Estimation and validation of Leaf Area Index time series for crops on 5m scale from space
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| Title: | Main Title: Estimation and validation of Leaf Area Index time series for crops on 5m scale from space |
| Description: | Abstract: Time series of Leaf Area Index (LAI) is of utmost importance for various disciplines of bio and geosciences where satellite remote sensing makes LAI estimation possible for large areas in less time and resources. Remote sensing LAI, validated against in situ LAI, is used as base for calculating LAI for large areas e.g. on catchment scale. To have an in situ LAI reference for satellite data, two different LAI meters i.e. LAI2200 and delta-T SunScan and one destructive method was used at different places inside winter wheat fields at two different location in the vicinity of Rur river. To test the impact of radiometric normalization for calculating vegetation indices on a time series of satellite images, pre and post radiometric normalization LAI was compared. Prior to vegetation indices calculation, radiometric normalization was applied to the time series of RapidEye data but here is no sufficient improvement in correlation coefficient between remote sensing based LAI and destructive LAI except than smoothening the LAI temporal plot and removing invalid below zero LAI values. Utilization of the unique red-edge spectral band (0.690 – 0.730 μm) in several vegetation indices was also tested in this paper for accurate estimation of LAI, but it did not show any promising results. SAVI (Soil Adjusted vegetation Index) presents good correlation between remote sensing based predicted LAI against destructive LAI for two test sites in winter wheat fields (for Selhausen R² = 0.73 and for Merzenhausen R² = 0.97). More precise and high resolution estimation of LAI for large areas is of vital importance for improving hydrological models and soil moisture estimation in radiometric transfer models. |
Responsible Party
| Creator: | Muhammad Ali (Author) |
| Publisher: | CRC/TR32 Database (TR32DB) |
| Publication Year: | 2013 |
Topic
| TR32 Topic: | Remote Sensing |
| Related Subproject: | C6 |
| Subject: | Keyword: PhD Report |
File Details
| Filename: | Report2_Ali_2012.pdf |
| Data Type: | Text - Text |
| File Size: | 658 KB |
| Date: | Available: 31.12.2012 |
| Mime Type: | application/pdf |
| Data Format: | |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Only Project Members |
| General Access and Use Conditions: | For internal use only. |
| Access Limitations: | For internal use only. |
| Licence: | [TR32DB] Data policy agreement |
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Specific Information - Report
| Report Date: | 31st of December, 2012 |
| Report Type: | PhD Report |
| Report City: | Jülich, Germany |
| Report Institution: | Institute of Bio and Geosciences Agrosphere (IBG-3), Research Center Jülich |
| Number of Pages: | 24 (1 - 24) |
| Further Information: | TR32 Student Report Phase II |
Metadata Details
| Metadata Creator: | Muhammad Ali |
| Metadata Created: | 04.12.2013 |
| Metadata Last Updated: | 04.12.2013 |
| Subproject: | C6 |
| Funding Phase: | 2 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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Dataset Statistics
| Page Visits: | 1128 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 3 |
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