July 27, 2023
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Charlie Siggs
As the 2023 growing season unfolds, challenging drought conditions have persistently loomed over the corn and soybean fields of Illinois, raising concerns about the potential impact on crop yields. With rainfall levels reminiscent of the infamous drought of 1988, farmers and agronomists are acutely aware of the challenges that lie ahead. However, in today's technologically advanced era, there is reason for cautious optimism.
With the advent of remote sensing technologies, the 2023 growing season stands in stark contrast to historical drought periods, such as those of 1988 and 2012. During these times of crisis, growers lacked the risk management tools and technologies available today, leaving them more vulnerable to the adverse impacts of drought. At this critical juncture, innovative solutions are crucial for mitigating the potential yield losses and ensuring the sustainability of corn and soybean crops.
By harnessing thermal infrared and hyperspectral imagery, farmers and agricultural stakeholders can gain a comprehensive understanding of crop health stress levels, and water availability. These advanced sensing technologies offer the ability to monitor fields at a granular level, allowing for timely interventions and more effective resource allocation.
This article aims to further explore:
Temperature is driving everything
Satellite derived Land Surface Temperature (LST) provides an insight into the impacts of heat and water stress at a critical time when actions can actually be taken to protect yield. Actions, such as applying biological stress stimulants, can help the crop cope with a stress event; crops can also be irrigated before the stress has a major impact on yield, further optimizing the impact of irrigation.
Temperature is a critical variable in the estimation of yield, which on a regional and national scale has major impacts in the forecasted crop production, greatly impacting commodity prices. Governments therefore need a way to accurately monitor crop canopy temperature across the whole country at a sub-field level to derive more accurate yield forecasts.
The limitation of near-infrared vegetation metrics is that their utility for long term agricultural projection is limited. NDVI primarily reflects the leaf structure and greenness of vegetation (Gamon et al., 1995; Ji and Peters, 2004), which are difficult to predict into the future (Ji and Peters, 2004). Moreover, they do not provide information on the underlying drivers of crop health or growing conditions. LST, however, is more indicative of external controls, such as the surface-energy balance, meteorological conditions, and soil moisture. In contrast to NDVI, it is possible to forecast these drivers using a combination of LST with geophysical principles and output from climate change models (Pede et al. 2010).
Case: Illinois, the 2nd largest producer of corn in the US
Producing 15% of the corn in the US makes Illinois a crucial supplier to the global corn market, if the production drops here, then it can have significant impacts on the global corn supply. It can cause corn prices to rise, which increases the production costs of livestock, and impacts how much corn is planted in other countries around the world, such as Brazil.
Yield forecasts will become even more important if the drought conditions in Illinois persist, which they currently are, according to the latest USDA reports. The forecast above average temperatures for August will further impact the yield of the corn and soybean crops of the Midwest. This can be detected by NDVI, but only after the event has happened -- LST can detect the impact of the event days or sometimes even weeks before the visible symptoms. It provides an indication of the water available to the crop, which is a factor that governments include in their yield forecast calculations.
Understanding the response of different practices and cultivar to drought and heat stress events that we have seen in recent years empowers a grower to deploy the practices that provide the highest level of risk mitigation. Practices such as implementing no-till and cover crops across a wider area, planting seeds with proven drought tolerance, varying planting date and using crop protection products that enhance response to drought.
Meeting Agriculture's Data Demands with LST Technology
In order to make these decisions farmers need sub-field level data with high accuracy of measurement and regular frequency, that is easy to interpret. Governments need data sources that inform them what is happening on a field level, before the impacts are visible.
The agriculture industry needs data that is at the field level, frequent, accurate, scalable and actionable. LST from constellr’s celestR fulfills all of these requirements and will increase in frequency, resolution and accuracy with the launch of HiVE in 2024.
For more information or a commercial offer please get in touch with Charlie Siggs or via sales@constellr.com