Application of Hyper Spectral Remote Sensing for Urban Forestry Monitoring in Natural Disaster Zones

Abstract

Urban forestry is the core resource used to achieve a virtuous cycle of urban ecosystems and the main subject of urban life support systems. Natural disasters appear in characteristics of high frequency, intensity, and often result in huge losses in their area of destruction. Therefore, the situation requires real-time, accurate and dynamic monitoring, which is an important guarantee for maintaining a healthy and low-carbon urban ecological environment. Hyper spectral remote sensing is a remote sensing technology which provides a new technological means for scientific urban forest monitoring. In this paper, our group tries to provide a data processing method for analyzing of hyper spectral remote sensing images, starting from radiometric correction for image enhancement processing, then adopting dimension reduction operation, and finally match the spectral information. Based on hyper spectral remote sensing technology, the authors do investigation, monitoring and evaluation of urban forests in natural disaster zones. Combined with specific examples like the forest fires in California, the dendrolimus superans disaster of urban forestry in Greater Khingan Prefecture, and the classification of Californian coniferous species, our group makes evaluation and analysis of the hyper spectral remote sensing images. Relying on the advantages of hyper spectral remote sensing images like narrow-band, multi-channel, union of image and spectrum for dynamic monitoring of urban forestry, we prove that hyper spectral remote sensing has broad application prospects in fields like forest fire monitoring, pest monitoring and investigation of changes of urban forest resources in natural disaster zones, and propose directions of hyper spectral remote sensing for further research.