Article Title :
Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review
3 (2019)
58-73
Calibration , Canopy , Indices , NDVI , UAS , UAV , Vegetation
Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the biophysical parameters of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.
The Unmanned Aerial System (UAS) based Vegetative indices are critically reviewed in the paper.
Timely, intensive, cost effective and efficient data collection with less labor and time can be possible using UAV systems.
VIs is widely used for agricultural applications: leaf area estimations, canopy analysis, plant nutrients analysis (nitrogen status), biomass estimations, plant growth, crop yield estimations, etc.
UAV-RGB based vegetation indices have great potential of high precision and low-cost assessment, planning and monitoring of agriculture, water resources, settlements, deserters, etc.
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