Evaluation of ALOS-AVNIR2 Spectral Indices for Prediction of Rice Biomass
Subject Areas : Urban and Regional Planning Studies
Keywords: Rice, ALOS-AVNIR2 sensor, Vegetation indices, Biomass estimation,
Abstract :
Introduction Quantification and monitoring of biophysical and biochemical parameters of vegetation play a vital role in the terrestrial ecosystems. Biophysical parameters such as biomass and leaf area index (LAI) are the indicators of the productivity and function of crop. Rice is one of the major staples and widely planted crop in northern part of Iran. Rapid population growth, demands more rice production, while agricultural lands are gradually reducing with urban expansion. Monitoring rice production by remote sensing has been widely carried out in many countries where rice is the main food. The advantages of remotely sensed data, such as repetition of data collection, a synoptic view, a digital format that allows fast processing of large quantities of data, and the high correlation between spectral bands and vegetation parameters, make it the primary source for large area biomass estimation, especially in areas of difficult access. Therefore, remote sensing-based biomass estimation has increasingly attracted scientific interest. The possibility of estimation biomass by satellite remote sensing has been investigated in several studies at various spatial scales and environments. However this study aims to estimate the amount of fresh biomass of rice using Vegetation indices from ALOS satellite image which is rather new satellite.