| dc.contributor.author | Thenkabail, P. |
| dc.contributor.author | Ward, A.D. |
| dc.contributor.author | Lyon, J. |
| dc.date.accessioned | 2019-12-04T11:33:15Z |
| dc.date.available | 2019-12-04T11:33:15Z |
| dc.date.issued | 1994 |
| dc.identifier.citation | Thenkabail, P., Ward, A.D. & Lyon, J. (1994). Landsat- 5 thematic mapper models of soybean and corn crop characteristics. International Journal of Remote Sensing, 15(1), 49-61. |
| dc.identifier.issn | 0143-1161 |
| dc.identifier.uri | https://hdl.handle.net/20.500.12478/5589 |
| dc.description.abstract | This study used Landsat-5 Thematic Mapper (TM) data to develop empirical models for determining soybean and corn crop yield, leaf area index, wet biomass, dry biomass and plant height. Ground-truth data was obtained from more than 50 commercial farms in Ohio, USA, during 1988 and 1989. Several significant linear, non-linear, logarithmic, exponential, and power models were developed. The best soybean models generally comprised of information from the commonly-used bands 3 and 4. TM data for the most significant soybean models explained 69 to 76 per cent of the between field variability in wet biomass, dry biomass, and plant height, 63 per cent of the variability in leaf area index, and 35 per cent of the variability in yield. The best corn models incorporated band 5 and/or band 7 along with band 4. The most significant corn models explained 80 per cent of the variability in wet biomass, 66 to 67 per cent of the variability in dry biomass, plant height, and leaf area index, and 52 per cent of the variability in yield. A new cubed ratio vegetation index, (TM4/TM5)3, was found to be particularly useful for modelling corn characteristics. |
| dc.language.iso | en |
| dc.subject | Data |
| dc.subject | Yields |
| dc.subject | Soybeans |
| dc.title | Landsat 5 thematic mapper models of soybean and corn crop characteristics |
| dc.type | Journal Article |
| dc.description.version | Peer Review |
| cg.contributor.affiliation | International Institute of Tropical Agriculture |
| cg.contributor.affiliation | Ohio State University |
| cg.coverage.region | Africa |
| cg.coverage.region | Acp |
| cg.coverage.region | West Africa |
| cg.coverage.region | North America |
| cg.coverage.country | Nigeria |
| cg.coverage.country | United States |
| cg.isijournal | ISI Journal |
| cg.authorship.types | CGIAR and advanced research institute |
| cg.iitasubject | Research Method |
| cg.iitasubject | Plant Production |
| cg.iitasubject | Soybean |
| cg.iitasubject | Food Security |
| cg.accessibilitystatus | Limited Access |
| local.dspaceid | 104869 |
| cg.identifier.doi | https://doi.org/10.1080/01431169408954050 |
