Assessing the Impact of Soil on Species Diversity Estimation Based on UAV Imaging Spectroscopy in a Natural Alpine Steppe

Abstract

Grassland species diversity monitoring is essential to grassland resource protection and utilization. “Spectral variation hypothesis” (SVH) provides a remote sensing method for monitoring grassland species diversity at pixel scale by calculating spectral heterogeneity. However, the pixel spectrum is easily affected by soil and other background factors in natural grassland. Unmanned aerial vehicle (UAV)-based imaging spectroscopy provides the possibility of soil information removal by virtue of its high spatial and spectral resolution. In this study, UAV-imaging spectroscopy data with a spatial resolution of 0.2 m obtained in two sites of typical alpine steppe within the Sanjiangyuan National Nature Reserve were used to analyze the relationships between four spectral diversity metrics (coefficient of variation based on NDVI (CVNDVI), coefficient of variation based on multiple bands (CVMulti), minimum convex hull volume (CHV) and minimum convex hull area (CHA)) and two species diversity indices (species richness and the Shannon–Wiener index). Meanwhile, two soil removal methods (based on NDVI threshold and the linear spectral unmixing model) were used to investigate the impact of soil on species diversity estimation. The results showed that the Shannon–Wiener index had a better response to spectral diversity than species richness, and CVMulti showed the best correlation with the Shannon–Wiener index between the four spectral diversity metrics after removing soil information using the linear spectral unmixing model. It indicated that the estimation ability of spectral diversity to species diversity was significantly improved after removing the soil information. Our findings demonstrated the applicability of the spectral variation hypothesis in natural grassland, and illustrated the impact of soil on species diversity estimation.

[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

“…Spectrum estimation, spatial allocation, and management of public sport facilities resources can delete duplicate management information [ 3 ] and not only save resource allocation and management costs but also improve the utilization rate of public sport facilities resources and improve the management accuracy of users. Therefore, it has a certain theoretical significance and practical value to optimize the allocation and management of public sport facilities resources of government and health institutions [ 4 ]. Domestic literature on resource allocation and management optimization of public sport facilities has increased year by year, and the results are given in Table 1 .…”

Diversity of Prokaryotic Microbiota in Iloilo River, Iloilo Province, Philippines Through Partial 16S rrna Gene Sequence Analysis

“…where H' is the species diversity index, s is the number of species, and pi is the proportion of individuals of each species belonging to the ith species of the total number of individuals [31,32].…”

Design and implementation of an ecological big data sharing incentive system based on contract theory and game theory

“…The Three Rivers Source Region is the largest nature reserve in China, with a unique geographical location and highland features. Its ecological protection is of great significance for China's ecological conservation [1,2] , and its ecological data plays a crucial role in ecological protection and construction [3,4,5] . Sharing ecological big data allows for a better understanding of the ecological environment's status, timely identification and resolution of ecological environmental problems, promotion of sustainable development, and provision of more accurate information to decision-makers for formulating more scientific policies, thereby promoting sustainable development.…”