AIRS level-2 CO_2 dataset (1–9 February 2010) - mid-tropospheric CO_2 Feb-1-9 2010

training_*.csv is training dataset. validation_*.csv is validation dataset.

Additional Information

Field	Value
Data last updated	August 11, 2019
Metadata last updated	August 8, 2019
Created	August 8, 2019
Format	zip,csv
License	Creative Commons Attribution
Datastore active	False
Has views	False
Id	e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c
Package id	57754d62-d037-4e94-88e9-b581078340e2
Position	0
State	active
Url type	upload

Field

Value

Data last updated

August 11, 2019

Metadata last updated

August 8, 2019

Created

August 8, 2019

Format

zip,csv

License

Creative Commons Attribution

Datastore active

False

Has views

False

e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c

Package id

57754d62-d037-4e94-88e9-b581078340e2

Position

State

active

Url type

upload

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async-timeout	4.0.3	https://github.com/aio-libs/async-timeout	Timeout context manager for asyncio programs
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certifi	2024.7.4	https://github.com/certifi/python-certifi	Python package for providing Mozilla's CA Bundle.
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package	{'author': 'J. Bradley, N. Cressie, T. Shi', 'author_email': 'bradley@stat.fsu.edu', 'creator_user_id': '0a859259-94bf-4ec3-a97f-dbb66600e927', 'id': '57754d62-d037-4e94-88e9-b581078340e2', 'isopen': True, 'license_id': 'cc-by', 'license_title': 'Creative Commons Attribution', 'license_url': 'http://www.opendefinition.org/licenses/cc-by', 'maintainer': 'Yi Cao', 'maintainer_email': 'ycao@uow.edu.au', 'metadata_created': '2019-08-08T02:24:35.966603', 'metadata_modified': '2019-08-29T00:30:18.127277', 'name': 'airs-co_2-feb-2010', 'notes': '## Description\r\n\r\nThis is a benchmark dataset for comparing a number of methods of spatial prediction, found in: A comparison of spatial predictors when datasets could be very large by Jonathan R. Bradley, Noel Cressie, and Tao Shi, which can be found [here](https://arxiv.org/abs/1410.7748). This dataset reports level-2 mid-tropospheric CO_2 values at a 17.6 km × 17.6 km spatial resolution, which is obtained from Atmospheric Infrared Sounder (AIRS) data retrieved from 1–9 February 2010. AIRS is a remote sensing instrument on board the Aqua satellite administered by the National Aeronautics and Space Administration (NASA). Among other measurements, it collects CO_2 measurements in the form\r\nof spectra (level 1) that are then converted to mid-tropospheric CO_2 values (level 2) given in units of parts per\r\nmillion (ppm). \r\n\r\nThis dataset is in the form given by Bradley et al. (2016) and is freely available under the Creative Commons Attribution 4.0 Australia License.\r\n\r\nThe ZIP file contains three folders, "Small," "Large," and "VeryLarge," the data in these folders are used in a comparison study in Section 4 of Bradley et al. (2016). \r\n\r\nIn each folder, there are two excel csv files, respectively for the training and the validation datasets. In each excel file, the first two columns are the latitude and longitude, respectively. The third column is mid-tropospheric CO_2 in ppm.\r\n\r\n## Reference\r\n\r\nBradley, J.R., Cressie, N., and Shi, T. (2016). A comparison of spatial predictors when datasets could be very large. Statistics Surveys, 10, 100-131. ', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'AIRS level-2 CO_2 dataset (1–9 February 2010)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2019-08-08T02:30:15.577326', 'datastore_active': False, 'description': 'training_\\.csv is training dataset.\r\nvalidation_\\.csv is validation dataset.', 'format': 'zip,csv', 'hash': '', 'id': 'e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c', 'last_modified': '2019-08-11T23:55:15.243134', 'metadata_modified': '2019-08-08T02:30:15.577326', 'mimetype': None, 'mimetype_inner': None, 'name': 'mid-tropospheric CO_2 Feb-1-9 2010', 'package_id': '57754d62-d037-4e94-88e9-b581078340e2', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/57754d62-d037-4e94-88e9-b581078340e2/resource/e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c/download/mid-tropospheric-co2-feb-1-9-2010-data.zip', 'url_type': 'upload', 'has_views': False}], 'tags': [{'display_name': 'CO_2', 'id': '9a472202-7e3e-445f-8d27-d22779a94976', 'name': 'CO_2', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Methodology', 'id': 'a103ee7b-9814-4ec5-a6b6-b1373adb7f5a', 'name': 'Methodology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial dataset', 'id': '1163b337-bc2f-4785-b197-161ed708d694', 'name': 'spatial dataset', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}
pkg	<Package id=57754d62-d037-4e94-88e9-b581078340e2 name=airs-co_2-feb-2010 title=AIRS level-2 CO_2 dataset (1–9 February 2010) version= url= author=J. Bradley, N. Cressie, T. Shi author_email=bradley@stat.fsu.edu maintainer=Yi Cao maintainer_email=ycao@uow.edu.au notes=## Description This is a benchmark dataset for comparing a number of methods of spatial prediction, found in: A comparison of spatial predictors when datasets could be very large by Jonathan R. Bradley, Noel Cressie, and Tao Shi, which can be found [here](https://arxiv.org/abs/1410.7748). This dataset reports level-2 mid-tropospheric CO_2 values at a 17.6 km × 17.6 km spatial resolution, which is obtained from Atmospheric Infrared Sounder (AIRS) data retrieved from 1–9 February 2010. AIRS is a remote sensing instrument on board the Aqua satellite administered by the National Aeronautics and Space Administration (NASA). Among other measurements, it collects CO_2 measurements in the form of spectra (level 1) that are then converted to mid-tropospheric CO_2 values (level 2) given in units of parts per million (ppm). This dataset is in the form given by Bradley et al. (2016) and is freely available under the Creative Commons Attribution 4.0 Australia License. The ZIP file contains three folders, "Small," "Large," and "VeryLarge," the data in these folders are used in a comparison study in Section 4 of Bradley et al. (2016). In each folder, there are two excel csv files, respectively for the training and the validation datasets. In each excel file, the first two columns are the latitude and longitude, respectively. The third column is mid-tropospheric CO_2 in ppm. ## Reference Bradley, J.R., Cressie, N., and Shi, T. (2016). A comparison of spatial predictors when datasets could be very large. Statistics Surveys, 10, 100-131. license_id=cc-by type=dataset owner_org=4207b363-dfff-475d-a24c-fd97ca7f9e9a creator_user_id=0a859259-94bf-4ec3-a97f-dbb66600e927 metadata_created=2019-08-08 02:24:35.966603 metadata_modified=2019-08-29 00:30:18.127277 private=False state=active plugin_data=None>
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mid-tropospheric CO_2 Feb-1-9 2010

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ckan.site_about	'INTRODUCTION BY DIRECTOR: PROFESSOR Marijka Batterham \r\n----------------------\r\n\r\nThe National Institute for Applied Statistics Research Australia (NIASRA) at the University of Wollongong aims to identify Australia as a place where the discipline of applied statistics collaborates with academics and professionals in science, government, business and industry to tackle strategic problems. Methods for obtaining relevant and reliable data and methods that can be used to extract the information and evidence that the data can provide are fundamental in solving important and complex problems facing society. The huge increase in data available in all fields and relating to every issue challenging a modern society means that there are large gaps between the methods needed to fully exploit these data and the methods available to do so. New statistical methods are needed to handle uncertainty and risk in large and complex data structures and to generate knowledge that can be acted upon. NIASRA is undertaking a program of research developing new statistical methods for obtaining and analysing data relevant to agriculture, energy, engineering, environmental sciences, finance, health, medicine, mining, natural resources, and social sciences. The Institute aims to provide leading-edge research and consulting capacity in applied statistics for Australia and our region through the skills and activities of its staff and research students. \r\n \r\n\r\nNIASRA is committed to developing and applying innovative statistical methods to important problems. It conducts: \r\n\r\n- fundamental methodological research; \r\n- industry-focused and contract research; \r\n- major consulting projects;\r\n- professional education and training. \r\n \r\nNIASRA’s research is focused in Biometry and Bioinformatics, Environmental Informatics, Survey Methodology, and also research in Statistical Education and Statistical and Mathematical Methodology in Finance. It is led by Director Prof David Steel and includes: \r\n\r\n- Centre for Bioinformatics and Biometrics Research – Director Prof Brian Cullis;\r\n- Centre for Environmental Informatics – Director Distinguished Prof Noel Cressie;\r\n- Centre for Sample Survey Methodology – Director Prof Ray Chambers;\r\n- Statistical Consulting Centre - Director A/Professor Marijka Batterham, focussing on support for research within the University in design and analysis.\r\n \r\nThe institute is a Research Strength of the University of Wollongong and has over 20 academic staff members and 25 research students. It has been successful in developing long-term collaborative partnerships. It has two externally funded research professors: Professor Chambers is funded by the Australian Bureau of Statistics and Professor Brian Cullis is funded by CSIRO and the Grains Research Development Corporation. It has formal partnerships with the NZ Ministry of Health and the Australian Market and Social Research Society. \r\n \r\n\r\nThe themes that underpin the research at NIASRA are:\r\n\r\n- statistical design - developing efficient methods of obtaining relevant and reliable data in surveys, experiments, and other data collections;\r\n- complexity of data arising from observations in large scale real populations – often involving hierarchical or auto-correlated data - and computational methods to handle such data; and\r\n- working with major organisations on significant problems. \r\n \r\nInternationally competitive areas of methodological research include: statistical design - survey and experimental design; analysis of complex data from complex populations - survey, biometric, environmental, longitudinal, spatial, aggregated data, and also combining data; statistical modelling – methods for spatial, temporal and spatial-temporal data, semi-parametric and nonparametric methods, time series, quasi-likelihood, multi-level modelling, Bayesian analysis, and estimating equations;\r\ndata quality and survey methods - particularly telephone, household, internet and environmental surveys;\r\nstatistical confidentiality.\r\n \r\nNIASRA offers postgraduate and professional education courses and programs that build on our world-class staff, extensive experience and industry collaborations.'
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/dataset/<id>/resource/<resource_id>/edit	dataset_resource.edit	GET, HEAD, OPTIONS, POST	False	None
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/dataset/new	dataset.new	GET, HEAD, OPTIONS, POST	False	None
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/group/changes_multiple	activity.group_changes_multiple	GET, HEAD, OPTIONS	False	None
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/group/follow/<id>	group.follow	OPTIONS, POST	False	None
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/group/member_delete/<id>	group.member_delete	GET, HEAD, OPTIONS, POST	False	None
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/no/	home.redirect_locale	GET, HEAD, OPTIONS	False	None
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/organization/activity/<id>	activity.organization_activity	GET, HEAD, OPTIONS	False	None
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/organization/delete/<id>	organization.delete	GET, HEAD, OPTIONS, POST	False	None
/organization/edit/<id>	organization.edit	GET, HEAD, OPTIONS, POST	False	None
/organization/follow/<id>	organization.follow	OPTIONS, POST	False	None
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package	{'author': 'J. Bradley, N. Cressie, T. Shi', 'author_email': 'bradley@stat.fsu.edu', 'creator_user_id': '0a859259-94bf-4ec3-a97f-dbb66600e927', 'id': '57754d62-d037-4e94-88e9-b581078340e2', 'isopen': True, 'license_id': 'cc-by', 'license_title': 'Creative Commons Attribution', 'license_url': 'http://www.opendefinition.org/licenses/cc-by', 'maintainer': 'Yi Cao', 'maintainer_email': 'ycao@uow.edu.au', 'metadata_created': '2019-08-08T02:24:35.966603', 'metadata_modified': '2019-08-29T00:30:18.127277', 'name': 'airs-co_2-feb-2010', 'notes': '## Description\r\n\r\nThis is a benchmark dataset for comparing a number of methods of spatial prediction, found in: A comparison of spatial predictors when datasets could be very large by Jonathan R. Bradley, Noel Cressie, and Tao Shi, which can be found [here](https://arxiv.org/abs/1410.7748). This dataset reports level-2 mid-tropospheric CO_2 values at a 17.6 km × 17.6 km spatial resolution, which is obtained from Atmospheric Infrared Sounder (AIRS) data retrieved from 1–9 February 2010. AIRS is a remote sensing instrument on board the Aqua satellite administered by the National Aeronautics and Space Administration (NASA). Among other measurements, it collects CO_2 measurements in the form\r\nof spectra (level 1) that are then converted to mid-tropospheric CO_2 values (level 2) given in units of parts per\r\nmillion (ppm). \r\n\r\nThis dataset is in the form given by Bradley et al. (2016) and is freely available under the Creative Commons Attribution 4.0 Australia License.\r\n\r\nThe ZIP file contains three folders, "Small," "Large," and "VeryLarge," the data in these folders are used in a comparison study in Section 4 of Bradley et al. (2016). \r\n\r\nIn each folder, there are two excel csv files, respectively for the training and the validation datasets. In each excel file, the first two columns are the latitude and longitude, respectively. The third column is mid-tropospheric CO_2 in ppm.\r\n\r\n## Reference\r\n\r\nBradley, J.R., Cressie, N., and Shi, T. (2016). A comparison of spatial predictors when datasets could be very large. Statistics Surveys, 10, 100-131. ', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'AIRS level-2 CO_2 dataset (1–9 February 2010)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2019-08-08T02:30:15.577326', 'datastore_active': False, 'description': 'training_\\.csv is training dataset.\r\nvalidation_\\.csv is validation dataset.', 'format': 'zip,csv', 'hash': '', 'id': 'e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c', 'last_modified': '2019-08-11T23:55:15.243134', 'metadata_modified': '2019-08-08T02:30:15.577326', 'mimetype': None, 'mimetype_inner': None, 'name': 'mid-tropospheric CO_2 Feb-1-9 2010', 'package_id': '57754d62-d037-4e94-88e9-b581078340e2', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/57754d62-d037-4e94-88e9-b581078340e2/resource/e84a6a7c-c6a7-4e88-9ff0-b68ffbf6e32c/download/mid-tropospheric-co2-feb-1-9-2010-data.zip', 'url_type': 'upload', 'has_views': False}], 'tags': [{'display_name': 'CO_2', 'id': '9a472202-7e3e-445f-8d27-d22779a94976', 'name': 'CO_2', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Methodology', 'id': 'a103ee7b-9814-4ec5-a6b6-b1373adb7f5a', 'name': 'Methodology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial dataset', 'id': '1163b337-bc2f-4785-b197-161ed708d694', 'name': 'spatial dataset', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}
pkg	<Package id=57754d62-d037-4e94-88e9-b581078340e2 name=airs-co_2-feb-2010 title=AIRS level-2 CO_2 dataset (1–9 February 2010) version= url= author=J. Bradley, N. Cressie, T. Shi author_email=bradley@stat.fsu.edu maintainer=Yi Cao maintainer_email=ycao@uow.edu.au notes=## Description This is a benchmark dataset for comparing a number of methods of spatial prediction, found in: A comparison of spatial predictors when datasets could be very large by Jonathan R. Bradley, Noel Cressie, and Tao Shi, which can be found [here](https://arxiv.org/abs/1410.7748). This dataset reports level-2 mid-tropospheric CO_2 values at a 17.6 km × 17.6 km spatial resolution, which is obtained from Atmospheric Infrared Sounder (AIRS) data retrieved from 1–9 February 2010. AIRS is a remote sensing instrument on board the Aqua satellite administered by the National Aeronautics and Space Administration (NASA). Among other measurements, it collects CO_2 measurements in the form of spectra (level 1) that are then converted to mid-tropospheric CO_2 values (level 2) given in units of parts per million (ppm). This dataset is in the form given by Bradley et al. (2016) and is freely available under the Creative Commons Attribution 4.0 Australia License. The ZIP file contains three folders, "Small," "Large," and "VeryLarge," the data in these folders are used in a comparison study in Section 4 of Bradley et al. (2016). In each folder, there are two excel csv files, respectively for the training and the validation datasets. In each excel file, the first two columns are the latitude and longitude, respectively. The third column is mid-tropospheric CO_2 in ppm. ## Reference Bradley, J.R., Cressie, N., and Shi, T. (2016). A comparison of spatial predictors when datasets could be very large. Statistics Surveys, 10, 100-131. license_id=cc-by type=dataset owner_org=4207b363-dfff-475d-a24c-fd97ca7f9e9a creator_user_id=0a859259-94bf-4ec3-a97f-dbb66600e927 metadata_created=2019-08-08 02:24:35.966603 metadata_modified=2019-08-29 00:30:18.127277 private=False state=active plugin_data=None>
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