Fallow-land Algorithm based on Neighborhood and TemporalAnomalies (FANTA) to map planted versus fallowed croplands usingMODIS data to assist in drought studies leading to water and foodsecurity assessments

GIScience and Remote Sensing
By: , and 

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Abstract

An important metric to monitor for optimizing water use in agricultural areas is the amount of cropland left fallowed, or unplanted. Fallowed croplands are difficult to model because they have many expressions; for example, they can be managed and remain free of vegetation or be abandoned and become weedy if the climate for that season permits. We used 250 m, 8-day composite Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index data to develop an algorithm that can routinely map cropland status (planted or fallowed) with over 75% user’s and producer’s accuracies. The Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA) compares the current greenness of a cultivated pixel to its historical greenness and to the greenness of all cultivated pixels within a defined spatial neighborhood, and is therefore transportable across space and through time. This article introduces FANTA and applies it to California from 2001 to 2015 as a case study for use in data-poor places and for use in historical modeling. Timely and accurate knowledge of the extent of fallowing can provide decision makers with insights and knowledge to mitigate the impacts of drought and provide a scientific basis for effective management response. This study is part of the WaterSMART (Sustain and Manage America’s Resources for Tomorrow) project, an interdisciplinary and collaborative research effort focused on improving water conservation and optimizing water use.

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Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Fallow-land Algorithm based on Neighborhood and TemporalAnomalies (FANTA) to map planted versus fallowed croplands usingMODIS data to assist in drought studies leading to water and foodsecurity assessments
Series title GIScience and Remote Sensing
DOI 10.1080/15481603.2017.1290913
Volume 54
Issue 2
Year Published 2017
Language English
Publisher Taylor & Francis
Contributing office(s) Western Geographic Science Center
Description 25 p.
First page 258
Last page 282
Country United States
State California
Other Geospatial Central Valley