Site-specific management of common olive
作者： Omid Noori , Sudhanshu Sekhar Panda
DOI: 10.1016/J.COMPAG.2016.07.031
关键词:
摘要: The goal of this paper was to determine the correlation between image digital information and healthy olive trees management.Many data were gathered from tree soil. Such as: fruit set, canopy volume (CV), shoot length (SL), trunk diameter (TD), height (TH), SPAD, LAI, leaf dry matter percent, N K in leaves.Numerous multivariate regression models running showed pixel value combinations have highly with growth parameters.Multicollinearity analyses completed on input parameters reduce redundancy usage. Site-specific crop management (SSCM) is a part precision agriculture which helping increase production minimal input. It has enhanced cost-benefit scenario production. main use advanced geospatial techniques acquisition, remote sensing (RS), processing, geographic systems (GIS), global positioning (GPS) statistical modeling characteristics. be noted that assumptions based overall greenness as trees. This research carried out during 2012-2014 an irrigated orchards located Tarom region, Zanjan province Iran. following gathered: set percent shoot, soil plant analysis development (SPAD), area index (LAI), (LDMP), properties like nitrogen (N) potassium (K) content leaves, properties/characteristics amount Clay, Silt, Sand, Sodium adsorption rate (SAR), organic (OM), available phosphorous (Pav), (Kav), boron (B), total neutralizing (TNV), electrical conductivity (EC), chloride (Cl), iron (Feav). Advanced land observing satellite-Advanced visible near infrared radiometer type 2 (ALOS-AVNIR-2) used experiment. A six clusters existing compacted parcel chosen. indices developed for study normalized vegetation (NDVI), newly vegetative vigor (VVI) adjusted (SAVI). Multivariate using remotely sensed values relation site specific mentioned above. As stated above, individual band DN statistics characteristics such CV, SL, TD, TH, LDMP output development. Multicollinearity related variables shows VVI b1 are correlated other variables. also observed NDVI - b3 b2-b4 hence omitted parameter list. SAVI along (Green, Red Infrared bands) TH SPAD provided excellent coefficient determination (R2) 0.98, 0.99 0.99, respectively. SAVI, Red-, Green-, Blue-band together best estimated R2 0.84. Similarly, SL LA 0.88 0.96, NDVI, 0.98. same predicted maximum (R2=0.99). Similarly correlations (R2=0.99 0.79, respectively) Blue-band. Algorithms could by farmers or orhard managers estimating physical similar environmental conditions prevailed our imagery non-invasive, economic, efficient manner.
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