Work

Regression model estimation of early season crop proportions: North Dakota, some preliminary results

Year: 1982

Type: article

Abstract: To estimate crop proportions early in the season, an approach is proposed based on: use of a regression-based prediction equation to obtain an a priori estimate for specific major crop groups; modification of this estimate using current-year LANDSAT and weather data; and a breakdown of the major crop groups into specific crops by regression models. Results from the development and evaluation of appropriate regression models for the first portion of the proposed approach are presented. The results show that the model predicts 1980 crop proportions very well at both county and crop reporting district levels. In terms of planted acreage, the model underpredicted 9.1 percent of the 1980 published data on planted acreage at the county level. It predicted almost exactly the 1980 published data on planted acreage at the crop reporting district level and overpredicted the planted acreage by just 0.92 percent.

Source: NASA STI Repository (National Aeronautics and Space Administration)

Author: Kevin Lin

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Zero hunger, Life on land

Open Access status: green

Funders: U.S. Department of Commerce, U.S. Department of State, U.S. Department of Agriculture, United States Agency for International Development

OpenAlex ID: W823888557

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Related to: 10