Data From: Topographic Position Index Predicts Within-field Yield Variation In A Dryland Cereal Production System by US Government | Finance and Economics

About this Dataset

Data From: Topographic Position Index Predicts Within-field Yield Variation In A Dryland Cereal Production System

We investigated drivers of sub-field spatial variability in yield for 3 crops (hard red winter wheat, Triticum aestivum L. variety Langin; corn, Zea mays L.; and proso millet, Panicum milaceum L.) usings this multi-year dataset from a dryland research farm in northeastern Colorado, USA. The dataset spanned 18 2.6-4.3 ha management units collected over 4 years (2019-2022). The data includes high resolution topographic data collected via real-time kinematic GPS, densely sampled soil texture and chemical properties, and meteorological data from an on-site weather station.
Organization: Department of Agriculture
Last updated: 2025-06-05T09:51:30.391317
Tags: dryland, machine-learning, precision-agriculture, rainfed, random-forest, spatial-variability, topographic-position-index, yield

Tables

Modeling Data

@usgov.usda_gov_data_from_topographic_position_index_predicts_5803474e.modeling_data

53.58 KB
721 rows
21 columns


CREATE TABLE modeling_data (
  "easting_utm13n" DOUBLE,
  "northing_utm13n" DOUBLE,
  "yield_kg_ha" DOUBLE,
  "crop" VARCHAR,
  "year" BIGINT,
  "rotation" VARCHAR,
  "field" VARCHAR,
  "elev" DOUBLE,
  "twi" DOUBLE,
  "psri" DOUBLE,
  "curv" DOUBLE,
  "slope" DOUBLE,
  "tpi" DOUBLE,
  "roughness" DOUBLE,
  "sand_percent" DOUBLE,
  "carbon_percent" DOUBLE,
  "n_kg_ha" DOUBLE,
  "p_spring_mm" VARCHAR,
  "spei3_prior_sep" VARCHAR,
  "p_summer_mm" VARCHAR,
  "spei3_jun" VARCHAR
);

Data Dictionary

@usgov.usda_gov_data_from_topographic_position_index_predicts_5803474e.data_dictionary

5.64 KB
21 rows
5 columns


CREATE TABLE data_dictionary (
  "column_name" VARCHAR,
  "unit" VARCHAR,
  "descriptions" VARCHAR,
  "code_definition" VARCHAR,
  "unnamed_4" VARCHAR
);