Biophysical and biochemical vegetation parameters are significant indicators of carbon and nutrient cycling and energy exchange in ecosystems. Remote-sensing inversion is an important method of obtaining regional and global biophysical and biochemical vegetation parameters. However, spectral and spatial scale effects result in differences among remotely sensed bio-parameters from different sources. This limits their use in unified applications and affects the precision of ecological models that utilize them as input parameters. This review examines the concept of the spectral-scale effect of remotely sensed bio-parameters and its causes. The spectral-scale effect is the phenomenon in which differences exist in the remotely sensed bio-parameters obtained using different band resolutions and band positions. The spectral-scale effect has two main aspects:the response of different regions of the spectrum to different internal structures, and the response to the chemical composition of green vegetation. Moreover, the response intensities and bandwidths of different sensors are different. This paper reviews relevant research on the spectral-scale from the perspectives of spectral-band position and bandwidth. Studies on band position usually analyze finite and discontinuous bands through statistical methods, but the physical characteristics of spectrum itself are not accounted for. Studies have not reached a consensus on whether a wide band or narrow band is more suitable for vegetation physicochemical parameter estimation. The manner in which spectral bandwidth influences extraction of vegetation information, construction of vegetation indices, and bio-parameter estimation is not yet clear. Research on the influence of the spatial effect on remotely sensed bio-parameters was summarized and analyzed from the perspectives of understanding the causes of the spatial effect, spatial heterogeneity description methods, and spatial scaling methods. The main conclusion of existing research is that the spatial-scale effect of remotely sensed bio-parameter inversion is related to use of nonlinear inversion methods and spatial heterogeneity of the parameters. However, most studies focused on leaf area index (LAI) and are aimed at relatively simple estimation models based on vegetation indices such as the normalized differential vegetation index (NDVI). Commonly used spatial-scale effect description methods are the variance method, the fractal method, the variation-function method, and the wavelet-transform method. Future research should seek to explain the physical meaning of the spatial-scale effect and to systematically and quantitatively simulate and analyze its characteristics. Although the spatial-scaling method has been adapted for use in spatial-scaling modeling from mathematical, statistical and physical methods, a great gap still exists between the theory of spatial-scaling models and their practical application. This review elucidates the need for more studies on spectral-scale effects in biophysical and biochemical vegetation parameters. In-depth spatial-scale effect studies aimed at the various vegetation parameters and inversion methods, using more complex physical models, are required. Studies on coupled spectral and spatial effects are a possible future direction, and theories and methods from ecology and other fields may provide valuable guidance.