By Geitner Simmons
Acollaboration between a Husker scientist and the U.S. Department of Agriculture has created a web-based application now available to facilitate digital soil mapping and optimize soil sampling.
The Soil Sample Planning Organizer Tool, or SSPOT, “was designed as a user-friendly tool to help both producers and researchers make informed sampling decisions,” said Trenton Franz, a University of Nebraska–Lincoln professor of hydrogeophysics and associate director of research for the School of Natural Resources.
The tool can be accessed at https://sspot.scinet.usda.gov.
“Every project aiming to understand soil variability across a field faces the same questions: How many samples should I take, and where should I collect them?” said Franz, who developed the initial algorithm and provided the scientific backing behind SSPOT. “While these questions seem straightforward, the answers vary greatly depending on location and project goals.”
After Franz’s initial work, consultant Ben Cook worked with him to develop the original SSPOT prototype, and both contributed greatly to the new SSPOT interface, which was developed with support from industry partner Esri, inc.
USDA’s Agricultural Research Service and its Partnership for Data Innovations led the testing and refining of the software, incorporating valuable feedback from stakeholders throughout the process.
Effective soil management relies on understanding the various factors that drive soil productivity, including pH levels, nutrient variability and organic soil carbon. Soil sampling has emerged as a valuable tool in advancing precision farming, particularly in today's changing climate and the growing need to monitor carbon footprint in agriculture.
Land managers and researchers rely on routine soil sampling to monitor soil variability and determine the best practices to increase production while maintaining sustainability. However, they often face the challenge of identifying the optimal number of soil samples and their locations in complex and varied landscapes while managing limited time, resources and labor.
Selecting a well-distributed set of sampling sites is crucial for effective soil management decisions, and SSPOT aims to simplify this process.
SSPOT’s integrated algorithms help users determine the optimal placement of samples needed to comprehensively understand soil activity in various soil types over time. The algorithms simplify the process for non-experts and ultimately save land managers, producers and soil researchers time and money.
Users can select their specific Area of Interest (AOI) on the SSPOT map and utilize one of two “optimizer” algorithms. The algorithms use the USDA's Soil Survey Geographic Database and customizable grids to ensure sampling activities are thorough and efficiently capture the full picture of soil health within the selected area. SSPOT enables users to customize parameters for their search and export the results for practical applications in the field.
"SSPOT is an example of collaborative science, where a multidisciplinary team of experts from academia, the federal government and the private sector worked together to bring a vision to life," said Virginia Jin, location coordinator and research leader with the ARS Agroecosystem Management Research Unit. "We are confident that this tool can push forward the advancement of research for the benefit of croplands, grazing lands and forestry."
In addition, a version of SSPOT will support the USDA's National Resources Conservation Services in its conservation evaluation and monitoring activity efforts, including soil sampling needs.
SSPOT is part of ongoing collaborations among UNL, USDA and PDI aiming to strategize soil sampling to and improve soil health in the U.S.
Source : unl.edu