scholarly journals Annual canopy interception at artificial lowland tropical forest

2015 ◽  
Vol 12 (5) ◽  
pp. 4879-4907 ◽  
Author(s):  
A. B. Azinoor-Azida ◽  
L. Minjiao
Keyword(s):  
Tropical Forest ◽  
Temporal Resolution ◽  
Canopy Interception ◽  
Lowland Tropical Forest ◽  
Interception Loss ◽  
Canopy Interception Loss

Abstract. The objective of this paper is to present the application of interception model developed in artificial lowland tropical forest. This model estimates annual canopy interception loss with temporal resolution effects. A 12-month data from 2 plots in study area were collected and the measured interception loss was compared with results calculated using original Gash, modified Gash and the interception model developed. The results show that the model can be applied to estimate annual interception loss.

scholarly journals Monitoring Vegetation Change in the Presence of High Cloud Cover with Sentinel-2 in a Lowland Tropical Forest Region in Brazil

2020 ◽  
Vol 12 (11) ◽  
pp. 1829
Author(s):  
Tatiana Nazarova ◽  
Pascal Martin ◽  
Gregory Giuliani
Keyword(s):  
Tropical Forest ◽  
Temporal Resolution ◽  
Cloud Cover ◽  
Detection System ◽  
Forest Degradation ◽  
High Cloud ◽  
Lowland Tropical Forest ◽  
Forest Region ◽  
Vegetation Loss ◽  
Sentinel 2

Forests play major roles in climate regulation, ecosystem services, carbon storage, biodiversity, terrain stabilization, and water retention, as well as in the economy of numerous countries. Nevertheless, deforestation and forest degradation are rampant in many parts of the world. In particular, the Amazonian rainforest faces the constant threats posed by logging, mining, and burning for agricultural expansion. In Brazil, the “Sete de Setembro Indigenous Land”, a protected area located in a lowland tropical forest region at the border between the Mato Grosso and Rondônia states, is subject to illegal deforestation and therefore necessitates effective vegetation monitoring tools. Optical satellite imagery, while extensively used for landcover assessment and monitoring, is vulnerable to high cloud cover percentages, as these can preclude analysis and strongly limit the temporal resolution. We propose a cloud computing-based coupled detection strategy using (i) cloud and cloud shadow/vegetation detection systems with Sentinel-2 data analyzed on the Google Earth Engine with deep neural network classification models, with (ii) a classification error correction and vegetation loss and gain analysis tool that dynamically compares and updates the classification in a time series. The initial results demonstrate that such a detection system can constitute a powerful monitoring tool to assist in the prevention, early warning, and assessment of deforestation and forest degradation in cloudy tropical regions. Owing to the integrated cloud detection system, the temporal resolution is significantly improved. The limitations of the model in its present state include classification issues during the forest fire period, and a lack of distinction between natural vegetation loss and anthropogenic deforestation. Two possible solutions to the latter problem are proposed, namely, the mapping of known agricultural and bare areas and its subsequent removal from the analyzed data, or the inclusion of radar data, which would allow a large amount of finetuning of the detection processes.

scholarly journals Observation of Canopy Interception Loss in an Abandoned Coniferous Plantation.

2010 ◽  
Vol 92 (1) ◽  
pp. 54-59 ◽  
Author(s):  
Yoshinori Shinohara ◽  
Jun’ichiro Ide ◽  
Naoko Higashi ◽  
Hikaru Komatsu ◽  
Tomonori Kume ◽  
...  
Keyword(s):  
Canopy Interception ◽  
Coniferous Plantation ◽  
Interception Loss ◽  
Canopy Interception Loss

Forest canopy interception loss exceeds wet canopy evaporation in Japanese cypress (Hinoki) and Japanese cedar (Sugi) plantations

2013 ◽  
Vol 507 ◽  
pp. 287-299 ◽  
Author(s):  
Takami Saito ◽  
Hiroki Matsuda ◽  
Misako Komatsu ◽  
Yang Xiang ◽  
Atsuhiro Takahashi ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Japanese Cedar ◽  
Canopy Interception ◽  
Japanese Cypress ◽  
Interception Loss ◽  
Canopy Interception Loss

scholarly journals Modeling and measurement of two-layer-canopy interception losses in a subtropical mixed forest of central-south China

2005 ◽  
Vol 2 (5) ◽  
pp. 1995-2024 ◽  
Author(s):  
G. Zhang ◽  
G. M. Zeng ◽  
Y. M. Jiang ◽  
G. H. Huang ◽  
J. B. Li ◽  
...  
Keyword(s):  
Tropical Forests ◽  
South China ◽  
Mixed Forest ◽  
Canopy Interception ◽  
Sparse Model ◽  
Hydrological Fluxes ◽  
Interception Loss ◽  
Forested Ecosystems ◽  
Canopy Interception Loss ◽  
Central South

Abstract. The original Gash analytical model and the sparse Gash's model have been applied to simulate rainfall interception losses from the two canopy layers in Shaoshan forest of central-south China during 2003. The total estimated interception loss from the two canopy layers is 478.4 mm with an error of 12.4 mm or 2.7% of total measured interception loss (466.0 mm). Both the original Gash model for top-canopy interception loss and the sparse model for sub-canopy loss overestimate interception losses. The simulated results show that the interception losses in top-canopy is 182.6 mm with an overestimation of 4.9% of measured losses and that in sub-canopy is 295.8 mm with an overestimation of 1.3%. The simulated values of the top-canopy suggest that 47% of the simulated interception losses are evaporated in the stage of "during storms" and 38% in "after storms", which is similar to the published results in temperate and tropical forests. However, the modelled losses from the sub-canopy show that 17% of interception losses are evaporated in "during storms" and 70% in "after storms", which is deviated from the reported results. The simulated results of two canopy interception losses in Shaoshan forest indicate that canopy structures may strongly impact hydrological fluxes in forested ecosystems.

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