Data

Historical land cover and paddy rice mapping for Northwest Bangladesh 1989 to 2016

Commonwealth Scientific and Industrial Research Organisation
Pena Arancibia, Jorge ; Golam, Mahboob ; Islam, AFM Tariqul ; Mainuddin, Mohammed ; Yu, Yingying ; Ahmad, Mobin-ud-Din ; Ibn Murad, Khandakar F. ; Saha, Kowshik K. ; Hossain, Akbar ; Moniruzzaman, M ; Ticehurst, Catherine ; Kong, Dongdong
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/5ec4fcfbbb3c4&rft.title=Historical land cover and paddy rice mapping for Northwest Bangladesh 1989 to 2016&rft.identifier=https://doi.org/10.25919/5ec4fcfbbb3c4&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=High resolution (30 m) land cover and cropping maps in GeoTIFF format for two main rice types in northern Bangladesh, dry season Boro rice (January to May) and wet season Aman rice (October to January) for the cropping seasons of 1989–1990 to 2015–2016. Other land cover types include other vegetated type, water, water non-permanent, and bare. The values in the Boro season are as follows: 10 represents Boro, 11 and 13 represent other vegetated areas, 14 represents water, 15 represents water non-permanent and 16 represents bare. The values in the Aman season are as follows: 20 represents Aman, 23 represents other vegetated areas, 24 represents water, 25 represents water non-permanent and 26 represents bare. Value 0 is a null value in both rice season maps. Associated GeoTIFF maps show the number of months missing in each pixel per mapping season per cropping year (using the unfilled monthly composite images) as a guide for quality. \nLineage: The data used to produce the maps encompassed nearly three decades of Landsat TM/ETM+/OLI TOA reflectance data from several satellite platforms, sourced and pre-processed through the freely available petabyte archive and geostatistical processing power of Google Earth Engine. Geospatial techniques were used to reduce gaps in the data. A combination of unsupervised K-means clustering and supervised Random Forest Machine Learning algorithms were implemented to produce a predictive model that includes vegetation indices and other covariates, which explain the phenology of different land cover types.&rft.creator=Pena Arancibia, Jorge &rft.creator=Golam, Mahboob &rft.creator=Islam, AFM Tariqul &rft.creator=Mainuddin, Mohammed &rft.creator=Yu, Yingying &rft.creator=Ahmad, Mobin-ud-Din &rft.creator=Ibn Murad, Khandakar F. &rft.creator=Saha, Kowshik K. &rft.creator=Hossain, Akbar &rft.creator=Moniruzzaman, M &rft.creator=Ticehurst, Catherine &rft.creator=Kong, Dongdong &rft.date=2020&rft.edition=v2&rft.coverage=westlimit=87.999953379161; southlimit=23.599910326406; eastlimit=90.000411683616; northlimit=26.703679461851; projection=WGS84&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2020.&rft_subject=Remote sensing&rft_subject=machine learning&rft_subject=irrigation&rft_subject=rice&rft_subject=Other earth sciences not elsewhere classified&rft_subject=Other earth sciences&rft_subject=EARTH SCIENCES&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/

Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2020.

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Brief description

High resolution (30 m) land cover and cropping maps in GeoTIFF format for two main rice types in northern Bangladesh, dry season Boro rice (January to May) and wet season Aman rice (October to January) for the cropping seasons of 1989–1990 to 2015–2016. Other land cover types include other vegetated type, water, water non-permanent, and bare. The values in the Boro season are as follows: 10 represents Boro, 11 and 13 represent other vegetated areas, 14 represents water, 15 represents water non-permanent and 16 represents bare. The values in the Aman season are as follows: 20 represents Aman, 23 represents other vegetated areas, 24 represents water, 25 represents water non-permanent and 26 represents bare. Value 0 is a null value in both rice season maps. Associated GeoTIFF maps show the number of months missing in each pixel per mapping season per cropping year (using the unfilled monthly composite images) as a guide for quality.
Lineage: The data used to produce the maps encompassed nearly three decades of Landsat TM/ETM+/OLI TOA reflectance data from several satellite platforms, sourced and pre-processed through the freely available petabyte archive and geostatistical processing power of Google Earth Engine. Geospatial techniques were used to reduce gaps in the data. A combination of unsupervised K-means clustering and supervised Random Forest Machine Learning algorithms were implemented to produce a predictive model that includes vegetation indices and other covariates, which explain the phenology of different land cover types.

Available: 2020-06-30

Data time period: 1989-10-01 to 2016-05-01

This dataset is part of a larger collection

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90.00041,26.70368 90.00041,23.59991 87.99995,23.59991 87.99995,26.70368 90.00041,26.70368

89.000182531389,25.151794894128

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