File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/JSTARS.2013.2264870
- Scopus: eid_2-s2.0-84894595974
- WOS: WOS:000331457400007
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Improving LAI mapping by integrating MODIS and CYCLOPES LAI products using optimal interpolation
Title | Improving LAI mapping by integrating MODIS and CYCLOPES LAI products using optimal interpolation |
---|---|
Authors | |
Keywords | CYCLOPES Data fusion LAI MODIS Optimal interpolation |
Issue Date | 2014 |
Citation | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, v. 7, n. 2, p. 445-457 How to Cite? |
Abstract | Leaf area index (LAI) is an important land surface biophysical variable used to characterize vegetation amount and activity. Current satellite LAI products, however, do not satisfy the requirements of the modeling community due to their large uncertainties and frequent missing values. There is an urgent need for advanced methods to integrate multiple LAI products to improve the product's accuracy and integrity for various applications. To meet this need, this study proposes a method based on Optimal Interpolation (OI) to integrate MODIS true LAI and CYCLOPES effective LAI retrievals. Multiple years' LAI means and variances (LAI climatology) are pre-calculated and used as the baseline for data integration. The locally adjusted cubic-spline capping algorithm is used to smooth the climatology data. An LAI normalization scheme, based on a linear measurement error model, is developed to account for the systematic difference between the two products and to generate the LAI predictions. This integration process removes the unrealistically large temporal variations of the original LAI products. The data gaps are filled with information from adjacent pixels and the prior knowledge acquired from multiyear climatology. A spatially and temporally continuous true LAI data set is generated. High resolution reference maps of true LAI are collected to validate the two true LAI data sets: MODIS LAI product and the integrated LAI values. The validation results suggest that the integrated results agree better with the LAI reference maps than the MODIS LAI product, showing higher R2, smaller bias and root mean squared error. © 2013 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/321567 |
ISSN | 2023 Impact Factor: 4.7 2023 SCImago Journal Rankings: 1.434 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Dongdong | - |
dc.contributor.author | Liang, Shunlin | - |
dc.date.accessioned | 2022-11-03T02:19:49Z | - |
dc.date.available | 2022-11-03T02:19:49Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, v. 7, n. 2, p. 445-457 | - |
dc.identifier.issn | 1939-1404 | - |
dc.identifier.uri | http://hdl.handle.net/10722/321567 | - |
dc.description.abstract | Leaf area index (LAI) is an important land surface biophysical variable used to characterize vegetation amount and activity. Current satellite LAI products, however, do not satisfy the requirements of the modeling community due to their large uncertainties and frequent missing values. There is an urgent need for advanced methods to integrate multiple LAI products to improve the product's accuracy and integrity for various applications. To meet this need, this study proposes a method based on Optimal Interpolation (OI) to integrate MODIS true LAI and CYCLOPES effective LAI retrievals. Multiple years' LAI means and variances (LAI climatology) are pre-calculated and used as the baseline for data integration. The locally adjusted cubic-spline capping algorithm is used to smooth the climatology data. An LAI normalization scheme, based on a linear measurement error model, is developed to account for the systematic difference between the two products and to generate the LAI predictions. This integration process removes the unrealistically large temporal variations of the original LAI products. The data gaps are filled with information from adjacent pixels and the prior knowledge acquired from multiyear climatology. A spatially and temporally continuous true LAI data set is generated. High resolution reference maps of true LAI are collected to validate the two true LAI data sets: MODIS LAI product and the integrated LAI values. The validation results suggest that the integrated results agree better with the LAI reference maps than the MODIS LAI product, showing higher R2, smaller bias and root mean squared error. © 2013 IEEE. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | - |
dc.subject | CYCLOPES | - |
dc.subject | Data fusion | - |
dc.subject | LAI | - |
dc.subject | MODIS | - |
dc.subject | Optimal interpolation | - |
dc.title | Improving LAI mapping by integrating MODIS and CYCLOPES LAI products using optimal interpolation | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/JSTARS.2013.2264870 | - |
dc.identifier.scopus | eid_2-s2.0-84894595974 | - |
dc.identifier.volume | 7 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 445 | - |
dc.identifier.epage | 457 | - |
dc.identifier.eissn | 2151-1535 | - |
dc.identifier.isi | WOS:000331457400007 | - |