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Diseases and insect pest are the most restricting factors affecting the crop health, the improvement of the crop yield and quality. It is of great significant to strengthen the development of crop disease and insect pest monitoring. Therefore, to undertake the precise prevent and control on the crop disease and insect pest is key for ensuring the food safety, and improve the yield and quality of crop. The traditional disease and insect pest monitoring mainly relies on the manual field investigation, with low efficiency and quality, which can no longer meet the needs of efficient, intelligent and professional modern agriculture. With the development of information technology, the monitoring of crop diseases and insect pest has gradually developed from the traditional manual monitoring to remote sensing monitoring. Crop monitoring platform, monitoring sensor technology, data analysis and processing technology are key technologies for the development of remote sensing monitoring of crop diseases and insect pest. The development of the above technologies determined the development of remote sensing monitoring technology of crop disease and insect pest. The research progress of monitoring platform, monitoring sensor technology, data analysis and processing technology for crop disease and insect pests were summarized. In terms of monitoring platform, the research status of ground machinery platform, aircraft platform, and satellite platform was summarized. In the monitoring sensor technology, the research progress of radar sensor, image sensor, thermal imaging sensor and spectral sensor for crop diseases and pests monitoring was summarized. In data analysis and processing technology, the research achievements of classical statistical algorithms, computer image processing algorithms, machine learning algorithms and deep learning algorithms in crop diseases and insect pests monitoring were expounded. Furthermore, recommendations were proposed for further promoting the development of crop diseases and insect pests monitoring, including building multi-scale integrated application monitoring platform, promoting the development of multi-scale data fusion sensor, and continuous optimizing multidisciplinary theory and algorithm structure research.