Oil palm is recognized as the golden crop. It produces the highest oil yield among oil seed crops. Malaysia, as the world’s second largest producer of palm oil, has 16 % of its lands planted with oil palms. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are forecasted to increase globally by 12 to 19 million hectares by 2050. Multisensor remote sensing plays an important role by providing relevant, timely and accurate information that can be developed into a plantation monitoring system to optimize production and sustainability. The use of synthetic aperture radar (SAR), a form of microwave remote sensing, in combination with visible and infrared (VIR) data has several distinct advantages, the biggest benefits being daylight and weather independent. SAR produces ‘cloud-free’ images. However, SAR image are difficult to interpret. Using optical remote sensing provides important physical parameters of the plantation using multispectral data acquisition. Both types of data are complementary and need to be exploited simultaneously to obtain a holistic view on the plantation. Using interferometric SAR a topographical surface and height profiles of oil palm plantations can be derived. The information is crucial in the effort of mapping the oil palms age profile in the country. With this monitored, a replanting program could be effectively installed to maximize national production. VIR remote sensing delivers information on the plants’ health and stress along with other biophysical parameters. Therefore the study aims to discover a set of parameters for oil palm plantation monitoring, which are retrievable from multisensor remote sensing data. The parameters are validated through the collection of ground. It is anticipated to derive all relevant information for the oil palm industry to implement a sustainable plantation management. The workflow on the parameter extraction and information derivation is designed and optimized.