Study on detection method of vegetation ecology mutation based on NDVI long and short time series data

Vegetation is the core component of the surface ecosystem, which plays a very important role in maintaining the stability of the ecosystem. With the increasing social and economic activities of human beings, scientific, accurate and efficient detection of vegetation ecology mutation has become particularly critical. Using Terra satellite MOD13Q1 data, a method for detecting vegetation ecology mutation based on NDVI (Normalized Vegetation Index) long and short time series data is established. It can not only analyze the vegetation change law and characteristics by using NDVI long time series data, but also detect whether there is mutation in NDVI short time series data, and determine the mutation time, position and ground object type before and after mutation. The experimental results of vegetation ecology mutation in Block 1 from 2005 to 2007 and Block 2 from 2015 to 2017 in typical areas of Hetian, Xinjiang show that the vegetation ecology of Block 1 changed suddenly in 2006 compared with that of 2005, and the vegetation type was woodland, but there was no mutation in vegetation ecology in 2007 compared with that of 2006, and the vegetation type did not change. Compared with 2015, the vegetation ecology of Block 2 changed suddenly in 2016, and no matching vegetation type was found. Compared with 2016, the vegetation ecology changed suddenly in 2017, and it was judged as wasteland. The results are consistent with those of high-definition satellite images and field investigation. This method can detect the vegetation ecology mutation in the target area scientifically, accurately and efficiently, which is of great significance to the protection and rational development and utilization of ecology resources in the process of regional economic construction.