Using Satellite Imagery and Machine Learning to Address Climate Challenges in Agriculture

Indigo Atlas is a geospatial platform developed by Indigo Agriculture to address several agriculture problems globally. Indigo Agriculture is a company that is dedicated to helping farmers sustainably feed the planet.

Image credit: Indigo AG

In recent years, extreme weather and climate change have increased the challenges for agriculture globally. Since agriculture is very sensitive to weather and climate conditions, their impact has substantial direct and indirect effects on farm production and profitability. Climate change affects, both positively and negatively, the location, timing, and productivity of crop, livestock, and fishery systems at local, national, and global levels. It also changes and continues to alter the stability of food supplies and create new food security challenges as the world seeks to feed nine billion people by the year 2050.

However, the adoption of regenerative practices ─ those that have been proven to reduce emissions and remove carbon dioxide from the atmosphere ─ can address climate change issues related to agriculture, while creating a more resilient and beneficial food system. Indigo’s GeoInnovation team uses satellite imagery and in-field identification to map regenerative farming practices across the US and evaluate their potential resilience against environmental stressors.

“As climate change reshapes how, where, and when our food is available ─ an issue made all the more critical by the recent spread of COVID-19 ─ we are committed to assisting the public sector’s efforts to solve our most pressing global challenges,” says David Potere, Indigo’s Head of GeoInnovation.

Adoption of technology

Indigo Atlas, a satellite imaging and machine learning platform, forecasts crop yields and crop health daily around the world. Its stakeholders, including growers and partners, use the data that is collected for many objectives ─ for doing soil analysis to provide multi-layered soil maps, drawing field boundaries to meter-level accuracy, and identifying differences in crop health across a region throughout the season. Atlas connects satellite feeds with global crop maps to capture the pulse of the world’s food production. Every day, it scans plant canopies across agricultural lands to check progress and conditions, while making comparisons against more than a decade’s worth of historical information. When combined at national levels with other data sources like weather and government crop reports, it acts as training data for machine learning models. These models allow Indigo to forecast end-of-season yields, which help farmers make better marketing decisions in real-time.

Sensor for pre-harvest quality test | Image credit: Indigo AG

Atlas combines remote sensing, ground equipment, historical data, and weather data to track the dynamic variables that affect crop health. The technology can characterize local soil conditions, recognize field boundaries, and discern subtle differences in crop performance across regions. The immediacy and accuracy of this information can support growers in the marketing and sale of their grains. 

In 2017, Indigo’s models predicted the final corn yield within 1% of the final data, five months ahead of the USDA’s (United States Department of Agriculture’s) end of season report.

Using this technology, the World Bank is monitoring crop productivity in many growing regions like the Middle East and North America, where scarce agricultural land and water resources, together with growing populations, have worsened issues of food independence and security. In support of national and regional policies to address these challenges, Indigo will assess changes in cropland, crops, irrigation, and degradation of land over the past two decades, to identify opportunities for more efficient and sustainable future land management.

Indigo is also deploying its satellite capabilities to estimate corn yield shortfalls in provinces across Zambia, a country that has faced two consecutive years of drought. By equipping the South African nation’s agriculture and water specialists with an objective and comprehensive overview of the farms and irrigation systems throughout the country, Indigo and the World Bank aim to improve access to irrigation services in times of critical need. Insights gained from the analysis will be used to proactively optimize public sector services and infrastructure in a country on the front lines of climate change.


Value proposition

By offering real-time agricultural data generated through Indigo Atlas, Indigo’s collaboration with the World Bank will better inform decision-making in areas particularly vulnerable to the impact of climate change and help more efficiently direct resources in times of global food shortage.

Footnote: This case study is published with permission of Indigo Ag, Inc.

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