ConstellR, a startup based in Freiburg, Germany, aims to provide land surface temperature measurements with high spatio-temporal resolution for the whole planet using a CubeSat constellation.
The company has estimated that it would need 11 satellites to provide land surface temperature monitoring with 48 hr revisit time over mid-latitudes and about 30-35 for daily global coverage. It will offer Land surface temperature (LST) data which is the primary dataset for monitoring applications across different markets as well as the basis for many remote sensing products, including evapotranspiration & water stress and crop yield prediction models.
ConstellR has a strong network of partners in both the industry and academia, with its home institutes being a part of German Fraunhofer Society for Applied Science and the German Aerospace Center, which are two of Europe’s largest research organizations. OHB System AG, one of Europe’s large system integrators, is supporting ConstellR technologically.
ConstellR will provide up-to-date analytics-ready datasets for different sectors. This information will play a crucial role in water quality monitoring, wildlife monitoring, vegetation water stress, flash drought prediction and water management.
“We have identified core challenges and we worked hard for years to find ways to overcome them and bring highly precise thermal infrared monitoring to a CubeSat format.”, says Max Gulde, ConstellR CEO and scientist at Fraunhofer Ernst-Mach-Institute, in an interview with Geospatial World. Excerpts.
What are the major challenges in continuously monitoring the Earth’s temperature?
Well, first of all, thermal infrared sensors are recording in the wavelength between 8 – 14 µm which means that we need about 20 times larger apertures compared to the visual range to generate imagery of similar resolution. That’s increasing the size of the payload massively. Furthermore, we need to cool the sensor to achieve high-temperature measurement accuracy. Cooling is a relatively inefficient and power-consuming process and we also need to get rid of the excess heat somehow, usually via large areas pointing into deep space. If we only made the sensor smaller, we would at the same time increase the number of satellites needed for global daily monitoring. Both points usually prohibit the use of a CubeSat platform with limited volume, surface area and power.
What is the main advantage of Thermal infrared imagery over conventional high-resolution satellite imagery?
The thermal infrared provides us with information about our planet’s surface temperature, which is a key environmental variable. While we are restricted – as we are in the visual regime – by cloud coverage, we are independent of reflected light, which means that we can see during the night as well as we can during daylight.
Moreover, thermal infrared can yield information not accessible in the visual or near-infrared regimes. For example, thermal infrared is ideally suited to monitor vegetation health, i.e. by early detection of water stress in plants (which leads to a decrease in transpiration and hence an increase in canopy temperature). This detection is possible well before any physiological changes, i.e. changing of the leaf color, is taking place and can help to timely install appropriate measures to avoid permanent damage and decrease in crop yield. In the visual, we have to wait for such physiological changes to take place to be able to act. That’s one of the powers of thermal infrared imaging.
Do you think mapping urban heat islands could provide a better and more sustainable way for smart city planning?
Definitely, yes. There is plenty of scientific literature on this topic, in particular on ways to improve data availability of high spatio-temporal resolutions. Of course, megacities, as well as cities in hot regions, are mostly affected – Shanghai, London, Paris – but the general temperature trend will force us to deal with it on a global scale. For example, in the summer of 2003 there were an estimated 70,000 heat-related casualties in Europe alone, and most of them were in urban areas. Even if we succeed to stay below the 2 °C global temperature rise, we have to be aware that this is an average value and the mean temperature in many large cities is already well above this limit. It’s simply due to the fact that cities make up only about 3% of our planet’s surface area that this dangerous trend is underestimated.
If we have the capability to continuously map the energy flow in cities with high resolution, we will have a very efficient way to directly evaluate counter mechanisms. Moreover, we can determine the biggest influencing factors in existing cities. In my opinion, it would be a big leap forward to have a high-resolution data source. But frankly, data alone will not solve the problem. We also need respective models to simulate the complex urban environment.
Land surface temperature datasets have a host of applications from wildfire monitoring to drought prediction. Do you think it could play a big role in boosting precision agriculture and preventing ecological destruction?
Only about 1% of our planet’s land surface is actively irrigated. Nevertheless, more than 70% of global freshwater consumption can be linked to agriculture. Even if we would only assume a marginal water savings potential, the impact – economically and environmentally – would be enormous. And it is direly needed, since we will need to produce about 60% more food by 2050 compared to 2010 to feed a growing world population. Taking into account that we have an increasing amount of land degradation the only ways to prevent an agricultural breakdown are increasing crop and water productivity and rededication of land, like pastures into crop-producing fields. And I am sure it will be a combination of both ways in the end.
We have had discussions with specialists in this area on how to tackle this problem. For instance, using ground sensors in precision farming can lead to a reduction in water consumption by up to 30 %. However, such sensors are too expensive for many countries in the world and require manual installation and maintenance. In my view, satellite data provides the only globally applicable solution. So again, we cannot underestimate the role of thermal data in this domain.
An additional challenge in precision farming is also the user uptake. Since agriculture is such a fragmented market, it is difficult to quickly deploy new solutions. Here, we recognize the crucial role of value-added service providers in the agricultural sector to develop an attractive and affordable solution using the data we will provide.
Do you think the various infrared imagery could be merged to provide actionable insights that would help in the realization of UN SDGs?
Yes. Just to give you a few examples: SDG 2, Zero Hunger, could be leveraged by means of improvement in farming efficiency as mentioned earlier: higher water productivity will improve the efficiency of agriculture, leading to a higher yield in food production. Also, the ability to substantially improve crop yield predictions and detect water stress days in advance, before physiological changes manifest themselves in the crops, will allow implementing resilient practices for farmers and economic decision-makers alike.
SDG 6, Clean Water and Sanitation, will definitely be supported by our data by improving water management practices: temperature monitoring of inland waters is vital for the risk assessment of pandemic outbreaks and modeling of disease propagation vectors. Based on such information, early warning systems for water quality could be established.
SDG 13: Climate Action. Specifically, the reduction in water consumption and active monitoring of permafrost areas will lead to a substantial reduction of CO2 emissions. Here also volcanic monitoring and ice coverage analysis can play an additional role.