Stand Parameter Estimation of Artificial Evergreen Conifer Forests Using Airborne Images: An Evaluation of Seasonal Difference on Accuracy and Best Wavelength

2000 ◽  
Vol 5 (4) ◽  
pp. 247-258 ◽  
Author(s):  
Yoshio Awaya ◽  
Nobuhiko Tanaka ◽  
Kunihiro Tanaka ◽  
Gen Takao ◽  
Eiji Kodani ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Seasonal Difference ◽  
Conifer Forests ◽  
Evergreen Conifer

scholarly journals Seasonal variation in the canopy color of temperate evergreen conifer forests

2020 ◽  
Author(s):  
Bijan Seyednasrollah ◽  
David R. Bowling ◽  
Rui Cheng ◽  
Barry A. Logan ◽  
Troy S. Magney ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Conifer Forests ◽  
Evergreen Conifer

scholarly journals Unexpected Evergreen Expansion in the Siberian Forest under Warming Hiatus

2017 ◽  
Vol 30 (13) ◽  
pp. 5021-5039 ◽  
Author(s):  
Yongli He ◽  
Jianping Huang ◽  
Herman Henry Shugart ◽  
Xiaodan Guan ◽  
Bin Wang ◽  
...  
Keyword(s):  
Mixed Forest ◽  
Winter Season ◽  
Forest Composition ◽  
Conifer Forests ◽  
Conifer Forest ◽  
Forest Change ◽  
Model Simulations ◽  
Forest Model ◽  
Evergreen Conifer ◽  
Warming Hiatus

Siberia has experienced a pronounced warming over the past several decades, which has induced an increase in the extent of evergreen conifer forest. However, the potential slowing of the trend of increasing surface air temperature (SAT) has produced intense debate since the late 1990s. During this warming hiatus, the Siberian region experienced a significant cooling during the winter season around 10 times that of the Northern Hemisphere (NH) as a whole. This potentially stresses evergreen conifer forests because cooler winters can cause cold-temperature damage and, hence, increase the mortality of young evergreen conifer forests. In this study, the response of Siberian forest composition during the warming hiatus was investigated using satellite observations coupled with model simulations. Observations indicated that from 2001 to 2012, the apparent area of evergreen conifer forest has increased by 10%, while that of the deciduous conifer forest has decreased by 40%. The transition from deciduous to evergreen conifer forest usually occurs through mixed forest or woody savannas as a buffer. To verify the response of evergreen conifer forest, model experiments were performed using an individual-based forest model. Hysteresis of forest change seen in the model simulations indicates that changes in forest composition dynamics under temperature oscillations induced by internal climate variability may not reverse this composition change. As a result, the evergreen conifer forest expansion under climate warming is expected to be a continuing process despite the occurrence of a warming hiatus, exerting far-reaching implications for climate-change-induced albedo shifts in the Siberian forest.

scholarly journals Reevaluating growing season length controls on net ecosystem production in evergreen conifer forests

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
David M. Barnard ◽  
John F. Knowles ◽  
Holly R. Barnard ◽  
Michael L. Goulden ◽  
Jia Hu ◽  
...  
Keyword(s):  
Growing Season ◽  
Net Ecosystem Production ◽  
Conifer Forests ◽  
Season Length ◽  
Growing Season Length ◽  
Ecosystem Production ◽  
Evergreen Conifer

scholarly journals Modeling acclimation of photosynthesis to temperature in evergreen conifer forests

2010 ◽  
Vol 188 (1) ◽  
pp. 175-186 ◽  
Author(s):  
Guillermo Gea-Izquierdo ◽  
Annikki Mäkelä ◽  
Hank Margolis ◽  
Yves Bergeron ◽  
T. Andrew Black ◽  
...  
Keyword(s):  
Conifer Forests ◽  
Evergreen Conifer

Weighted Combination of Prior and Sample Information and Parameter Estimation

Optimization ◽  
1976 ◽  
Vol 7 (5) ◽  
pp. 665-672
Author(s):  
H. Burke ◽  
C. Hennig ◽  
W H. Schmidt
Keyword(s):  
Parameter Estimation ◽  
Sample Information ◽  
Weighted Combination

Sequential accuracy in parameter estimation for population correlation coefficients.

2019 ◽  
Vol 24 (4) ◽  
pp. 492-515 ◽  
Author(s):  
Ken Kelley ◽  
Francis Bilson Darku ◽  
Bhargab Chattopadhyay
Keyword(s):  
Parameter Estimation ◽  
Correlation Coefficients ◽  
Population Correlation
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