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Remote sensing application that used integrated with environmentally factors for oil palm yield estimating using Worldview-2 Imagery vegetation index (VI) was done. The aims of this study to get : 1) Red Edge Normalized Different Vegetation Index (RENDVI) and C h l o r o p h y l l I n d e x R e d E d g e ( C IRE ) ; 2) Correlation both of VI and oil palm yield; 3) oil palm yield estimation. The methods that used in this study were VI calculation by using RENDVI [(λNIR -λRED EDGE)/(λNIR +λRED EDGE )] and CIRE = [(λNIR /λRED EDGE )-1]. Oil EDGE NIR RED EDGE NIR RED EDGE palm yield estimation done by using linier regression and multiple linier regression. Linier regression used oil palm yield as dependent factor (Y) and VI as independent factor. Multiple linier regression used oil palm yield as dependent factor (Y), vegetative factors (oil palm yield, population per hectars, leaf area index) and environmentally factor (% clay, soil fertility index, altitude and water balance) as independent factors. The results of this study were: 1) the RENDVI value range -1 to 0.493 with average 0.30; while the CIRE value range -1 until 1.845 with average value 0.85. 2) The RENDVI dan CIRE have low positive linier correlation with oil pal yield rendah (rRENDVI = 0.355 dan rCIRE = 0.354); 3) Oil palm RENDVI CIRE yield estimation that using RENDVI and CIRE , vegetatation factors, environmentally factors data integration have similar correlation (r=0.763). Overall estimation model accuration get more than 90% estimation accuration on current month.
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