In order to accurately monitor and objectively evaluate the damage of the rice leaf roller, Cnaphalocrocis medinalis Guenee (C. medinalis), to rice growth, breeding and yield formation, in this paper, the canopy hyperspectral data and soil and plant analyzer development (SPAD) values of rice in the controlled field experiments (in 2015 and 2019) and the natural field experiments (in 2020) were measured by the instruments of ASD Field Spec3 and SPAD-502 at different growth stages (jointing stage, booting stage, filling stage and maturing stage). The pest number and the percentage of rolled leaves in rice resulted from C. medinalis was measured by the manual investigations. The hyperspectral characteristics of rice canopy, physiological and ecological parameters of rice and the characteristics of C. medinalis' occurrence parameters in the two experiments were analyzed. Models for estimating physiological and ecological parameters of rice after being damaged by C. medinalis based on the hyperspectral parameters were established. The results showed that:(1) in the two experiments, the reflectance of the red edge to near-infrared band of rice SPAD value and canopy decreased with the aggravation of the degree of C. medinalis infestation, while the reflectivity of the visible light band was the opposite. (2) The SPAD value of the natural field test and the canopy reflectance in the red light to near-infrared wavelength range were significantly lower than those of the control field test in the early stage of rice growth and development, and slightly higher than that of the control field test in the later stage. (3) After comprehensively analyzing the experimental data, the multiple pest characteristic parameters and vegetation indices in the natural field experiments and the controlled field experiments were selected. A set of single factor estimation models and multi-factor estimation models of SPAD were constructed, respectively. Each model achieved the good estimation effect, among which the binomial function simulation effect of Enhanced Vegetation Index (EVI) was the best in the single factor model. However, the simulation effect of the multi-factor linear regression estimation model was better than that of all single-factor models. (4) Through application test of these models in 2021, it was found that the estimated SPAD values of the single factor estimation models based on the pest number, percentage of rolled leaf, Optimized Soil-Adjusted Vegetation Index (OSAVI), EVI and Difference Vegetation Index (DVI) in these models were highly consistent with the measured value, and their R_v² were more than 0.8. It indicated that these five models achieved relatively ideal estimation effect. This study provided a high-precision and feasible estimation method for the SPAD value estimation of rice under the infestation of C. medinalis.