Analysis of canopy structural and functional properties of tropical forests in a fertilisation experiment by Sentinel-2 images

2020 ◽  
Author(s):  
Maral Maleki ◽  
Lore Verryckt ◽  
Jose Miguel Barrios ◽  
Josep Peñuelas ◽  
Ivan Janssens ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Forest Canopy ◽  
Canopy Structure ◽  
Soil Fertilization ◽  
Structural And Functional Properties ◽  
Tropical Forest Soil ◽  
High Resolution Satellite Imagery ◽  
Sentinel 2

<p>Tropical forests such as Amazon is repository of ecological services. Understanding how tropical forest responds to the climate helps to improve ecosystem modeling and declining the uncertainty in calculation of carbon balance. Nowadays, the availability of very high resolution satellite imagery such as Sentinel-2 are powerful tools for analyzing the canopy structural and functional shifts over time, especially for tropical forest.</p><p>In this study, we examined the effect of the nutrient availability (nitrogen (N) and phosphorus (P)) on canopy and structural properties in tropical forest of French Guiana. In situ observations of canopy structure and functioning (i.e. photosynthesis, leaf N, chlorophyll content) were collected at two experimental sites (Paracou and Nouragues). Three topographical positions in each site were considered (top of the hills, middle and bottom end of the slope) and four plots were manipulated with different level of fertilization (Control, N, P, NP) in September 2016. Statistical analysis were conducted to analyze how the fertilization affect the forest canopy seasonality and if differences between sites and across positions existed. Furthermore, we tested whether Sentinel-2 data could help or not to describe the canopy changes observed in the field. Therefore, all Sentinel-2 images available before the start of the experiment, which date represent the natural situation, and two years after the intensive and repeated fertilization were collected. Greenness, chlorophyll and N, P related indicators were calculated from Sentinel-2 images.</p><p>Key words: Sentinel-2, Tropical forest, soil fertilization, topographical position.</p>

scholarly journals Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations

2021 ◽  
Author(s):  
Trina Merrick ◽  
Stephanie Pau ◽  
Matteo Detto ◽  
Eben North Broadbent ◽  
Stephanie Bohlman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Primary Productivity ◽  
Forest Canopy ◽  
Vegetation Index ◽  
Near Infrared ◽  
Canopy Structure ◽  
Gross Primary Productivity ◽  
Spatiotemporal Variability ◽  
Individual Tree ◽  
Tropical Forest Canopy

Abstract. Presented here for the first time are emerging vegetation indicators: near-infrared reflectance (NIRv) of vegetation, the fluorescence correction vegetation index (FCVI), and radiance (NIRvrad) of vegetation, for a tropical forest canopy calculated using UAS-based hyperspectral data. Fine-scale tropical forest heterogeneity represented by NIRv, FCVI, and NIRvrad, is investigated using unmanned aerial vehicle data and eddy covariance-based gross primary productivity estimates. By exploiting near-infrared signals, emerging vegetation indicators captured the greatest spatiotemporal variability, followed by the enhanced vegetation index (EVI), then the normalized difference vegetation index (NDVI), which saturates. Wavelet analyses showed the dominant spatial variability of all indicators is driven by tree clusters and larger-than-tree-crown size gaps (not individual tree crowns or leaf clumps), but emerging indices and EVI captured structural information at smaller spatial scales (~50 m) than NDVI (~90 m) and lidar (~70 m). As predicted in previous studies, we confirm that NIRv and FCVI are virtually identical for a dense green canopy despite the differences in how these indices were derived. Furthermore, we show that NIRvrad, which does not require separate irradiance measurements, correlated most strongly with gross primary productivity and photosynthetically active radiation. These emerging indicators, which are related to canopy structure and the radiation regime of vegetation canopies are promising tools to improve understanding of tropical forest canopy structure and function.

Indirect Measurement of Forest Canopy Structure from In Situ Optical Sensors

2003 ◽  
pp. 77-113 ◽  
Author(s):  
Richard A. Fournier ◽  
Daniel Mailly ◽  
Jean-Michel N. Walter ◽  
Kamel Soudani
Keyword(s):  
Optical Sensors ◽  
Forest Canopy ◽  
Canopy Structure ◽  
Indirect Measurement

scholarly journals Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations

2021 ◽  
Vol 18 (22) ◽  
pp. 6077-6091
Author(s):  
Trina Merrick ◽  
Stephanie Pau ◽  
Matteo Detto ◽  
Eben N. Broadbent ◽  
Stephanie A. Bohlman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Canopy ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Canopy Structure ◽  
Temporal Heterogeneity ◽  
Spatial And Temporal Heterogeneity ◽  
And Function ◽  
Tropical Forest Canopy

Abstract. Recently, remotely sensed measurements of the near-infrared reflectance (NIRv) of vegetation, the fluorescence correction vegetation index (FCVI), and radiance (NIRvrad) of vegetation have emerged as indicators of vegetation structure and function with potential to enhance or improve upon commonly used indicators, such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). The applicability of these remotely sensed indices to tropical forests, key ecosystems for global carbon cycling and biodiversity, has been limited. In particular, fine-scale spatial and temporal heterogeneity of structure and physiology may contribute to variation in these indices and the properties that are presumed to be tracked by them, such as gross primary productivity (GPP) and absorbed photosynthetically active radiation (APAR). In this study, fine-scale (approx. 15 cm) tropical forest heterogeneity represented by NIRv, FCVI, and NIRvrad and by lidar-derived height is investigated and compared to NIRv and EVI using unoccupied aerial system (UAS)-based hyperspectral and lidar sensors. By exploiting near-infrared signals, NIRv, FCVI, and NIRvrad captured the greatest spatiotemporal variability, followed by the enhanced vegetation index (EVI) and then the normalized difference vegetation index (NDVI). Wavelet analyses showed the dominant spatial scale of variability of all indicators was driven by tree clusters and larger-than-tree-crown size gaps rather than individual tree crowns. NIRv, FCVI, NIRvrad, and EVI captured variability at smaller spatial scales (∼ 50 m) than NDVI (∼ 90 m) and the lidar-based surface model (∼ 70 m). We show that spatial and temporal patterns of NIRv and FCVI were virtually identical for a dense green canopy, confirming predictions in earlier studies. Furthermore, we show that NIRvrad, which does not require separate irradiance measurements, correlated more strongly with GPP and PAR than did other indicators. NIRv, FCVI, and NIRvrad, which are related to canopy structure and the radiation regime of vegetation canopies, are promising tools to improve understanding of tropical forest canopy structure and function.

Tropical Forest Canopy Structure and Change Assessment Using Landsat, GEDI, and Airborne Lidar Data

2021 ◽  
Author(s):  
Peter Potapov ◽  
Xinyuan Li ◽  
Andres Hernandez-Serna ◽  
Svetlana Turubanova ◽  
Alexandra Tyukavina ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Canopy ◽  
Canopy Structure ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Change Assessment ◽  
Airborne Lidar Data ◽  
Tropical Forest Canopy

scholarly journals Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests

2018 ◽  
Vol 8 (2) ◽  
pp. 20170038 ◽  
Author(s):  
Sabina Roşca ◽  
Juha Suomalainen ◽  
Harm Bartholomeus ◽  
Martin Herold
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Structure From Motion ◽  
Laser Scanning ◽  
Canopy Structure ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Forest Monitoring ◽  
Forest Change ◽  
Forest Inventories

Terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) equipped with digital cameras have attracted much attention from the forestry community as potential tools for forest inventories and forest monitoring. This research fills a knowledge gap about the viability and dissimilarities of using these technologies for measuring the top of canopy structure in tropical forests. In an empirical study with data acquired in a Guyanese tropical forest, we assessed the differences between top of canopy models (TCMs) derived from TLS measurements and from UAV imagery, processed using structure from motion. Firstly, canopy gaps lead to differences in TCMs derived from TLS and UAVs. UAV TCMs overestimate canopy height in gap areas and often fail to represent smaller gaps altogether. Secondly, it was demonstrated that forest change caused by logging can be detected by both TLS and UAV TCMs, although it is better depicted by the TLS. Thirdly, this research shows that both TLS and UAV TCMs are sensitive to the small variations in sensor positions during data collection. TCMs rendered from UAV data acquired over the same area at different moments are more similar (RMSE 0.11–0.63 m for tree height, and 0.14–3.05 m for gap areas) than those rendered from TLS data (RMSE 0.21–1.21 m for trees, and 1.02–2.48 m for gaps). This study provides support for a more informed decision for choosing between TLS and UAV TCMs to assess top of canopy in a tropical forest by advancing our understanding on: (i) how these technologies capture the top of the canopy, (ii) why their ability to reproduce the same model varies over repeated surveying sessions and (iii) general considerations such as the area coverage, costs, fieldwork time and processing requirements needed.

scholarly journals Long-Term Nitrogen Addition Decreases Soil Carbon Mineralization in an N-Rich Primary Tropical Forest

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 734
Author(s):  
Xiankai Lu ◽  
Qinggong Mao ◽  
Zhuohang Wang ◽  
Taiki Mori ◽  
Jiangming Mo ◽  
...  
Keyword(s):  
Microbial Biomass ◽  
Organic Carbon ◽  
Tropical Forest ◽  
Soil Carbon ◽  
Tropical Forests ◽  
Carbon Mineralization ◽  
N Deposition ◽  
Soil Carbon Mineralization ◽  
N Additions

Anthropogenic elevated nitrogen (N) deposition has an accelerated terrestrial N cycle, shaping soil carbon dynamics and storage through altering soil organic carbon mineralization processes. However, it remains unclear how long-term high N deposition affects soil carbon mineralization in tropical forests. To address this question, we established a long-term N deposition experiment in an N-rich lowland tropical forest of Southern China with N additions such as NH4NO3 of 0 (Control), 50 (Low-N), 100 (Medium-N) and 150 (High-N) kg N ha−1 yr−1, and laboratory incubation experiment, used to explore the response of soil carbon mineralization to the N additions therein. The results showed that 15 years of N additions significantly decreased soil carbon mineralization rates. During the incubation period from the 14th day to 56th day, the average decreases in soil CO2 emission rates were 18%, 33% and 47% in the low-N, medium-N and high-N treatments, respectively, compared with the Control. These negative effects were primarily aroused by the reduced soil microbial biomass and modified microbial functions (e.g., a decrease in bacteria relative abundance), which could be attributed to N-addition-induced soil acidification and potential phosphorus limitation in this forest. We further found that N additions greatly increased soil-dissolved organic carbon (DOC), and there were significantly negative relationships between microbial biomass and soil DOC, indicating that microbial consumption on soil-soluble carbon pool may decrease. These results suggests that long-term N deposition can increase soil carbon stability and benefit carbon sequestration through decreased carbon mineralization in N-rich tropical forests. This study can help us understand how microbes control soil carbon cycling and carbon sink in the tropics under both elevated N deposition and carbon dioxide in the future.

scholarly journals Reply to Comment on “Comparison of Cloud Cover Detection Algorithms on Sentinel–2 Images of the Amazon Tropical Forest”

2021 ◽  
Vol 13 (5) ◽  
pp. 1028
Author(s):  
Alber Hamersson Sanchez ◽  
Michelle Cristina A. Picoli ◽  
Gilberto Camara ◽  
Pedro R. Andrade ◽  
Michel Eustaquio D. Chaves ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Cloud Cover ◽  
Optimal Performance ◽  
Detection Algorithms ◽  
Sentinel 2

In their comments about our paper, the authors remark on two issues regarding our results relating to the MACCS-ATCOR Joint Algorithm (MAJA). The first relates to the sub-optimal performance of this algorithm under the conditions of our tests, while the second corresponds to an error in our interpretation of MAJA’s bit mask. To answer the first issue, we acknowledge MAJA’s capacity to improve its performance as the number of images increases with time. However, in our paper, we used the images we had available at the time we wrote our paper. Regarding the second issue, we misread the MAJA’s bit mask and mistakenly labelled shadows as clouds. We regret our error and here we present the updated tables and images. We corrected our estimation and, consequently, there is an increment in MAJA’s accuracy in the detection of clouds and cloud shadows. However, these increments are not enough to change the conclusion of our original paper.

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