scholarly journals Does Sentinel-1A Backscatter Capture the Spatial Variability in Canopy Gaps of Tropical Agroforests? A Proof-of-Concept in Cocoa Landscapes in Cameroon

2020 ◽  
Vol 12 (24) ◽  
pp. 4163
Author(s):  
Frederick N. Numbisi ◽  
Frieke Van Coillie
Keyword(s):  
Spatial Variability ◽  
Spatial Correlation ◽  
Canopy Cover ◽  
Canopy Gaps ◽  
Canopy Gap ◽  
Forest Landscape ◽  
Proof Of Concept ◽  
Backscatter Intensity ◽  
Gap Fraction ◽  
Cocoa Production

A reliable estimation and monitoring of tree canopy cover or shade distribution is essential for a sustainable cocoa production via agroforestry systems. Remote sensing (RS) data offer great potential in retrieving and monitoring vegetation status at landscape scales. However, parallel advancements in image processing and analysis are required to appropriately use such data for different targeted applications. This study assessed the potential of Sentinel-1A (S-1A) C-band synthetic aperture radar (SAR) backscatter in estimating canopy cover variability in cocoa agroforestry landscapes. We investigated two landscapes, in Center and South Cameroon, which differ in predominant vegetation: forest-savannah transition and forest landscape, respectively. We estimated canopy cover using in-situ digital hemispherical photographs (DHPs) measures of gap fraction, verified the relationship with SAR backscatter intensity and assessed predictions based on three machine learning approaches: multivariate bootstrap regression, neural networks regression, and random forest regression. Our results showed that about 30% of the variance in canopy gap fraction in the cocoa production landscapes was shared by the used SAR backscatter parameters: a combination of S-1A backscatter intensity, backscatter coefficients, difference, cross ratios, and normalized ratios. Based on the model predictions, the VV (co-polarization) backscatter showed high importance in estimating canopy gap fraction; the VH (cross-polarized) backscatter was less sensitive to the estimated canopy gap. We observed that a combination of different backscatter variables was more reliable at predicting the canopy gap variability in the considered type of vegetation in this study—agroforests. Semi-variogram analysis of canopy gap fraction at the landscape scale revealed higher spatial clustering of canopy gap, based on spatial correlation, at a distance range of 18.95 m in the vegetation transition landscape, compared to a 51.12 m spatial correlation range in the forest landscape. We provide new insight on the spatial variability of canopy gaps in the cocoa landscapes which may be essential for predicting impacts of changing and extreme (drought) weather conditions on farm management and productivity. Our results contribute a proof-of-concept in using current and future SAR images to support management tools or strategies on tree inventorying and decisions regarding incentives for shade tree retention and planting in cocoa landscapes.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

Distribution of epicormic branches and foliage on Douglas-fir as influenced by adjacent canopy gaps

2018 ◽  
Vol 48 (11) ◽  
pp. 1320-1330
Author(s):  
John W. Punches ◽  
Klaus J. Puettmann
Keyword(s):  
Branch Length ◽  
Canopy Gaps ◽  
Douglas Fir ◽  
Canopy Gap ◽  
Tree Age ◽  
Gap Size ◽  
Terminal Bud ◽  
Total Branch Length ◽  
A Minor ◽  
Epicormic Branches

The influence of adjacent canopy gaps on spatial distribution of epicormic branches and delayed foliage (originating from dormant buds) was investigated in 65-year-old coastal Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco). Sample trees were selected across a broad range of local densities (adjacent canopy gap sizes) from a repeatedly thinned stand in which gaps had been created 12 years prior to our study. Lengths and stem locations of original and epicormic branches were measured within the south-facing crown quadrant, along with extents to which branches were occupied by sequential (produced in association with terminal bud elongation) and (or) delayed foliage. Epicormic branches, while prevalent throughout crowns, contributed only 10% of total branch length and 2% of total foliage mass. In contrast, delayed foliage occupied over 75% of total branch length, accounted for nearly 39% of total foliage mass, and often overlapped with sequential foliage. Canopy gap size did not influence original or epicormic branch length or location. On original branches, larger gaps may have modestly negatively influenced the relative extent of sequential foliage on branches and (or) slightly positively influenced delayed foliage mass. Delayed foliage appears to contribute substantially to Douglas-fir crown maintenance at this tree age, but canopy gap size had a minor influence, at least in the short term.

scholarly journals Canopy gap edge determination and the importance of gap edges for plant diversity

Web Ecology ◽  
2002 ◽  
Vol 3 (1) ◽  
pp. 1-5 ◽  
Author(s):  
D. Salvador-Van Eysenrode ◽  
F. Kockelbergh ◽  
J. Bogaert ◽  
I. Impens ◽  
P. Van Hecke
Keyword(s):  
Fagus Sylvatica ◽  
Plant Diversity ◽  
Forest Cover ◽  
Beech Forest ◽  
Canopy Gaps ◽  
Canopy Gap ◽  
Structural Elements ◽  
Forest Patch ◽  
Young Forest ◽  
Maintenance Of Diversity

Abstract. Canopy gaps, i.e. openings in the forest cover caused by the fall of structural elements, are considered to be important for the maintenance of diversity and for the forest cycle. A gap can be considered as a young forest patch in the forest matrix, composed of interior surrounded by an edge, both enclosed by a perimeter. Much of the attention has been focused on the gap interior. However, at gap edges the spectrum of regeneration opportunities for plants may be larger than in the interior. Although definitions of gap are still discussed, any definition can describe it in an acceptable way, if justified, but defining edges is complicated and appropriate descriptors should be used. A method to determine gap interior and edge, using light as a descriptor, is presented with an example of gaps from a beech forest (Fagus sylvatica) in Belgium. Also, the relevance and implications of gap edges for plant diversity and calculation of forest turnover is discussed.

scholarly journals Restoration of above canopy reference hemispherical image from below canopy measurements for plant area index estimation in forests/ Metsa võrastiku läbipaistvuse mõõtmine digitaalsete poolsfäärikaamerate abil

2013 ◽  
Vol 59 (1) ◽  
pp. 13-27 ◽  
Author(s):  
Mait Lang ◽  
Ave Kodar ◽  
Tauri Arumäe
Keyword(s):  
Field Measurements ◽  
Incident Radiation ◽  
Canopy Gap ◽  
Raw Data ◽  
Area Index ◽  
Gap Fraction ◽  
Cmos Sensor ◽  
Plant Area Index ◽  
Plant Area ◽  
Thresholding Algorithm

Abstract Canopy gap fraction has been estimated from hemispherical images using a thresholding method to separate sky and canopy pixels. The optimal objective thresholding rule has been searched by many authors without satisfactory results due to long list of reasons. Some recent studies have shown that unprocessed readings of camera CCD or CMOS sensor (raw data) have linear relationship with incident radiation. This allows a pair of cameras used in similar to a pair of plant canopy analyzers and canopy gap fraction can be calculated as the ratio of below canopy image and above canopy image. We tested new freeware program HemiSpherical Project Manager (HSP) for the restoration of the above canopy image from below canopy image which allows making field measurements with single below canopy operated camera. Results of perforated panel image analysis and comparison of plant area index (PAI) estimated independently by three operators from real canopy hemispherical images showed high degree of reliability of the new approach. Determination coefficients of linear regression of the PAI estimations of the three operators were 0.9962, 0.9875 and 0.9825. The canopy gap fraction data obtained from HSP were used to validate Nobis-Hunziker automatic thresholding algorithm. The results indicated that the Nobis-Hunziker algorithm underestimated PAI from out of camera JPEG images and overestimated PAI from raw data.

Use of airborne lidar for estimating canopy gap fraction and leaf area index of tropical montane forests

2015 ◽  
Vol 36 (10) ◽  
pp. 2569-2583 ◽  
Author(s):  
Janne Heiskanen ◽  
Lauri Korhonen ◽  
Jesse Hietanen ◽  
Petri K.E. Pellikka
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Canopy Gap ◽  
Airborne Lidar ◽  
Montane Forests ◽  
Area Index ◽  
Tropical Montane Forests ◽  
Gap Fraction

Estimating canopy gap fraction and diffuse light interception in 3D maize canopy using hierarchical hemispheres

2019 ◽  
Vol 276-277 ◽  
pp. 107594 ◽  
Author(s):  
Weiliang Wen ◽  
Xinyu Guo ◽  
Baojun Li ◽  
Chuanyu Wang ◽  
Yongjian Wang ◽  
...  
Keyword(s):  
Light Interception ◽  
Canopy Gap ◽  
Diffuse Light ◽  
Gap Fraction

Ecosystem Structure throughout the Brazilian Amazon from Landsat Observations and Automated Spectral Unmixing

2005 ◽  
Vol 9 (7) ◽  
pp. 1-31 ◽  
Author(s):  
Gregory P. Asner ◽  
David E. Knapp ◽  
Amanda N. Cooper ◽  
Mercedes M. C. Bustamante ◽  
Lydia P. Olander
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Brazilian Amazon ◽  
Canopy Gap ◽  
Amazon Forest ◽  
Ecosystem Structure ◽  
Gap Fraction ◽  
Cerrado Savanna ◽  
Spectral Mixture

Abstract The Brazilian Amazon forest and cerrado savanna encompasses a region of enormous ecological, climatic, and land-use variation. Satellite remote sensing is the only tractable means to measure the biophysical attributes of vegetation throughout this region, but coarse-resolution sensors cannot resolve the details of forest structure and land-cover change deemed critical to many land-use, ecological, and conservation-oriented studies. The Carnegie Landsat Analysis System (CLAS) was developed for studies of forest and savanna structural attributes using widely available Landsat Enhanced Thematic Mapper Plus (ETM+) satellite data and advanced methods in automated spectral mixture analysis. The methodology of the CLAS approach is presented along with a study of its sensitivity to atmospheric correction errors. CLAS is then applied to a mosaic of Landsat images spanning the years 1999–2001 as a proof of concept and capability for large-scale, very high resolution mapping of the Amazon and bordering cerrado savanna. A total of 197 images were analyzed for fractional photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare substrate covers using a probabilistic spectral mixture model. Results from areas without significant land use, clouds, cloud shadows, and water bodies were compiled by the Brazilian state and vegetation class to understand the baseline structural typology of forests and savannas using this new system. Conversion of the satellite-derived PV data to woody canopy gap fraction was made to highlight major differences by vegetation and ecosystem classes. The results indicate important differences in fractional photosynthetic cover and canopy gap fraction that can now be accounted for in future studies of land-cover change, ecological variability, and biogeochemical processes across the Amazon and bordering cerrado regions of Brazil.

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