Chlorophyll is a significant indicator of plant vigor and plant health which enables to estimate final crop yield. Current experiment was conducted to acquire high resolution multispectral image from UAV and accurately estimate chlorophyll contents using spectral chlorophyll indices in vertical crop plantation. Ground truthing was performed by taking chlorophyll values from citrus leaves using (SPAD-502 Minolta) chlorophyll meter. Five vegetation indices including DVI (difference vegetation index), RDVI (renormalized difference vegetation index), MTVI2 (modified triangular vegetation index 2), SARVI (soil and atmospherically resistant vegetation index) and Iron Oxide index were derived to determine most robust index by developing linear regression models among VIs and citrus leaves chlorophyll contents. Triangular indices (MTVI2) expressed highest correlation coefficient R2 = 0.81 with high accuracy and precision for ground truthed citrus leaves chlorophyll contents. MTVI2 and SARVI were proven as most robust indices to map spatial differences in chlorophyll content with R2 = 0.81 and R2 = 0.76, respectively. DVI, RDVI and Iron Oxide index resulted in less efficient VIs in vertical plantations with coefficient of determination (R2) values 0.57, 0.59 and 0.69, respectively. Moreover, in this study low cost multispectral UAV (DJI Phantom4 Pro) was used to monitor biophysical status of crop in real time and develop an on-field cost efficient, precise and accurate agricultural monitoring system against conventional techniques. This article has covered the aspect of chlorophyll detection using spectrally modified VIs in vertical hierarchy that was a citrus field and manual efforts were used by taking the help of UAV. The novel aspect of this study covers the chlorophyll detection in the trees which is not studied by the scientists as a part of Remotesensing.