Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes
Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-09-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/7/9/11992 |
| _version_ | 1818321502098948096 |
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| author | Heinz Gallaun Martin Steinegger Roland Wack Mathias Schardt Birgit Kornberger Ursula Schmitt |
| author_facet | Heinz Gallaun Martin Steinegger Roland Wack Mathias Schardt Birgit Kornberger Ursula Schmitt |
| author_sort | Heinz Gallaun |
| collection | DOAJ |
| description | Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging. |
| first_indexed | 2024-12-13T10:41:55Z |
| format | Article |
| id | doaj.art-83b12d1522504e8c8bba33a05e836a6e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:41:55Z |
| publishDate | 2015-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-83b12d1522504e8c8bba33a05e836a6e2022-12-21T23:50:27ZengMDPI AGRemote Sensing2072-42922015-09-0179119921200810.3390/rs70911992rs70911992Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover ChangesHeinz Gallaun0Martin Steinegger1Roland Wack2Mathias Schardt3Birgit Kornberger4Ursula Schmitt5Remote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaRemote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaRemote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaRemote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaRemote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaRemote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, Graz A-8010, AustriaLand cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.http://www.mdpi.com/2072-4292/7/9/11992land cover changedeforestationREDD monitoringaccuracy assessmentarea estimationsamplingbootstrappingconfidence interval |
| spellingShingle | Heinz Gallaun Martin Steinegger Roland Wack Mathias Schardt Birgit Kornberger Ursula Schmitt Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes Remote Sensing land cover change deforestation REDD monitoring accuracy assessment area estimation sampling bootstrapping confidence interval |
| title | Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes |
| title_full | Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes |
| title_fullStr | Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes |
| title_full_unstemmed | Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes |
| title_short | Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes |
| title_sort | remote sensing based two stage sampling for accuracy assessment and area estimation of land cover changes |
| topic | land cover change deforestation REDD monitoring accuracy assessment area estimation sampling bootstrapping confidence interval |
| url | http://www.mdpi.com/2072-4292/7/9/11992 |
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