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Field Perspectral Remote Sensing Data To Dagnose Crop Variables Tropical Irrigated Wetland Rice
Oleh:
Evri, Muhammad
;
Sadly, Muhamad
Jenis:
Article from Journal - ilmiah nasional - terakreditasi DIKTI
Dalam koleksi:
Makara Seri Sains vol. 13 no. 2 (Nov. 2009)
,
page 141-150.
Topik:
Hyperspectrcal Vegetation Indices
;
LAI
;
LDW
;
Rice
;
SPAD Value
Ketersediaan
Perpustakaan Pusat (Semanggi)
Nomor Panggil:
MM65
Non-tandon:
1 (dapat dipinjam: 0)
Tandon:
tidak ada
Lihat Detail Induk
Isi artikel
Measurement of canopy spectral (400-980 nm) using ground-based hyperspectrcal device and the crop variables of rice such as leaf area index (LAI), leaf dry weight (LDW) and SPAD values were measured periodocally during growth season with involving three rice cultivars (Pandanwangi, Ciherang and IR Jumbo) and four nitrogen (N) application levels (N0, N80, N92 and N103 kg/ha). This study explored all possible combination wavebands tested in hyperspectrcal-based vegetation indices (HVIs) and to develop the relationship model between HVIs with crop variables. Several HVIs used are NDVI (Normalized Diffrence Vegetation Index), RDVI (Renormalized Difference Vegetation Index), RVI (Ratio Vegetation Index) and SAVI (Soil Adjusted Vegetation Index). Analysis of pairing waveband used in HVIs was investigated with 6.786 combinations to gain optimal waveband. NDVI shown the highest R2 values for LAI were found in band combinations from green to red region (500nm to 730 nm). Validation model using FDR implied better accuracy to estimate LAI using whole season data (R2=0.856), however, inversely for LDW and SPAD values, validation using reflectance data indicated better accuracy to predict LDW and SPAD values. Model using SAVI denoted the highest values (R2=0.856) for predicting LAI Validation of model using RVI implied the highest value (R2=0.797) for predicting LDW. Testing model using SAVI indicated the highest value (R2=0.658) for predicting SPAD values. RVI has the best accuracy to validate the model of LAI than of LDW or SPAD values.
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