligence is employed to descry deforestation at an early stage, for example, this insight can be used to facilitate prevention or curtail the outbreak of infectious trees. 

Furthermore, in addition to utilizing artificial intelligence algorithms tailored to trees and vegetation. AI provides real-time data regarding growth risks based on species, growth, weather, and climate, allowing us to alter our management strategies and improve carbon sequestration in forests. According to Pachama (2021) by harnessing satellite imagery and artificial intelligence to measure and monitor carbon capture in forests.  The implementation of AI not only streamlines the process, saves time, and reduces manual efforts, but it also reduces the cost of the procedure while yielding precise results. The reduction in the cost of measuring a forest’s carbon storage allows a greater share of the money spent on carbon offsets to reach landowners. People and businesses who buy carbon offsets can be more confident that their money is being spent on effective carbon removal technologies as the precision of those data improves.

While technological advancements have proven to be helpful in many fields such as forestry, there still exists a slim possibility that the robots could malfunction, despite the high success rate of these advancements. Research indicates that there might be various factors contributing to artificial intelligence malfunctioning. According to Taipei times(2021), one reason might be a technical error in the control system.

Ultimately, I agree that the adoption of AI-technology deployment is critical towards sustainability and the process of forestry simplification management. Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as lidar, aerial technology, and robotics, simplifies forest management, whilst obtaining accurate data. AI can also help by providing real-time data about growth risks based on species, growth, weather, and climate. 

In my opinion, I believe through the deployment of artificial intelligence, forestry maintenance work will be executed more effectively, swiftly, and efficiently.



Citations:

Author, G. (2019, June 11). Detecting forest threats with Artificial Intelligence. AZO Space of Innovation. Retrieved February 13, 2022, from                                                                                    https://space-of-innovation.com/detecting-forest-threats-with-ai/ 


Lopez, I. (2020, October 13). Treeswift's autonomous robots take flight to save forests. Phys.org. Retrieved February 13, 2022, from                                                                   https://phys.org/news/2020-10-treeswift-autonomous-robots-flight-forests.html#:~:text=Chen%20founded%20Treeswift%20as%20a,%2C%20inventory%2C%20and%20map%20timberland. 


Pachama. (2021, March 11). Pachama recognized as the world’s most innovative AI company of 2021 in fast company’s annual list. GlobeNewswire News Room.          https://www.globenewswire.com/news-release/2021/03/11/2191352/0/en/Pachama-Recognized-as-the-World-s-Most-Innovative-AI-Company-of-2021-in-Fast-Company-s-Annual-List.html


Parisa, Z., & Nova, M. (2021, June 24). This AI can see the forest and the trees.                               IEEE Spectrum. Retrieved February 13, 2022, from                                               https://spectrum.ieee.org/this-ai-can-see-the-forest-and-the-trees 


Taipei Times. (2021, February 19).Military drone crashes in Park; no injuries reported.             Retrieved February 13, 2022, from                                                 https://www.taipeitimes.com/News/taiwan/archives/2021/02/20/2003752557 




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