Observing Earth from space

1 Observe Earth from space Observing Earth from space Resource booklet for Tū’desē’cho Wholistic Indigenous Leadership Development produced by Arctic PASSION 2 Observe Earth from space This system will enhance scientific and community-based monitoring, incorporating Indigenous and Local knowledge. It also seeks to improve data access and sharing, ensuring long-term usability. Partnering with Snowchange, Tū’desē’cho Wholistic Indigenous Leadership Development (TWILD) is creating a database of Indigenous Knowledge to track climate change impacts on the land, plants, animals, water, and fish, aiding in future sustenance hunting and fishing. TWILD’s Tene Mehodihi youth program will use drone footage to measure glacier ice extent and compare it with historical data to illustrate ice loss around the Sheslay River headwaters. You will also map disturbances from recent forest fires in lower elevations to understand wildfire history in Tahltan territory. Climate change is affecting the Arctic faster than other parts of Europe. As part of the Arctic, Europe wants to co-create new knowledge together with those who know the Arctic best: the local and Indigenous Peoples’ Communities. Climate change observation funded by the European Union Our project aims to support your observations by sharing how scientists monitor changes in glaciers and wildfires, including aerial photos and satellite imagery. In this booklet, you will find the following: • Natural Colour satellite image • False colour satellite image • Mud Glacier 1985 – 2022 • Great Glacier 1982-2022 • Choquette Glacier 1985-2022 • Hoodoo-Twin Glaciers 1985-2022 • Porcupine Glacier 1985-2022 As well as theoretical background information on disturbance maps for wildfire observations. 2Observe Earth from space Arctic PASSION aims to develop a better system, called the ‘Pan-Arctic Observing System of Systems – pan-AOSS’, for monitoring the Arctic. 3 Observe Earth from space 4 Observe Earth from space Satellites orbit high above Earth and use special cameras and sensors to capture images and data of the surface. Scientists look at these images to find glaciers by spotting large areas covered in ice and snow. They can also measure the temperature and see how the glaciers move over time. This helps scientists understand how glaciers are changing, which is really important for studying our planet’s climate and water supply. So, satellites are like space detectives, keeping an eye on Earth’s icy parts! Natural color imagery  Natural color imagery is like seeing the world through a satellite’s eyes, just as we would see it with our own. Satellites capture images using the same colors our eyes can see: red, green, and blue. When these images are combined, they create a true-to-life picture of Earth’s surface. This helps scientists and researchers observe landscapes, cities, forests, and oceans in a way that’s familiar and easy to understand. It’s like taking a giant, super-detailed photo from space, showing us the natural colors of our planet exactly as they appear in real life. 4Observe Earth from space Detecting glaciers using satellites is like taking super detailed photos from space! 5 Observe Earth from space 6 Observe Earth from space 6Observe Earth from space False color imagery  False color imagery is a cool trick scientists use to see things that our eyes can’t. Normally, we see colors based on visible light, but false color imagery uses different colors to represent invisible wavelengths like infrared. For example, in this satellite image healthy and dense vegetation reflect a lot of infrared light, so in false color images, they might appear red instead of green. This helps scientists study vegetation, water, and even the surface of other planets in ways that wouldn’t be possible with regular photos. By changing the colors, they can highlight important details and patterns, making it easier to understand what’s happening in nature and beyond. 7 Observe Earth from space 8 Observe Earth from space One cool way they do it is by using a method called “geodetic monitoring” which involves taking pictures and measurements from high above the glacier. Step 1: Capturing Images First, scientists use airplanes or satellites to take detailed photographs or laser scans of the glacier’s surface. They do this at different times, maybe a few years apart. The images show the shape and height of the glacier’s surface. Step 2: Creating 3D Maps Next, they use special computer programs to turn those images into 3D maps of the glacier’s surface. It’s like creating a virtual model of the glacier! Step 3: Comparing the Maps By comparing the 3D maps from different years, scientists can see how the glacier’s surface has changed over time. If the surface has gotten lower, it means the glacier has lost some of its ice. Monitoring Glaciers from Above Have you ever wondered how scientists keep track of the massive rivers of ice called glaciers? Step 4: Calculating the Changes Using math, scientists can calculate exactly how much ice the glacier has lost or gained. They do this by measuring the difference in height between the maps and then converting that to a volume of ice. This geodetic method is really useful because it gives scientists a complete picture of what’s happening to the whole glacier. However, it does require special equipment and a bit of guesswork about how dense the ice is. By monitoring glaciers from above, scientists can better understand how they are being affected by climate change and how that might impact the rest of the planet. Here are satellite images for the glaciers you will be monitoring, with photos taken in 1985 and in 2022. Can you spot the differences between the two images? Credits: ESRI, NASA, USGS, Earthstar Geographics, NGA, CGIAR, NLS, OS, NMA 8Observe Earth from space 9 Observe Earth from space 16 Observe Earth from space 17 Observe Earth from space 18 Observe Earth from space 19 Observe Earth from space 20 Observe Earth from space One key aspect is how much sunlight different objects reflect, known as reflectance. Reflectance varies by material and sunlight angle; for instance, soil, plants, and water reflect sunlight differently, as do various types of vegetation like forests and wheat fields. This variation helps us distinguish different colors. As plants change over time, their reflectance also changes. By measuring reflectance from space, we can identify soil, water, snow, ice, or vegetation in an area and assess the health, growth, and abundance of plants. Observe Earth from space Observing the Earth from above allows us to understand aspects that are invisible from the ground. NASA, ESA, Leah Hustak (STScI) 21 Observe Earth from space Descartes Labs Inc 22 Observe Earth from space For example, detecting changes in the number of trees (forest change) is easier than identifying forest degradation due to natural or human causes. Tracking forest changes, like deforestation and recovery, has been ongoing since the 1980s and 1990s with Landsat data. Today, we have global and country-specific maps showing yearly deforestation rates. However, we still lack complete information on forest degradation. Now, with more detailed satellite images, we can create time series to monitor areas over time. This helps us spot small changes in deforestation and degradation and send alerts when changes occur. For more information on satellite observations, visit the My Sustainable Forest webpage, which offers well-documented products, application examples, videos, and webinars. What we want to observe The complexity of what we want to observe affects the difficulty of doing so. 23 Observe Earth from space Roncal Valley of the Pyrenees (Navarra, Spain) – The forest mask locates the forested area MySustainableForest, ESA 24 Observe Earth from space “Forest disturbance” refers to natural events causing the loss of tree cover or biomass, such as storms, fires, droughts, insect infestations, and disease outbreaks. It can also include human activities like logging that harm the forest. Disturbances are usually one-time events with short-term effects, often part of the natural forest cycle. “Forest degradation,” however, primarily involves longterm negative effects caused by human activities, resulting from one or more disturbances. Examples of large-scale forest disturbances include: • Windthrow in a Picea abies forest (a) • Massive ice storm damage in 2014 (b) • Forest fires in the sub-Mediterranean (c-d) • Dieback of Fraxinus excelsior caused by the fungal disease Hymenoscyphus fraxineus (e) • Forest management after a disturbance, such as salvage logging (f) Disturbance or degradation Earth-Science Reviews vol 235, a) A. Marinšek, b) L. Kutnar, c-d) K. Eler, e) J. Kermavnar, f) L. Kutnar 25 Observe Earth from space Since the 1980s, Landsat missions have used satellites to monitor changes on the Earth’s surface. These satellites have sensors that measure surface reflectance in specific parts of the electromagnetic spectrum. Selecting the right channels is crucial and complex, resulting in each satellite having a unique combination of channels. Technological advancements have led to the development of hyper-spectral sensors, which measure a large number of wavelengths across broader spectral channels, simplifying the challenge of channel selection. Besides measuring different parts of the electromagnetic spectrum, these sensors also feature high spatial resolution, allowing them to observe smaller areas of the surface. Our eyes: multispectral sensors on satellites Highly accurate measurements of Earth’s thermal energy obtained by Landsat 5 Satellite Imaging Corporation 32 Observe Earth from space Unlike the image-to-image method, this approach requires a continuous series of images taken over a period of time, necessitating regular coverage of the area of interest. Time series analysis closely examines how images evolve over time and typically comprises three components: 1. Long-term trend: Indicates the overall direction of change. 2. Seasonal component: Reflects changes occurring at different times of the year. 3. Residual component: Includes unexpected changes that are not part of the long-term trend or seasonal variations. Toward a Near-time monitoring of degradation/disturbances Depending on the study focus, one or all of these components may be significant. To apply this method effectively, these components must be separated and the time series smoothed using mathematical techniques. For monitoring forest degradation, isolating the residual component is crucial to distinguish it from random noise. In different forest regions, understanding the seasonal component is also pivotal for assessing disturbances accurately. Near-real time disturbance detection using time series looks for breaks from modelled seasons patterns in forest reflectance Another method for detecting changes in forests is Time Series Analysis-based Change Detection. EU 2022, Jonas Viehweger 33 Observe Earth from space Scientists use disturbance maps to understand and manage wildfires better. These maps show areas where wildfires have caused changes in the landscape. By comparing images taken before and after a wildfire, scientists can see exactly where the fire burned and how severe it was. This information helps them plan for future wildfires, figure out which areas need replanting or other restoration efforts, and study how wildfires affect the environment. Disturbance maps are essential tools for keeping forests healthy and safe. Scientists study areas burned by fires by analyzing how the surface reflects light before and after a fire. Use disturbance maps for wildfires Healthy vegetation reflects a lot of green light that our eyes can see, but after a fire, the landscape turns brown or black, with reduced reflectance. Even though our eyes can’t see it, satellites can detect these changes in near-infrared light (which is just beyond what we can see). Healthy Vegetation vs. Burned Areas Disturbance maps are like treasure maps for understanding wildfires. NASA Applied Sciences 34 Observe Earth from space These indices show where fires have affected vegetation. Scientists also use fire detection data from satellites, which spot fires by sensing unusually high temperatures. By combining these tools, scientists can create maps that show where fires have burned and how severe the damage is, helping them manage and restore forests more effectively. Burn severity mapping Two important indices, NDVI and NBR, help scientists identify burned areas by comparing reflectance in visible and near-infrared light. NASA Applied Sciences 35 Observe Earth from space Hustak, Leah (NASA), 2021. Reflectance Spectra: Earth’s Surface Materials. https://webbtelescope.org/contents/media/images/01F8GFAGTM98 YTKDS0FZAAWWV2, accessed 18.06.2024. Spectral Signatures, https://blog.descarteslabs.com/a-look-into-thefundamentals-of-remote-sensing, accessed 18.06.2014. Forest mask: Roncal Valley, Navarre, Spain. Copernicus Sentinel-2A (2018) (acquired on 22/08/2017, GSD 10.0 m) provided by the European Space Agency. https://mysustainableforest.com/outputs/samplecases/, accessed 18.06.2014. The effects of large-scale forest disturbances on hydrology – An overview with special emphasis on karst aquifer systems. November 2022 EarthScience Reviews 235(1):104243, DOI:10.1016/j.earscirev.2022.104243, LicenseCC BY-NC-ND 4.0. Enhanced Image Western Australia, Satellite Imaging Corporation. https://www.satimagingcorp.com/satellite-sensors/other-satellitesensors/landsat-8/, accessed 18.06.2014. High-resolution (0.5m/pixel) image from Kompsat 3 where you can distinguish each individual tree. EOS Data Analytics. https://eos.com/ blog/spatial-resolution/, accessed 18.06.2014. Medium-resolution (10m/pixel) image from Sentinel-2 L2A, allowing you to make out the field boundaries without field details. EOS Data Analytics. https://eos.com/blog/spatial-resolution/, accessed 18.06.2014. Low-resolution (30m/pixel) image from Landsat 8 OLI and TIRS displaying the general landscape features of a vast area. EOS Data Analytics. https://eos.com/blog/spatial-resolution/ , accessed 18.06.2014. Morales-Barquero, L.; Skutsch, M.; Jardel-Peláez, E.J.; Ghilardi, A.; Kleinn, C.; Healey, J.R. Forest succession curve. Operationalizing the Definition of Forest Degradation for REDD+, with Application to Mexico. Forests 2014, 5, 16531681.https://doi.org/10.3390/f5071653 (Figure 1). https://geoawesomeness. com/mapping-forest-degradation/, accessed 18.06.2014. Ahmad Alzu’bi, Lujain Alsmadi, Monitoring deforestation in Jordan using deep semantic segmentation with satellite imagery, Ecological Informatics 70 (2022) 101745 Ecological Informatics 70 (2022) 101745, https://www. sciencedirect.com/science/article/pii/S1574954122001959?via%3Dihub, accessed 18.06.2014. Shifting the Goalposts: Land Use Change in Queensland. https://www. agriculture.gov.au/abares/aclump/land-use-change-overview, accessed 18.06.2014. European Union, 2022; Jonas Viehweger. Near-real time disturbance detection using time series looks for breaks from modelled seasons patterns in forest reflectance. https://forest.jrc.ec.europa.eu/en/ activities/forest-disturbances/, accessed 18.06.2014. ArcGIS, Change Detection in Amazon Floodplains Using Landsat Time Series Imagery & RemoteSensing, May 09, 2022, Hong Xu https://www. esri.com/arcgis-blog/products/arcgis-pro/imagery/change-detectionusing-landsat-time-series/, accessed 18.06.2014. References This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101003472 Learn more about Arctic PASSION