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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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Landsat-based maps of irrigated dry season cropping in Southeastern Anatolia, Turkey

Authors: Rufin, Philippe; Müller, Daniel; Schwieder, Marcel; Pflugmacher, Dirk; Hostert, Patrick;

Landsat-based maps of irrigated dry season cropping in Southeastern Anatolia, Turkey

Abstract

Landsat-based maps of irrigated dry-season cropping in Southeastern Anatolia, Turkey Long-term monitoring of the extent and intensity of irrigation systems is needed to track crop water consumption and to optimize land use in a changing climate. We mapped the expansion and land use intensity of irrigated dry season cropping in Turkey´s Southeastern Anatolia Project annually from 1990 to 2018 using Landsat time series and Google Earth Engine. This dataset includes multiple maps documenting the expansion and land use intensity of irrigated dry season cropping in Turkey´s largest irrigation scheme. We aggregated all Landsat imagery acquired during the July through September for the period 1990 to 2018 into spectral-temporal metrics and predicted dry season cropping annually using a machine learning classifier. We performed several post-processing steps to derive multiple map products for all areas with at least two dry season cropping cycles in the study period. The dataset comes in .zip format and includes the following map products: gap_dsc_fst.tif: first year of dry season cropping gap_dsc_yrs.tif: number of years with dry season cropping gap_dsc_frq.tif: dry season cropping frequency (% of years since first dry season cultivation): gap_dsc_trd.tif: five-year dry season cropping frequency trend magnitude gap_dsc_pvl.tif: significance level (p-values) Spatial coverage The maps come in 30m spatial resolution and cover the Southeastern Anatolia Project (Güneydoğu Anadolu Projesi, GAP) region. The region consists of nine provinces which account for approximately 10% of the Turkish land area. Temporal coverage The analyses cover the period 1990-2018. The first year of dry season cropping and the number of years with dry season cropping represent the time period 1990-2017. The temporal coverage of dry season cropping frequency varies on a pixel level, depending on the initial year of dry-season cultivation. The temporal coverage of the trend indicators also vary on a pixel level and furthermore have a constrained maximum temporal coverage of 1992-2012 due to the post-processing steps involved. Data format The data are delivered as 16bit single layer GeoTIFFs in EPSG:3035 projection. The images are LZW compressed, and have NoData value 0. Publication & further information Please see the publication for further information on the methodology and accuracy of the map products: Rufin, P.; Müller, D.; Schwieder, M.; Pflugmacher, D.; Hostert, P. (2020): Landsat time series reveal simultaneous expansion and intensification of irrigated dry season cropping in Southeastern Turkey. Journal of Land Use Science. DOI: http://dx.doi.org/10.1080/1747423X.2020.1858198 Acknowledgments This research contributes to the Landsat Science Team 2018-2023 (http://www.usgs.gov/land-resources/nli/landsat/landsat-science-teams) and the Global Land Programme (https://glp.earth/). We gratefully acknowledge the open cloud processing platform provided by Google.

Keywords

Cotton production, Turkey, Agricultural support payments, Land use, Crop water requirements, Agriculture, Landsat time series, Remote sensing, Irrigation

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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