DJI Terra for McGill University's Applied Remote Sensing Lab

Learn how McGill University's ARSL researches critical peatlands and other ecosystems using DJI Terra's advanced technology

By DJI Enterprise DJI Enterprise
September 3, 2024

McGill University, located in Montreal, Canada, is one of the country's top universities. It is also home to one of the country's top Applied Remote Sensing Labs (ARSL), standing at the forefront of innovative remote sensing research. Led by Dr. Margaret Kalacska, the lab works with satellite imagery, LiDAR technology, and multispectral and thermal imaging to analyze and interpret complex environmental data of aquatic ecosystems, natural hazards, and infrastructure. DJI Terra, a comprehensive 3D model mapping software, is used by ARSL to significantly enhance their capabilities in collecting and processing remote sensing data.

McGill University's Applied Remote Sensing Lab

ARSL's research spans several core areas, including LiDAR (Light Detection and Ranging), photogrammetry, and multispectral analysis. These methodologies allow for precise topographical mapping, detailed image capturing, and the study of various spectral bands to assess environmental conditions and changes across natural environments worldwide.

Dr. Margaret Kalacska's Contribution

Dr. Margaret Kalacska, an Associate Professor in the Department of Geography at McGill University, is a prominent figure in the field of remote sensing. She has made significant contributions to developing remote sensing applications in environmental science. Her work, which focuses on addressing ecological and environmental challenges, has been instrumental in establishing ARSL as a leader in applying advanced technologies. Dr. Kalacska's expertise and leadership are key factors to the lab's success.

 

Data Collection with DJI Terra

Dr. Margaret Kalacska and colleague reviewing data with DJI Terra

Researching the Mer Bleue Peatland in Canada

The Mer Bleue Peatland, an 8,000-year-old bog located in Eastern Ontario, Canada, is one of the most significant peatlands in the world. Recognized for its ecological and geological features, this site is paramount to the Canadian government and the global scientific community. It is a critical component of the Fluxnet-Canada Research Network, which focuses on understanding the effects of climate and environmental disturbances on carbon cycling in forest and peatland ecosystems. The importance of the Mer Bleue Peatland in global carbon cycling cannot be overstated, making it a crucial area of study for the scientific community.

 

mer bleue peatland

Mer Bleue Peatland in Canada

 

The unique biological and ecological dynamics of the Mer Bleue Peatland necessitate ongoing research to monitor how the ecosystem responds to changes in temperature, precipitation, and other environmental factors. However, the waterlogged and moisture-rich nature of this environment poses considerable challenges for ecological scientists. Traditional data collection methods often struggle to provide reliable readings in such conditions, underscoring the need for advanced technologies.

Dr. Margaret Kalacska and her team at McGill University's Applied Remote Sensing Lab (ARSL) employ advanced drone technology to overcome these challenges. Using DJI drones equipped with photogrammetry and LiDAR sensors, the team captures extensive datasets from the Mer Bleue Peatland. These datasets are then processed using DJI Terra, transforming into detailed point clouds, orthomosaics, and topographical maps. These maps reveal critical and nuanced differences in the terrain, offering valuable insights into the peatland's microtopography.

 

M350 RTK with Zenmuse P1

Setting up DJI M350 RTK with Zenmuse P1 to fly over Mer Bleue Peatland

 

The lab's work with DJI Terra continues beyond 3D modeling. DJI Terra is also pivotal in understanding the distribution of water beneath the peatland's surface—a factor closely tied to its function as a carbon sink. The Mer Bleue Peatland, approximately 7 meters deep at its center, with water levels that vary between 10 to 50 centimeters from the surface, depending on the time of year, plays a crucial role in carbon sequestration. By analyzing these details, researchers can better understand the peatland's role in carbon sequestration or, at times, carbon release, highlighting its ecological importance.

Furthermore, the ARSL collaborates with the German hyperspectral satellite EnMAP to validate satellite imagery within this unique ecosystem. The high spatial detail surface elevation models generated using DJI Terra serve as baseline maps for correcting hyperspectral images captured by drones, airborne sensors, and satellites. This collaboration is crucial for ensuring the accuracy of satellite data and deepening the understanding of the Mer Bleue Peatland's ecological processes.

Through the combined use of DJI drones, Terra software, and collaboration with international satellite missions, McGill University's Applied Remote Sensing Lab continues to advance the study of the Mer Bleue Peatland. This research contributes to the conservation of this vital ecosystem. It enhances our broader understanding of peatland environments and their critical role in global carbon cycling.

 

Field data collection

Dr. Margaret Kalacska and Dr. Pablo Arroyo-Mora at the Mer Bleue Peatland

Mapping Volcanic Craters in Costa Rica

Costa Rica, renowned for its diverse landscape, is home to numerous volcanoes. Poas Volcano stands out as one of the largest and most active. Located just over 20 miles from the capital city of San Jose, Poas has erupted 40 times in the past two centuries, most recently in September 2019. Due to its proximity to a major urban center, continuous monitoring of the volcano's dynamic crater is crucial for public safety and scientific research.

 

Poas Volcano

Poas Volcano in Costa Rica

 

The ARSL has conducted an in-depth study of Poas Volcano, utilizing advanced drone technology to collect vital data. The study involved two primary data collection efforts, each addressing different aspects of volcanic monitoring.

First, thermal imagery was captured using a DJI Mavic 2 Enterprise Advanced. This data focused on identifying temperature variations across the volcanic crater, allowing scientists to distinguish between temperature changes caused by volcanic activity and those influenced by external factors like solar heating. Understanding these temperature contrasts is essential to accurately assess the volcano's activity levels and potential hazards.

The second data set involved the use of photogrammetry, which was processed with DJI Terra to create a high-resolution 3D model of the crater. This detailed representation enables scientists to detect even the most minor changes—down to the centimeter level—before and after volcanic eruptions. Monitoring such fine-scale changes is vital for predicting future eruptions and mitigating the associated risks.

One of Costa Rica's primary concerns is emergency preparedness for volcanic eruptions. Poas experienced a significant eruption in 2017 that led to evacuations; another eruption occurred earlier this year. Given these events, OVSICORI, the Volcanological and Seismological Observatory of Costa Rica, and ARSL are interested in exploring the potential of using DJI Dock 2 for continuous monitoring and automated drone operations.

OVSICORI views the monitoring efforts at Poas as a proof of concept. If successful, they plan to expand the use of data collection and 3D mapping to other, more remote active volcanoes in the country. The photogrammetry model created with DJI Terra provides recent baseline data on the crater, particularly in areas that have collapsed. This model serves as a crucial reference for identifying changes in subsequent monitoring efforts, helping to enhance the accuracy and reliability of volcanic observation.

Using DJI Terra, the ARSL's work at Poas Volcano contributes to understanding volcanic activity and plays a significant role in improving emergency preparedness and public safety in Costa Rica. The insights gained from this research have the potential to inform monitoring strategies for other volcanoes, both within the region and globally.

 

DJI Terra

3D map of Poas Volcano generated with DJI Terra

Forest Health Monitoring in the Maldives

The Republic of Maldives, a small atoll nation in the Indian Ocean southwest of India, consists of 26 atolls and over 1,000 coral islands, sprawling across an area comparable to Greece. These islands boast dense tropical forests vital to the nation's thriving tourism industry, as the tree cover provides much-needed shade from the intense tropical heat. Among the most common and ecologically significant trees in the Maldives is the Indian Almond tree. Unfortunately, these trees face a severe threat from the Hairy Caterpillar (Euproctis Fraterna), an insect known for its voracious appetite for plant life. In severe cases, these caterpillars can defoliate and even kill the trees, posing a significant risk to the local environment.

In response to this threat, the ARSL, in collaboration with another Canadian agency, partnered with the Soneva Fushi Resort to undertake a critical conservation project. They focused on mapping the Indian Almond trees on Kunfunadhoo, a resort island in the Maldives, and a UNESCO World Biosphere Reserve. As the site of one of the country's largest resorts, Kunfunadhoo is integral to the Maldives' tourism economy, making preserving its forests a top priority.

 

Kunfunadhoo Island

Kunfunadhoo Island, Maldives

 

ARSL's primary objective was to develop a rapid remote diagnostic tool to identify trees affected by the Hairy Caterpillar. To achieve this, they utilized LiDAR technology to gather detailed point cloud data of the entire island. This data was processed using DJI Terra to create an accurate and high-resolution 3D model of the island's forest canopy.

The 3D map generated by DJI Terra played a crucial role in this conservation effort. The map provided a detailed visualization of the forest, allowing researchers to precisely geolocate each Indian Almond tree on Kunfunadhoo. The 3D model then served as a baseline for comparing the health of individual trees, enabling scientists to distinguish between healthy trees and those showing early signs of infestation.

Gaining real-time insights into forest health is one of the most significant advantages of using DJI Terra. These models allow researchers to monitor changes in the forest canopy over time with incredible precision. By comparing current data with historical baselines, scientists can identify subtle shifts in tree health, such as reduced foliage density or changes in leaf color, which are early indicators of pest infestation. This early detection is critical because it enables timely intervention, potentially saving trees before the infestation becomes too severe.

In the Maldives, where the economy heavily relies on the health and beauty of its natural environment, such real-time insights are invaluable. The 3D models aid in the immediate identification of threats like the Hairy Caterpillar and contribute to long-term forest management strategies. By continuously updating the 3D models, ARSL can track the effectiveness of pest control measures, adjust their plan as needed, and ensure that the forests remain a vibrant part of the island ecosystem. This technology is helping to safeguard the Indian Almond trees of Kunfunadhoo and, by extension, the vital tourism industry that depends on the natural beauty of the Maldives.

 

3d map of island3D map of the southern part of the island

ARSL and DJI Terra

DJI Terra's high-accuracy 3D model maps mark a significant advancement for organizations like ARSL at McGill University. With DJI Terra, LiDAR, photogrammetry, 2D, and 3D data can be processed swiftly, enabling teams to deliver actionable insights to their partners rapidly. Its utilization at ARSL is pivotal for its proactive and effective environmental strategy, facilitating a deeper understanding and protection of diverse biospheres worldwide.

To watch the complete case study between Mcgill University's Applied Remote Sensing Lab and DJI Enterprise click below:

 

 

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