Next Article in Journal
Mapping Smallholder Yield Heterogeneity at Multiple Scales in Eastern Africa
Previous Article in Journal
Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data
Open AccessArticle

Detecting Drought-Induced Tree Mortality in Sierra Nevada Forests with Time Series of Satellite Data

Department of Land, Air and Water Resources, University of California, Davis, CA 95616-8627, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(9), 929; https://doi.org/10.3390/rs9090929
Received: 22 July 2017 / Revised: 15 August 2017 / Accepted: 31 August 2017 / Published: 8 September 2017
(This article belongs to the Section Forest Remote Sensing)
A five-year drought in California led to a significant increase in tree mortality in the Sierra Nevada forests from 2012 to 2016. Landscape level monitoring of forest health and tree dieback is critical for vegetation and disaster management strategies. We examined the capability of multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) in detecting and explaining the impacts of the recent severe drought in Sierra Nevada forests. Remote sensing metrics were developed to represent baseline forest health conditions and drought stress using time series of MODIS vegetation indices (VIs) and a water index. We used Random Forest algorithms, trained with forest aerial detection surveys data, to detect tree mortality based on the remote sensing metrics and topographical variables. Map estimates of tree mortality demonstrated that our two-stage Random Forest models were capable of detecting the spatial patterns and severity of tree mortality, with an overall producer’s accuracy of 96.3% for the classification Random Forest (CRF) and a RMSE of 7.19 dead trees per acre for the regression Random Forest (RRF). The overall omission errors of the CRF ranged from 19% for the severe mortality class to 27% for the low mortality class. Interpretations of the models revealed that forests with higher productivity preceding the onset of drought were more vulnerable to drought stress and, consequently, more likely to experience tree mortality. This method highlights the importance of incorporating baseline forest health data and measurements of drought stress in understanding forest response to severe drought. View Full-Text
Keywords: forest; drought; Sierra Nevada; MODIS; tree mortality; California; remote sensing forest; drought; Sierra Nevada; MODIS; tree mortality; California; remote sensing
Show Figures

Graphical abstract

MDPI and ACS Style

Byer, S.; Jin, Y. Detecting Drought-Induced Tree Mortality in Sierra Nevada Forests with Time Series of Satellite Data. Remote Sens. 2017, 9, 929.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop