Abstract
Yunnan pine shoot beetles (PSB), Tomicus yunnanensis and Tomicus minor have spread through southwestern China in the last five years, leading to millions of hectares of forest being damaged. Thus, there is an urgent need to develop an effective approach for accurate early warning and damage assessment of PSB outbreaks. Remote sensing is one of the most efficient methods for this purpose. Despite many studies existing on the mountain pine beetle (MPB), very little work has been undertaken on assessing PSB stress using remote sensing. The objective of this paper was to develop a spectral linear mixing model aided by radiative transfer (RT) and a new Yellow Index (YI) to simulate the reflectance of heterogeneous canopies containing damaged needles and quantitatively inverse their PSB stress. The YI, the fraction of dead needles, is a physically-explicit stress indicator that represents the plot shoots damage ratio (plot SDR). The major steps of this methods include: (1) LIBERTY2 was developed to simulate the reflectance of damaged needles using YI to linearly mix the green needle spectra with the dead needle spectra; (2) LIBERTY2 was coupled with the INFORM model to scale the needle spectra to the canopy scale; and (3) a look-up table (LUT) was created against Sentinel 2 (S2) imagery and inversed leaf chlorophyll content (LCC), green leaf area index (LAI) and plot SDR. The results show that (1) LIBERTY2 effectively simulated the reflectance spectral values on infested needles (mean relative error (MRE) = 1.4–18%), and the YI can indicate the degrees of needles damage; (2) the coupled LIBERTY2-INFORM model is suitable to estimate LAI (R2 = 0.73, RMSE = 0.17 m m−2, NRMSE = 11.41% and the index of agreement (IOA) = 0.92) and LCC (R2 = 0.49, RMSE = 56.24 mg m−2, NRMSE = 25.22% and IOA = 0.72), and is better than the original LIBERTY model (LAI: R2 = 0.38, RMSE = 0.43 m m−2, NRMSE = 28.85% and IOA = 0.68; LCC: R2 = 0.34, RMSE = 76.44 mg m−2, NRMSE = 34.23% and IOA = 0.57); and (3) the inversed YI is positively correlated with the measured plot SDR (R2 = 0.40, RMSE = 0.15). We conclude that the LIBERTY2 model improved the reflectance simulation accuracy of both the needles and canopies, making it suitable for assessing PSB stress. The YI has the potential to assess PSB damage.
Highlights
The forest ecosystem plays an important role in the global carbon cycle [1,2]
Previous studies [36,47] have indicated that the INFORM model achieves a good performance in medium-dense and dense managed conifer stands with low a variation in tree height and open canopy
The spectral linear mixing method was used in LIBERTY2 which improved the accuracy of modeling heterogeneous needle reflectance
Summary
The forest ecosystem plays an important role in the global carbon cycle [1,2]. forest pests can destroy the stability of forest ecosystems and increase their vulnerability to natural disturbance [3,4]. There are two major types of pests, each attacking different organs of trees: defoliators eat leaves or needles and borers bore into the shoots, bark, or wood. These pests may cause a temporary physiological decline in trees (i.e., reduced moisture) or permanent damage to biochemical and biophysical parameters like leaf chlorophyll content (LCC) and green leaf area index (LAI). These changes result in canopy reflectance changes, making it possible to use Earth observation (EO) data to detect forest pests [5,6]. Remote sensing has become an effective technology for detecting forest damage (i.e., diseases and insects) because of the richness of high temporal, spatial and spectral resolution images [7,8,9,10,11,12,13]
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