Good practices for estimating area and assessing accuracy of land change
The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are cr...
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| Format: | Article |
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Elsevier
2014
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| Online Access: | https://eprints.nottingham.ac.uk/44846/ |
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| author | Olofsson, Pontus Foody, Giles M. Herold, Martin Stehman, Stephen V. Woodcock, Curtis E. Wulder, Michael A. |
| author_facet | Olofsson, Pontus Foody, Giles M. Herold, Martin Stehman, Stephen V. Woodcock, Curtis E. Wulder, Michael A. |
| author_sort | Olofsson, Pontus |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are critical to ensure the integrity of land change information. We provide practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data. The good practice recommendations address the three major components: sampling design, response design and analysis. The primary good practice recommendations for assessing accuracy and estimating area are: (i) implement a probability sampling design that is chosen to achieve the priority objectives of accuracy and area estimation while also satisfying practical constraints such as cost and available sources of reference data; (ii) implement a response design protocol that is based on reference data sources that provide sufficient spatial and temporal representation to accurately label each unit in the sample (i.e., the “reference classification” will be considerably more accurate than the map classification being evaluated); (iii) implement an analysis that is consistent with the sampling design and response design protocols; (iv) summarize the accuracy assessment by reporting the estimated error matrix in terms of proportion of area and estimates of overall accuracy, user's accuracy (or commission error), and producer's accuracy (or omission error); (v) estimate area of classes (e.g., types of change such as wetland loss or types of persistence such as stable forest) based on the reference classification of the sample units; (vi) quantify uncertainty by reporting confidence intervals for accuracy and area parameters; (vii) evaluate variability and potential error in the reference classification; and (viii) document deviations from good practice that may substantially affect the results. An example application is provided to illustrate the recommended process. |
| first_indexed | 2025-11-14T19:57:06Z |
| format | Article |
| id | nottingham-44846 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:57:06Z |
| publishDate | 2014 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-448462020-05-04T16:47:38Z https://eprints.nottingham.ac.uk/44846/ Good practices for estimating area and assessing accuracy of land change Olofsson, Pontus Foody, Giles M. Herold, Martin Stehman, Stephen V. Woodcock, Curtis E. Wulder, Michael A. The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs. Statistically robust and transparent approaches for assessing accuracy and estimating area of change are critical to ensure the integrity of land change information. We provide practitioners with a set of “good practice” recommendations for designing and implementing an accuracy assessment of a change map and estimating area based on the reference sample data. The good practice recommendations address the three major components: sampling design, response design and analysis. The primary good practice recommendations for assessing accuracy and estimating area are: (i) implement a probability sampling design that is chosen to achieve the priority objectives of accuracy and area estimation while also satisfying practical constraints such as cost and available sources of reference data; (ii) implement a response design protocol that is based on reference data sources that provide sufficient spatial and temporal representation to accurately label each unit in the sample (i.e., the “reference classification” will be considerably more accurate than the map classification being evaluated); (iii) implement an analysis that is consistent with the sampling design and response design protocols; (iv) summarize the accuracy assessment by reporting the estimated error matrix in terms of proportion of area and estimates of overall accuracy, user's accuracy (or commission error), and producer's accuracy (or omission error); (v) estimate area of classes (e.g., types of change such as wetland loss or types of persistence such as stable forest) based on the reference classification of the sample units; (vi) quantify uncertainty by reporting confidence intervals for accuracy and area parameters; (vii) evaluate variability and potential error in the reference classification; and (viii) document deviations from good practice that may substantially affect the results. An example application is provided to illustrate the recommended process. Elsevier 2014-05-25 Article PeerReviewed Olofsson, Pontus, Foody, Giles M., Herold, Martin, Stehman, Stephen V., Woodcock, Curtis E. and Wulder, Michael A. (2014) Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148 . pp. 42-57. ISSN 1879-0704 Accuracy assessment; Sampling design; Response design; Area estimation; Land change; Remote sensing http://www.sciencedirect.com/science/article/pii/S0034425714000704 doi:10.1016/j.rse.2014.02.015 doi:10.1016/j.rse.2014.02.015 |
| spellingShingle | Accuracy assessment; Sampling design; Response design; Area estimation; Land change; Remote sensing Olofsson, Pontus Foody, Giles M. Herold, Martin Stehman, Stephen V. Woodcock, Curtis E. Wulder, Michael A. Good practices for estimating area and assessing accuracy of land change |
| title | Good practices for estimating area and assessing accuracy of land change |
| title_full | Good practices for estimating area and assessing accuracy of land change |
| title_fullStr | Good practices for estimating area and assessing accuracy of land change |
| title_full_unstemmed | Good practices for estimating area and assessing accuracy of land change |
| title_short | Good practices for estimating area and assessing accuracy of land change |
| title_sort | good practices for estimating area and assessing accuracy of land change |
| topic | Accuracy assessment; Sampling design; Response design; Area estimation; Land change; Remote sensing |
| url | https://eprints.nottingham.ac.uk/44846/ https://eprints.nottingham.ac.uk/44846/ https://eprints.nottingham.ac.uk/44846/ |