Temperature
January 17, 2023
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Daniel Spengler
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Remote sensing of crop health
Farmers have always been the backbone of sustenance, with their feet firmly planted on the soil that feeds nations. Today, their hands are graced with an abundance of data, sourced from weather stations, drones, and years of experience, all of which guide them in optimizing local yields. Yet, a broader perspective is essential to tackle complex changes, predict and mitigate natural calamities, and craft policies for safeguarding food security.
Enter the satellites – those unblinking observers orbiting high above. Their role in this narrative is two-fold. Firstly, satellites bring a panoramic understanding of the myriad factors that sway agricultural yields and our ability to respond. Secondly, and more intriguingly, they often offer a microscopic, sub-field view, a realm where thermal monitoring satellites shine. These high-tech eyes in the sky provide intricate early alerts of stress, seamlessly enhancing existing input systems' efficiency.
First, let us briefly describe the difference between quite well-known optical sensors and thermal sensors for agricultural applications:
Optical sensors measure at the surface reflected solar radiation in the visible, near infrared, and shortwave infrared range of the electromagnetic spectrum. They measure the reflectance properties of materials and objects, providing information about their spectral characteristics that are related to properties of the vegetation and soil. Remote sensing techniques of imagery in visible ranges are widely used for land cover mapping, vegetation monitoring, and environmental analysis.
Thermal sensors capture data in the mid-infrared (MWIR: 3-5 μm) and long wave infrared (LWIR: 8-12 μm) regions of the electromagnetic spectrum. They measure the thermal radiation emitted by objects, providing information about their surface temperature and thermal properties. Thermal remote sensing is particularly useful for monitoring the energy balance of the surface that is linked to the water balance, and monitoring of thermal anomalies. In comparison to optical data, which can be acquired only during daytime, thermal sensors can operate and acquire imagery during the day and night.
Scientific background of thermal remote sensing of crop health
Drought, a recurring natural hazard, poses a formidable challenge to agriculture and food security worldwide. As changing climate patterns bring about more frequent and severe drought events, the need for innovative and accurate methods to assess and monitor drought stress in agriculture becomes increasingly critical. In this context, thermal remote sensing stands out as a valuable instrument that could transform our capacity not just to analyze and comprehend the effects of drought on crops but also to detect stress in a timely manner, enabling proactive mitigation (Cammalleri and Vogt, 2015, Reiners et al., 2023).
Thermal remote sensing, based on derived LST, offers a unique perspective on the complex dynamics of drought stress in agriculture (Gerhards et al., 2019). Unlike visible or near-infrared remote sensing, which primarily captures information related to vegetation health and structure, thermal sensors detect the thermal energy emitted by the earth's surface. This energy, often referred to as radiative temperature, is strongly influenced by the moisture content of the soil and vegetation.
In cases of drought, often due to insufficient irrigation, the plant undergoes an increased rate of water loss through its stomata compared to the rate at which it can absorb water through its roots. In response to this imbalance, the plant modulates the size of its stomatal openings as a mechanism to mitigate the extent of water loss during the evaporation process. This adaptive response plays a pivotal role in preventing wilting and excessive drying, with the degree of adjustment varying depending on the duration and severity of the stress (Bukhari et al., 2019, Seleiman et al., 2021). Closing of stomata leads to an increased Land Surface Temperature (LST) of the crop canopy and can be measured directly via thermal data. Moreover, water stress can be detected in thermal remote sensing data a couple of days earlier compared to using only optical data. Also modelling the actual Evapotranspiration considering thermal data will lead to improved results to estimate the energy and water balance of crops. Consequently, thermal remote sensing provides a direct indicator of water stress, making it a powerful ally in drought assessment and monitoring.
The added value of thermal data currently is quite unexplored because of missing data.
There is a deficiency in existing remote sensing technologies operating at the necessary thermal infrared wavelengths and with low latency capabilities. On one hand, missions like Sentinel-3 or MODIS are available providing data at a high temporal resolution (sub-daily), but in insufficient spatial resolution (1000 m) for the agricultural praxis. On the other hand, mission offering a higher spatial resolution (e.g. from ECOSTRESS - 70 m, Landsat 9 - 100 m) are only available rarely not only due to the revisit time, but also due to cloud cover (Landsat, 16 days) or without continuous frequency (ECOSTRESS – ISS orbit) and so are not sufficient for a regular monitoring. Consequently, there is currently no plant-temperature sensing solution available that can deliver the necessary blend of timely, precise, and field-scale measurements required for effective smart water management.
This data gap has been identified and a new generation of thermal satellite mission is in preparation. At public site three main mission are currently in preparation. The French/Indian mission TRISHNA, the NASA SBG mission and the ESA/Copernicus LSTM mission. TRISHNA will be able to acquire imagery of each place on Earth within 3 days (with different viewing angles) or 8 days (with the same acquisition angle) with a spatial resolution of 57m (land) and 1km (ocean). The satellite combines two instruments to cover the VNIR/SWIR spectral range (6 bands) and the LWIR (4 bands). The launch is scheduled for 2025.
The Surface Biology and Geology mission of the NASA/JPL is scheduled for 2028. The SBG mission combines a hyperspectral imaging spectrometer (VSWIR; ~30 m pixel resolution) with multispectral instruments covering MWIR and LWIR (~60 m pixel resolution). The temporal resolution is planned to be ≤ 3 days.
The ESA/European Commission Copernicus Land Surface Temperature Mission (LSTM) will operate in VNIR/SWIR), and LWIR spectral ranges. The spatial resolution of 50 m and a 1–3-day revisit with high accuracy will offer a very good data base for regular monitoring of environment and agriculture conditions. LSTM will consist of a pair of two similar instruments with expected launch dates in 2028 (LSTM-A) and 2030 (LSTM-B).
In the private sector, several companies are preparing thermal satellite missions with different objectives and technical specifications. All of them aim for a daily revisit of their constellation to ensure monitoring capabilities. For topics like the monitoring of infrastructure, industry, or single houses of urban areas a Very High spatial Resolutions (VHR) a dedicated limited small area is required. These data will be offered by companies like Albedo (2m) and SatelliteVU (4m).
For uses cases larger coverages and more coarse spatial resolution required, like agriculture, forestry or environmental monitoring in general, companies like constellr (30m), Hydrosat (50m), Aistech (50m) and Ororatech (200m), will offer thermal data in spatial resolution between 30 and 200m. Some of the systems are optimized for specific applications like Ororatech to detect active fire covering large areas with a very high temporal frequency.
Analysing the time series of LST and ET at the described spatial and temporal high resolution can support a new era where precision meets sustainability, and where data-driven decisions empower farmers to overcome challenges that once seemed impossible. As the wheels of technology turn, the skies above become more than just a canvas of stars – they evolve into a dynamic realm of possibility, where satellites and innovation unite to rewrite the script of food security and environmental equilibrium. The combination of the information derived by thermal data with data from well-known satellited based sensor technologies (multispectral optical and SAR) enables a more detailed estimation of vegetation parameter to assess plant health and growth, crucial for detailed crop analysis. This technology empowers analytics at local, regional, and even national levels, aiding in comprehensive crop development evaluation.
The integration of satellites in agriculture has evolved from data collection to actionable insights. Equipped with embedded cameras and imaging technologies, satellites capture essential parameters. Thermal imaging, for instance, detects emitted heat, making it perfect for large land surveys. Changes in plant temperature can signify stressors like pathogens or external factors.
constellr data offers to support agriculture decision making.
The mission with the highest potential to act as a precursor for the public missions is the HiVE (High-Precision Versatile Ecosphere Monitoring) mission. Like upcoming public an actively cooled multispectral TIR (4 bands between 8-12 mm) sensor is used to enable the retrieval of LST at a very high accuracy and temporal stability. The first generation of HiVE satellites will deliver 30 m ground resolution in the Thermal Infrared (TIR) and 10 m in Visible and Near Infrared (VNIR). HIVE is a pioneering microsatellite constellation designed explicitly for high-resolution Thermal Infrared Land Surface Temperature (TIR LST) monitoring (Taymans et al., 2023). constellr collaborates with industry leaders such as OHB System, NanoAvionics, and Frauenhofer EMI, bringing together innovative approaches from both the emerging new-space sector and traditional space programs.
The primary objective of the HiVE mission is to generate and deliver global-coverage LST imagery optimized specifically for applications in water and sustainable resource management, agricultural monitoring, and temperature-based crop health management. Fig. 2 shows exemplary the added value of the significantly increased spatial resolution of HiVE, for example, of agriculture, in comparison to current state of the TIR satellites. constellr satellites can cover an area up to 1.4 Mkm² per day (daylight, land) per satellite. In select areas, a one-day global temporal resolution will be achieved using five assets.
At constellr, we embrace a mission that aligns with this evolution. Our unique satellite constellation, equipped with cutting-edge thermal infrared sensors, aims to measure temperature, water, and carbon. This leap in technology promises to reshape how we perceive and manage agriculture, driving us toward more efficient and sustainable practices.
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