Updated Oct 06, 2020

Spatial data outlier detection and MODIS product version comparison applications for Google Earth Engine

Part of Michigan State University

http://www.ksu.edu/siil

Joseph Messina

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Open access spatial data outlier detection and product version comparison applications for Google Earth Engine that allows modelers and other users to minimize error and uncertainty in remote sensing data models.

Stage 5: Scaling

Focus Areas:

Agriculture

AgricultureSEE LESS

Implemented In:

Malawi and United States

Malawi and United StatesSEE LESS

2
Countries Implemented In
Verified Funding
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Problem

Access to accurate digital data to reduce error and uncertainty in geospatial models.

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Solution

This tool reduces error and uncertainty 100% of the time if used properly and is completely publicly accessible. It also helps other models to be more accurate in reducing errors and uncertainty in both inputs and resulting estimates.

Target Beneficiaries

Primary beneficiaries are modelers and others doing agriculture policy work at national and international scales. Secondary beneficiaries are those interested in using digital tools for predictions.

Competitive Advantage

A tool such as this has not been created. The tool is a great benefit to the field for modelers and others working in agricultural reform.

Milestone

Date Unknown
New Country Implemented In
United States
Date Unknown
New Country Implemented In
Malawi