Deriving 2011 cultivated land cover data sets using usda National Agricultural Statistics Service historic Cropland Data Layers. Boryan, C., Yang, Z., & Di, L. In 2012 IEEE International Geoscience and Remote Sensing Symposium, pages 6297–6300, July, 2012. doi abstract bibtex This paper describes the method used to derive 30 meter resolution 2011 US cultivated data sets based on multi-year National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data. This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. The strongest models for all states achieved overall (producer and user) accuracies greater than 94% for cultivated and non cultivated categories.
@inproceedings{boryan_deriving_2012,
title = {Deriving 2011 cultivated land cover data sets using usda {National} {Agricultural} {Statistics} {Service} historic {Cropland} {Data} {Layers}},
doi = {10.1109/IGARSS.2012.6352699},
abstract = {This paper describes the method used to derive 30 meter resolution 2011 US cultivated data sets based on multi-year National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data. This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. The strongest models for all states achieved overall (producer and user) accuracies greater than 94\% for cultivated and non cultivated categories.},
booktitle = {2012 {IEEE} {International} {Geoscience} and {Remote} {Sensing} {Symposium}},
author = {Boryan, C. and Yang, Z. and Di, L.},
month = jul,
year = {2012},
keywords = {Accuracy, agricultural engineering, agriculture, Agriculture, Buildings, CDL, crop mask, crops, cultivated data accuracy, cultivated data layer, cultivated land cover data sets, Data models, FSA CLU data, in situ 2011 Farm Service Agency Common Land Unit data, Information filtering, land cover, multi-year cultivated data layer, multiyear NASS cropland data layer data, Spatial resolution, terrain mapping, Training data, US cultivated data sets, USDA National Agricultural Statistics Service historic cropland data layers, vegetation mapping},
pages = {6297--6300},
file = {IEEE Xplore Abstract Record:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/SKI4VIZW/6352699.html:text/html;IEEE Xplore Full Text PDF:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/95D4TAGA/Boryan et al. - 2012 - Deriving 2011 cultivated land cover data sets usin.pdf:application/pdf}
}
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This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. The strongest models for all states achieved overall (producer and user) accuracies greater than 94% for cultivated and non cultivated categories.","booktitle":"2012 IEEE International Geoscience and Remote Sensing Symposium","author":[{"propositions":[],"lastnames":["Boryan"],"firstnames":["C."],"suffixes":[]},{"propositions":[],"lastnames":["Yang"],"firstnames":["Z."],"suffixes":[]},{"propositions":[],"lastnames":["Di"],"firstnames":["L."],"suffixes":[]}],"month":"July","year":"2012","keywords":"Accuracy, agricultural engineering, agriculture, Agriculture, Buildings, CDL, crop mask, crops, cultivated data accuracy, cultivated data layer, cultivated land cover data sets, Data models, FSA CLU data, in situ 2011 Farm Service Agency Common Land Unit data, Information filtering, land cover, multi-year cultivated data layer, multiyear NASS cropland data layer data, Spatial resolution, terrain mapping, Training data, US cultivated data sets, USDA National Agricultural Statistics Service historic cropland data layers, vegetation mapping","pages":"6297–6300","file":"IEEE Xplore Abstract Record:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/SKI4VIZW/6352699.html:text/html;IEEE Xplore Full Text PDF:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/95D4TAGA/Boryan et al. - 2012 - Deriving 2011 cultivated land cover data sets usin.pdf:application/pdf","bibtex":"@inproceedings{boryan_deriving_2012,\n\ttitle = {Deriving 2011 cultivated land cover data sets using usda {National} {Agricultural} {Statistics} {Service} historic {Cropland} {Data} {Layers}},\n\tdoi = {10.1109/IGARSS.2012.6352699},\n\tabstract = {This paper describes the method used to derive 30 meter resolution 2011 US cultivated data sets based on multi-year National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data. This paper presents different sets of rules (models) to build the cultivated data sets, and a comparison of the resulting cultivated data set accuracies to the accuracies of the original CDL input data. Nine models to create 2011 cultivated data sets for nine US states are tested. Each model provides a set of rules for merging pixels of multi-year (2007-2011) CDL data. The cultivated data accuracy was assessed against in situ 2011 Farm Service Agency (FSA) Common Land Unit (CLU) data. It was found that accuracies were close among the cultivated data generated using the different models. 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