A cultivated planet in 2010 – Part 1: The global synergy cropland map. Lu, M., Wu, W., You, L., See, L., Fritz, S., Yu, Q., Wei, Y., Chen, D., Yang, P., & Xue, B. Earth System Science Data, 12(3):1913–1928, August, 2020. ![A cultivated planet in 2010 – Part 1: The global synergy cropland map [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Abstract. Information on global cropland distribution and agricultural production is critical for the world's agricultural monitoring and food security. We present datasets of cropland extent and agricultural production in a two-paper series of a cultivated planet in 2010. In the first part, we propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of the cropland area, which is independent of training samples. First, cropland area statistics are used to rank the input cropland maps, and then a scoring table is built to indicate the agreement among the input datasets. Secondly, statistics are allocated adaptively to the pixels with higher agreement scores until the cumulative cropland area is close to the statistics. The multilevel allocation results are then integrated to obtain the extent of cropland. We applied SASAM to produce a global cropland synergy map with a 500 m spatial resolution for circa 2010. The accuracy assessments show that the synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics. The synergy cropland map is available via an open-data repository (https://doi.org/10.7910/DVN/ZWSFAA; Lu et al., 2020). This new cropland map has been used as an essential input to the Spatial Production Allocation Model (SPAM) for producing the global dataset of agricultural production for circa 2010, which is described in the second part of the two-paper series.
@article{lu_cultivated_2020,
title = {A cultivated planet in 2010 – {Part} 1: {The} global synergy cropland map},
volume = {12},
issn = {1866-3516},
shorttitle = {A cultivated planet in 2010 – {Part} 1},
url = {https://essd.copernicus.org/articles/12/1913/2020/},
doi = {10.5194/essd-12-1913-2020},
abstract = {Abstract. Information on global cropland distribution and
agricultural production is critical for the world's agricultural monitoring
and food security. We present datasets of cropland extent and agricultural
production in a two-paper series of a cultivated planet in 2010. In the
first part, we propose a new Self-adapting Statistics Allocation Model
(SASAM) to develop the global map of cropland distribution. SASAM is based
on the fusion of multiple existing cropland maps and multilevel statistics
of the cropland area, which is independent of training samples. First,
cropland area statistics are used to rank the input cropland maps, and then
a scoring table is built to indicate the agreement among the input datasets.
Secondly, statistics are allocated adaptively to the pixels with higher
agreement scores until the cumulative cropland area is close to the
statistics. The multilevel allocation results are then integrated to obtain
the extent of cropland. We applied SASAM to produce a global cropland
synergy map with a 500 m spatial resolution for circa 2010. The accuracy
assessments show that the synergy map has higher accuracy than the input
datasets and better consistency with the cropland statistics. The synergy
cropland map is available via an open-data repository (https://doi.org/10.7910/DVN/ZWSFAA; Lu et al., 2020). This new cropland map
has been used as an essential input to the Spatial Production Allocation
Model (SPAM) for producing the global dataset of agricultural production
for circa 2010, which is described in the second part of the two-paper series.},
language = {en},
number = {3},
urldate = {2023-06-15},
journal = {Earth System Science Data},
author = {Lu, Miao and Wu, Wenbin and You, Liangzhi and See, Linda and Fritz, Steffen and Yu, Qiangyi and Wei, Yanbing and Chen, Di and Yang, Peng and Xue, Bing},
month = aug,
year = {2020},
keywords = {NALCMS},
pages = {1913--1928},
}
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SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of the cropland area, which is independent of training samples. First, cropland area statistics are used to rank the input cropland maps, and then a scoring table is built to indicate the agreement among the input datasets. Secondly, statistics are allocated adaptively to the pixels with higher agreement scores until the cumulative cropland area is close to the statistics. The multilevel allocation results are then integrated to obtain the extent of cropland. We applied SASAM to produce a global cropland synergy map with a 500 m spatial resolution for circa 2010. The accuracy assessments show that the synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics. The synergy cropland map is available via an open-data repository (https://doi.org/10.7910/DVN/ZWSFAA; Lu et al., 2020). This new cropland map has been used as an essential input to the Spatial Production Allocation Model (SPAM) for producing the global dataset of agricultural production for circa 2010, which is described in the second part of the two-paper series.","language":"en","number":"3","urldate":"2023-06-15","journal":"Earth System Science Data","author":[{"propositions":[],"lastnames":["Lu"],"firstnames":["Miao"],"suffixes":[]},{"propositions":[],"lastnames":["Wu"],"firstnames":["Wenbin"],"suffixes":[]},{"propositions":[],"lastnames":["You"],"firstnames":["Liangzhi"],"suffixes":[]},{"propositions":[],"lastnames":["See"],"firstnames":["Linda"],"suffixes":[]},{"propositions":[],"lastnames":["Fritz"],"firstnames":["Steffen"],"suffixes":[]},{"propositions":[],"lastnames":["Yu"],"firstnames":["Qiangyi"],"suffixes":[]},{"propositions":[],"lastnames":["Wei"],"firstnames":["Yanbing"],"suffixes":[]},{"propositions":[],"lastnames":["Chen"],"firstnames":["Di"],"suffixes":[]},{"propositions":[],"lastnames":["Yang"],"firstnames":["Peng"],"suffixes":[]},{"propositions":[],"lastnames":["Xue"],"firstnames":["Bing"],"suffixes":[]}],"month":"August","year":"2020","keywords":"NALCMS","pages":"1913–1928","bibtex":"@article{lu_cultivated_2020,\n\ttitle = {A cultivated planet in 2010 – {Part} 1: {The} global synergy cropland map},\n\tvolume = {12},\n\tissn = {1866-3516},\n\tshorttitle = {A cultivated planet in 2010 – {Part} 1},\n\turl = {https://essd.copernicus.org/articles/12/1913/2020/},\n\tdoi = {10.5194/essd-12-1913-2020},\n\tabstract = {Abstract. Information on global cropland distribution and\nagricultural production is critical for the world's agricultural monitoring\nand food security. We present datasets of cropland extent and agricultural\nproduction in a two-paper series of a cultivated planet in 2010. In the\nfirst part, we propose a new Self-adapting Statistics Allocation Model\n(SASAM) to develop the global map of cropland distribution. SASAM is based\non the fusion of multiple existing cropland maps and multilevel statistics\nof the cropland area, which is independent of training samples. First,\ncropland area statistics are used to rank the input cropland maps, and then\na scoring table is built to indicate the agreement among the input datasets.\nSecondly, statistics are allocated adaptively to the pixels with higher\nagreement scores until the cumulative cropland area is close to the\nstatistics. The multilevel allocation results are then integrated to obtain\nthe extent of cropland. We applied SASAM to produce a global cropland\nsynergy map with a 500 m spatial resolution for circa 2010. The accuracy\nassessments show that the synergy map has higher accuracy than the input\ndatasets and better consistency with the cropland statistics. The synergy\ncropland map is available via an open-data repository (https://doi.org/10.7910/DVN/ZWSFAA; Lu et al., 2020). This new cropland map\nhas been used as an essential input to the Spatial Production Allocation\nModel (SPAM) for producing the global dataset of agricultural production\nfor circa 2010, which is described in the second part of the two-paper series.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2023-06-15},\n\tjournal = {Earth System Science Data},\n\tauthor = {Lu, Miao and Wu, Wenbin and You, Liangzhi and See, Linda and Fritz, Steffen and Yu, Qiangyi and Wei, Yanbing and Chen, Di and Yang, Peng and Xue, Bing},\n\tmonth = aug,\n\tyear = {2020},\n\tkeywords = {NALCMS},\n\tpages = {1913--1928},\n}\n\n\n\n","author_short":["Lu, M.","Wu, W.","You, L.","See, L.","Fritz, S.","Yu, Q.","Wei, Y.","Chen, D.","Yang, P.","Xue, B."],"key":"lu_cultivated_2020","id":"lu_cultivated_2020","bibbaseid":"lu-wu-you-see-fritz-yu-wei-chen-etal-acultivatedplanetin2010part1theglobalsynergycroplandmap-2020","role":"author","urls":{"Paper":"https://essd.copernicus.org/articles/12/1913/2020/"},"keyword":["NALCMS"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"article","biburl":"https://bibbase.org/zotero/NAAtlas2024","dataSources":["qLjf8q88GSLZ5dAmC"],"keywords":["nalcms"],"search_terms":["cultivated","planet","2010","part","global","synergy","cropland","map","lu","wu","you","see","fritz","yu","wei","chen","yang","xue"],"title":"A cultivated planet in 2010 – Part 1: The global synergy cropland map","year":2020}