Geospatial Data At Gro: Understanding The “Where” In Climate And Agriculture

What is geospatial data?

Geospatial data is any data that describes a place or an object located on the Earth. Most data related to climate, agriculture, and food security contains geospatial information, whether that is information spread across space and time or focused on a certain location (point) for a specific period of time.   

What is it used for?

Geospatial data is used for a wide variety of applications. For those related to climate change, agriculture, and food security, geospatial data can be used as inputs for yield prediction models. It can also be used to:

• Monitor crop conditions in real time/near-real time
• Assess the severity of a drought
• See how climate change will affect certain crops in the future

Through Gro’s platform, we offer a vast number of geospatial data sources on climate/weather, soil, and vegetation. Variables in these categories can be monitored, measured, or modeled:

These environmental variables can be measured directly using scientific instruments or remotely observed using sensors onboard satellites.  Remote sensing refers to any data that is collected from a distance, and satellite-remote sensing refers to data collected using sensors onboard satellites that orbit the Earth.  Satellite-remote sensing provides most of our geospatial data sources at Gro, but we also offer direct observations from sources like NOAA’s Global Historical Climatology Network (GHCN) weather stations, which measure precipitation and temperature.  

Gro’s Climate and Weather Data Foundation  

Let’s start by focusing on the weather data that underpins Gro’s climate data and analytics.  At Gro, our weather data sources include both historical and/or continuously updated satellite estimates and direct observations of temperature and precipitation.  

Satellite observations provide objective global spatial coverage with significant historical records for a vast number of environmental variables. Satellite-based observations offer users more objective results than direct observations because there is no risk of human intervention. Satellite estimates of surface precipitation and temperature are extremely valuable in regions where there are no weather stations or in regions that lack reliable weather station datasets.

Another way to analyze and monitor weather data is through direct measurements of precipitation from weather stations. One of the most valuable aspects of having access to direct observations from a global network of weather stations is that the data record goes back to 1763.  Direct observations of precipitation and temperature can be used to validate satellite estimates, and these observations can be used in longer-term climate trend analyses.  There is some inconsistency in station reporting throughout time and across space, so aggregating among stations across time is preferred.

Precipitation is also included in the Gro climate variables that are projected into future climate scenarios.  Gro’s climate change datasets help users understand how different IPCC climate scenarios will affect the global food system.  While these datasets are freely available from sources like the NOAA Geophysical Fluid Dynamics Lab, accessing these datasets through Gro lets users immediately see these projections in an agricultural context. 

Currently, Gro offers projections of monthly estimates of variables, like precipitation and temperature, up to 100 years into the future under five different IPCC categories of scenarios. These datasets are available through the Gro platform, for example in this chart and via Gro’s Climate Risk Navigator. 

Monitoring agricultural conditions is crucial to many of Gro’s platform users.  Looking at soil moisture and soil moisture anomalies for cropped areas allows users to detect potential crop failures or analyze the severity of drought events and their impacts on agriculture. 

We have covered a lot of different geospatial data sources offered at Gro that measure, model, or estimate observations of environmental variables within the categories of climate and weather, land and soil, and vegetation.  These datasets are used for a number of applications, but at Gro we offer them in order to address questions about climate and agriculture for any user-defined region in the world.  

For example, what if you wanted to understand more about how California was affected by drought this year? We created this display to answer that question using geospatial data sources.

For more information about how to use Gro’s geospatial data to solve your challenges in climate change, food security, or agriculture, or to schedule a demo on Gro’s Climate Risk Navigator, please contact our sales team at salesteam@gro-intelligence.com.