How the Soil Brightness Index enables Sustainable agriculture Practices

The Soil Brightness Index (SBI) is a valuable tool that can be used to do an express analysis of your soils, and is calculated by GeoPard based on satellite imagery. It is the fifteenth index on the GeoPard platform, it improves accessibility to soil analyses for those users who do not have access to soil sampling or electrical conductivity data, as it is collected via remote sensing

Soil Brightness Index calculated in GeoPard Agriculture platform
Soil Brightness Index calculated in GeoPard Agriculture platform

Soil brightness works as a proxy for soil organic matter, sands, and salinity areas, and is becoming an increasingly important index for studying changes in soil conditions over time. This is particularly relevant in measuring and monitoring soil degradation and soil erosion patterns, which are both critical environmental concerns around the world. A major goal of precision agriculture is to foster and contribute to more sustainable agricultural land management, and remote sensing is becoming an increasingly valuable technology with the resolution of satellite images improving so rapidly over time (1). Soil degradation and erosion are global issues, but also impact the longevity of individual agricultural operations and local environments. The most productive tier of a soil system is the topsoil, and when it becomes eroded farmers often need to increase production costs to maintain the same yields. Once topsoil has disappeared from a given area of land, erosion continues to degrade the stripped soil in a positive feedback cycle that creates an uneven land surface afflicted with rills and gullies, making efficient crop cultivation even more challenging (2). The Soil Color index can be used in multi-layer analysis with other indices to monitor changes in soils, like erosion patterns, which in turn can tell us vital information about crop productivity

Agronomists, growers and agribusinesses alike should appreciate how the information relayed by the SBI takes on the most value when it is used to inform decision-making about sustainable soil management and mitigate practices that may hinder it.

1. Marques, M. J., Alvarez, A., Carral, P., Sastre, B., & Bienes, R. (2020). The use of remote sensing to detect the consequences of erosion in gypsiferous soils. International Soil and Water Conservation Research8(4), 383-392.2. Seitz, S., Goebes, P., Puerta, V. L., Pereira, E. I. P., Wittwer, R., Six, J., … & Scholten, T. (2019). Conservation tillage and organic farming reduce soil erosion. Agronomy for Sustainable Development39(1), 1-10.

Soil Module

Soil chemical analysis is one of the most important data layers in crop farming. Typically, the soil information is coming from agrochemical laboratories analyzing field soil samples collected based on a grid or zonal approach. The number of soil characteristics in a concrete file can vary from 5-10 macronutrients such as Nitrogen(N), Phosphorus (P), Potassium (K), cation exchange capacity (CEC), soil organic matter (OM) content to 40-50 with all micronutrient properties.

How to use it?

You can upload soil sampling files into GeoPard Agriculture and get an easy-readable heatmap visualization of each attribute in the soil sampling file. In addition, you can delineate management zones based on any attribute, compare them with other layers like historical crop productivity and build variable rate fertilizer prescription files.

Moreover, GeoPard assists with the proper planning of zonal soil sampling. You can plan your soil sampling points and route based on GeoPard multi-year zones that reflect historical crop development pattern.

For the GeoPard team, the additional module with soil characteristics not only supports yet another powerful data layer but also is a step forward to cross-layer and multi-layer analytics.

Note that you are free to build own derivatives based on GeoPard analytics.

Many thanks to Isaac Hickerson (Data Manager at Hutson Precision Ag Team) and Jason Diller (Precision Ag Manager at Mercer Landmark, Inc.) for providing soil sampling datasets.

GeoPard Agriculture

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