Abstract: Crop diseases and pests severely affect food yield and quality, causing significant losses in agricultural production. Habitat suitability assessments for crop diseases and pests can effectively characterize environmental areas that are suitable for the breeding and prevalence of pests and diseases, which can provide crucial information for disease and pest prediction. The occurrence and prevalence of crop diseases and pests are affected by habitat factors. These factors are highly spatially and temporally heterogeneous and are difficult to effectively characterize through traditional meteorological station data and human surveys. This poses a great challenge for the evaluation of pest and disease habitats. Fortunately, the development and maturity of remote sensing technologies present significant opportunities. Multi-source remote sensing information not only has natural advantages in the representation of spatiotemporal heterogeneity but can also form information complementarities with traditional meteorological station data. Therefore, it can provide comprehensive and abundant information for habitat suitability evaluation of pests and diseases and support model construction. This paper reviewed the research progress of multi-source remote sensing information in evaluating the habitat suitability for crop pests and diseases, focusing on the potential of multi-source remote sensing data for the characterization of habitat factors, such as host crop distribution and growth status, environmental and meteorological conditions, and landscape, as well as modeling methods, such as statistical, machine learning, and niche models in a wide-scale habitat suitability assessment. On this basis, this paper proposed a framework for crop disease and pest habitat evaluation model construction based on multi-source remote sensing information and discussed the development trends in technology. This study provides technical support for highly accurate and scientific regional prevention and management strategies. In addition, it provides scientific guidance for integrated control and green prevention.