关键词: 无人机, 归一化植被指数, 植被覆盖度, 像元二分模型

Abstract: Salix cheilophila, a common shrub in arid and semi-arid areas, is usually used for vegetation restoration in Inner Mongolia. To clarify the effects of exogenous mechanical damage on self-healing of root mechanical properties, changes of mechanical properties of straight roots with diameter of 1-4 mm under different damage degrees and different recovery durations were examined in situ using the HG100 digital push and pull tester and self-developed experimental installation. The results showed that: (1) There were significant differences in tensile force and tensile strength among undamaged roots with different diameters. Tensile force was positively correlated with the diameter (power function), with average tensile force being 77.14±38.23 N for roots with diameter of 1-4 mm. Tensile strength was negatively correlated with root diameter, with an average of 15.22±2.85 MPa. (2) Exogenous mechanical damage could impede the regular growth and development of plant roots. Such inhibitory effects differed with the degree of damage to the roots. Severe damage had a stronger inhibitory effect on root diameter growth than mild damage. After self-healing for three and five months， comparing with control, the severe damage could decrease the growth rate of root diameter by 25.19% and 29.96% respectively, and the mild-damage for 18.76% and 26.89%.  (3) Tensile force and tensile strength of roots were significantly decreased after mechanical damage, with such effects being gradually eliminated with the help of root selfhealing mechanism. The longer the root recovery time, the greater the recovery rate of mechanical properties. The average recovery rates of tensile force after self-healing for three and five months were 37.63% and 48.13% respectively. The degree of damage also affected the self-healing of mechanical properties. The recovery rates of mechanical properties for severe damage roots were significantly lower than those for mild-damage roots under the same recovery durations.

Key words: pixel binary model, fractional vegetation cover, unmanned aerial vehicle, normalized difference vegetation index