EVALUATION OF RGB VEGETATION INDICES DERIVED FROM UAV IMAGES FOR RICE CROP GROWTH MONITORING

9 citations as recorded by crossref.

1. Applying RGB-Based Vegetation Indices Obtained from UAS Imagery for Monitoring the Rice Crop at the Field Scale: A Case Study in Portugal R. Gerardo & I. de Lima 10.3390/agriculture13101916
2. Research on identification and extraction of crop plants in plateau mountainous areas based on multi-dimensional features L. Yin et al. 10.1080/01431161.2024.2391080
3. Integration of Unmanned Aerial Vehicle and Multispectral Sensor for Paddy Growth Monitoring Application: A Review N. Mohidem et al. 10.47836/pjst.32.2.04
4. Condiciones agronómicas del cultivo de arroz con imágenes de vehículos aéreos no tripulados A. Conforme Ponce et al. 10.56124/sapientiae.v7i14.0003
5. Evaluation of Sugarcane Crop Growth Monitoring Using Vegetation Indices Derived from RGB-Based UAV Images and Machine Learning Models P. Ruwanpathirana et al. 10.3390/agronomy14092059
6. Utilising RGB drone imagery and vegetation indices for accurate above-ground biomass estimation: a case study of the cradle nature reserve, Gauteng Province, South Africa C. Matyukira & P. Mhangara 10.1080/10106049.2024.2390512
7. Incidence of environmental factors on travertine façade of heritage buildings in the historic center of Cuenca-Ecuador. A test scenario through Digital Imagen Processing M. Aguirre Ullauri et al. 10.37558/gec.v25i1.1293
8. Unmanned-Aerial-Vehicle Data as an Effective Tool for the Evaluation of Ancient Khorasan and Modern Kabot Spring Wheat Varieties under Different Tillage Systems K. Balážová et al. 10.3390/agronomy14010147
9. A novel linear spectral unmixing-based method for tree decline monitoring by fusing UAV-RGB and optical space-borne data M. Ghasemi et al. 10.1080/01431161.2024.2305630