Item talk:Q239099
From geokb
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"name": "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",
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"abstract": "An important metric to monitor for optimizing water use in agricultural areas is the\namount of cropland left fallowed, or unplanted. Fallowed croplands are difficult to\nmodel because they have many expressions; for example, they can be managed and\nremain free of vegetation or be abandoned and become weedy if the climate for that\nseason permits. We used 250 m, 8-day composite Moderate Resolution Imaging\nSpectroradiometer normalized difference vegetation index data to develop an algorithm\nthat can routinely map cropland status (planted or fallowed) with over 75% user\u2019s and\nproducer\u2019s accuracies. The Fallow-land Algorithm based on Neighborhood and\nTemporal Anomalies (FANTA) compares the current greenness of a cultivated pixel to\nits historical greenness and to the greenness of all cultivated pixels within a defined\nspatial neighborhood, and is therefore transportable across space and through time. This\narticle introduces FANTA and applies it to California from 2001 to 2015 as a case study\nfor use in data-poor places and for use in historical modeling. Timely and accurate\nknowledge of the extent of fallowing can provide decision makers with insights and\nknowledge to mitigate the impacts of drought and provide a scientific basis for effective\nmanagement response. This study is part of the WaterSMART (Sustain and Manage\nAmerica\u2019s Resources for Tomorrow) project, an interdisciplinary and collaborative\nresearch effort focused on improving water conservation and optimizing water use.",
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