REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN
Remote sensing is a rapid and reliable method for estimating crop growth data from individual plant to crops in irrigated agriculture ecosystem. The LAI is one of the important biophysical parameter for determining vegetation health, biomass, photosynthesis and evapotranspiration (ET) for the modell...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2012-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/367/2012/isprsarchives-XXXIX-B8-367-2012.pdf |
| _version_ | 1818317955516071936 |
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| author | I. Wittamperuma M. Hafeez M. Pakparvar J. Louis |
| author_facet | I. Wittamperuma M. Hafeez M. Pakparvar J. Louis |
| author_sort | I. Wittamperuma |
| collection | DOAJ |
| description | Remote sensing is a rapid and reliable method for estimating crop growth data from individual plant to crops in irrigated agriculture ecosystem. The LAI is one of the important biophysical parameter for determining vegetation health, biomass, photosynthesis and evapotranspiration (ET) for the modelling of crop yield and water productivity. Ground measurement of this parameter is tedious and time-consuming due to heterogeneity across the landscape over time and space. This study deals with the development of remote-sensing based empirical relationships for the estimation of ground-based LAI (LAI<sub>G</sub>) using NDVI, modelled with and without atmospheric correction models for three irrigated crops (corn, wheat and rice) grown in irrigated farms within Coleambally Irrigation Area (CIA) which is located in southern Murray Darling basin, NSW in Australia. Extensive ground truthing campaigns were carried out to measure crop growth and to collect field samples of LAI using LAI- 2000 Plant Canopy Analyser and reflectance using CROPSCAN Multi Spectral Radiometer at several farms within the CIA. A Set of 12 cloud free Landsat 5 TM satellite images for the period of 2010-11 were downloaded and regression analysis was carried out to analyse the co-relationships between satellite and ground measured reflectance and to check the reliability of data sets for the crops. Among all the developed regression relationships between LAI and NDVI, the atmospheric correction process has significantly improved the relationship between LAI and NDVI for Landsat 5 TM images. The regression analysis also shows strong correlations for corn and wheat but weak correlations for rice which is currently being investigated. |
| first_indexed | 2024-12-13T09:45:33Z |
| format | Article |
| id | doaj.art-9902dea3ed7642628d1b7aabdca83143 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-13T09:45:33Z |
| publishDate | 2012-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-9902dea3ed7642628d1b7aabdca831432022-12-21T23:52:05ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B836737310.5194/isprsarchives-XXXIX-B8-367-2012REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASINI. Wittamperuma0M. Hafeez1M. Pakparvar2J. Louis3School of Environmental Sciences, Charles Sturt University, Wagga Wagga NSW 2678, AustraliaSchool of Environmental Sciences, Charles Sturt University, Wagga Wagga NSW 2678, AustraliaFaculty of Bioscience Engineering Gent University, 673 Cupour Links, Gent 9000, BelgiumSchool of Computing and Mathematics, Charles Sturt University, Wagga Wagga NSW 2678, AustraliaRemote sensing is a rapid and reliable method for estimating crop growth data from individual plant to crops in irrigated agriculture ecosystem. The LAI is one of the important biophysical parameter for determining vegetation health, biomass, photosynthesis and evapotranspiration (ET) for the modelling of crop yield and water productivity. Ground measurement of this parameter is tedious and time-consuming due to heterogeneity across the landscape over time and space. This study deals with the development of remote-sensing based empirical relationships for the estimation of ground-based LAI (LAI<sub>G</sub>) using NDVI, modelled with and without atmospheric correction models for three irrigated crops (corn, wheat and rice) grown in irrigated farms within Coleambally Irrigation Area (CIA) which is located in southern Murray Darling basin, NSW in Australia. Extensive ground truthing campaigns were carried out to measure crop growth and to collect field samples of LAI using LAI- 2000 Plant Canopy Analyser and reflectance using CROPSCAN Multi Spectral Radiometer at several farms within the CIA. A Set of 12 cloud free Landsat 5 TM satellite images for the period of 2010-11 were downloaded and regression analysis was carried out to analyse the co-relationships between satellite and ground measured reflectance and to check the reliability of data sets for the crops. Among all the developed regression relationships between LAI and NDVI, the atmospheric correction process has significantly improved the relationship between LAI and NDVI for Landsat 5 TM images. The regression analysis also shows strong correlations for corn and wheat but weak correlations for rice which is currently being investigated.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/367/2012/isprsarchives-XXXIX-B8-367-2012.pdf |
| spellingShingle | I. Wittamperuma M. Hafeez M. Pakparvar J. Louis REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN |
| title_full | REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN |
| title_fullStr | REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN |
| title_full_unstemmed | REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN |
| title_short | REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN |
| title_sort | remote sensing based biophysical models for estimating lai of irrigated crops in murry darling basin |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/367/2012/isprsarchives-XXXIX-B8-367-2012.pdf |
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