草地草种遥感判别技术研究进展

Grassland is an important resource bank for regional economic development and a crucial ecological reservoir for the security of China’s land-based ecological environment. Remote sensing technology is rapid,efficient,and low-cost,and therefore provides the mainstream technical means for large-scale grassland monitoring. The use of remote sensing technology to discriminate grassland species is an important way to monitor the population dynamics and botanical community succession in grassland. Such information is conducive to the timely and accurate detection of changes in the grassland ecological environment and provides an important reference for the scientific management of grassland ecosystems and the construction of an ecologically aware civilization. This study focuses on the problem of remote sensing discrimination of grassland species,clarifies the technical process of grassland species discrimination and introduces the latest research progress. Technical difficulties are covered from three perspectives：The characteristics of the main remote sensing data sources for grassland species discrimination and their acquisition techniques,important grassland species discrimination features and their mining techniques and the current commonly used grassland species discrimination methods and models. This study concludes that hyperspectral and LiDAR remote sensing and their fusion technologies have application prospects in the remote sensing discrimination of grassland species, and that the deep mining of multidimensional features and the effective combination of complementary features can improve the accuracy of grassland species discrimination. This study identifies the main problems of the current remote sensing discrimination technology for grassland species,and opens the prospect of the future precise discrimination of grassland species through remote sensing technology and thereby provides a theoretical reference for a thorough understanding of the field of remote sensing identification of grassland species and in-depth research on grassland species discrimination. © 2023 Editorial Office of Acta Prataculturae Sinica. All rights reserved.