Abstract
Abstract. Space-based observation of crops and agro-system on the Earth surface is one of the most important applications of remote sensing using the sensors in optical and microwave spectrum to assess the crop growth for decision making for developing crop information and management system. Remote sensing technology provides scalable and reliable information in respect of rice crop grown area, its crop growth and prediction of crop yield due to acquisition of satellite imagery during the revisit of the orbit by space-borne sensors in optical and microwave spectrum. Synthetic Aperture Radar has the advantages of all-weather, day and night imaging, canopy penetration, and high-resolution capabilities, which makes Space-borne SAR sensors as an effective system for monitoring crop growth, crop classification and mapping of crop area based on the crop canopy interaction of SAR signals due to backscattering coefficients of the earth surface. SAR data from ERS-1/2 SAR, ENVISAT ASAR, ALOS-1/2 PALSAR, Radarsat-1/2 SAR, TerraSAR, COSMO-SkyMed, and Sentinel-1 have been used by various researchers for identification and analysis of rice crop growth based on the backscattering values in different regions of Asia and European region, where backscattered image depends of various earth surface and SAR sensors parameters. In this paper, knowledge based classifier using SAR images of existing space-borne-SAR sensors have been developed based on modeling of SAR backscattering coefficients in C-band and X-band for monitoring the rice crop growth and its analysis using multi-temporal and multi-frequency- SAR sensors data.
Highlights
Asian countries are the major rice and wheat growing region of the world due to its summer seasons with monsoon rainfall followed by winter seasons
Rice is considered as a pivotal political commodity in many Asian countries with its price often serves as a key indicator for government performance and crucial for policymakers to control rice trade flow for domestic rice market stable, which requires reliable information on rice area, seasonality, and yield as an essential part of many countries of Asian region in the context of food security and policy
Rice plants are transplanted in the paddy fields under flooded conditions and irrigated continuously until the mid-maturing stage of rice crops, so that the soil surface of paddy fields is under flooded conditions during the most growing period
Summary
Asian countries are the major rice and wheat growing region of the world due to its summer seasons with monsoon rainfall followed by winter seasons. Space-borne Synthetic Aperture Radar (SAR) sensors are an effective system for monitoring crop growth, crop classification and mapping of crop area based on the crop canopy interaction of radar signals due to backscattering coefficients of the earth surface as well as its advantages of all-weather, day and night imaging, canopy penetration, and high-resolution capabilities. C-band SAR sensors with single and multi-polarization capability is found most attractive for rice monitoring, discrimination of different growth stages and mapping at regional or continental scale, because image data from other SAR sensors in L-band and X-band due to limited spatial coverage (e.g., Terra-SAR-X) or longer revisit time (e.g., ALOS PALSAR). Knowledge based classifier have been modeled based on backscattering coefficients of Space-borne SAR sensors with rice canopy for monitoring the crop growth analysis depending upon the different radar parameters such as wavelength, incidence angle, polarization as well as its interaction with different stages of rice-crop growth
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