Using low-density discrete Airborne Laser Scanning data to assess the potential carbon dioxide emission in case of a fire event in a Mediterranean pine forest

This study assesses model temporal transferability using airborne laser scanning (ALS) data acquired over two different dates. Seven forest attributes (i.e. stand density, basal area, squared mean diameter, dominant diameter, tree dominant height, timber volume, and total tree biomass) were estimated using an area-based approach in Mediterranean Aleppo pine forests. Low-density ALS data were acquired in 2011 and 2016 while 147 forest inventory plots were measured in 2013, 2014, and 2016. Single-tree growth models were used to generate concomitant field data for 2011 and 2016. A comparison of five selection techniques and five regression methods were performed to regress field observations against ALS metrics. The selection of the best regression models fitted for each stand attribute, and separately for both 2011 and 2016, was performed following an indirect approach. Model performance and temporal transferability were analyzed by extrapolating the best fitted models from 2011 to 2016 and inversely from 2016 to 2011 using the direct approach. Non-parametric support vector machine with radial kernel was the best regression method with average relative % root mean square error differences of 2.13% for 2011 models and 1.58% for 2016 ones.

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Comparison of Airborne Laser Scanning (3D) with Sentinel-2 (2D) for Estimating Above Ground Biomass/Carbon Stock in a Subtropical Chir Pine Forest of Balakot, Pakistan

10.21203/rs.3.rs-173795/v1 ◽

2021 ◽

Author(s):

Sami Ullah ◽

Tahir Saeed ◽

Muhammad Shafique ◽

Muhammad Saad ◽

Adnan Khan

Keyword(s):

Carbon Stock ◽

Laser Scanning ◽

Forest Ecosystems ◽

Pine Forest ◽

Airborne Laser Scanning ◽

Biomass Carbon ◽

Above Ground Biomass ◽

Airborne Laser ◽

Chir Pine ◽

Sentinel 2

Abstract Forest ecosystems act as a sink of atmospheric carbon dioxide in the form of biomass, and plays one of the crucial role for carbon sequestration and in regulating the global carbon cycle. Few studies based on ground sample plots were conducted for estimating forest biomass/carbon stock across Pakistan. This study comparing the first time the potential of three dimensional (3D) airborne laser scanning (ALS) with two dimensional (2D) Sentinel-2 to estimate above-ground biomass/carbon stock (AGB/C) in a Subtropical Chir Pine forest of Balakot, Pakistan. We derived height and density metrics from the ALS canopy height model (CHM), and different metrics from Sentinel-2 images, and were regressed with field measured AGB/C at sample plots locations. We found R2 = 0.86 with RMSE% = 25.70, and R2 = 0.62 with RMSE% = 43.92 for ALS and for Sentinel-2 respectively with ground measured AGB/C at sample plots locations. Our study demonstrated that 3D ALS technology has greater potential and is the most accurate option as compared to 2D Sentinel-2 for regular planning and monitoring of AGB/C in the context of the national forest inventory of Pakistan. Our study will be useful for the accomplishment of the REDD+ in measuring, reporting, and verification of forest resources, and future sustainable utilization of forest, safeguarding the livelihoods of forest-dependent people, and reducing pressure on forest ecosystems.

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COMPARISON OF HIGH AND LOW DENSITY AIRBORNE LIDAR DATA FOR FOREST ROAD QUALITY ASSESSMENT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iii-8-167-2016 ◽

2016 ◽

Vol III-8 ◽

pp. 167-172

Author(s):

K. Kiss ◽

J. Malinen ◽

T. Tokola

Keyword(s):

Laser Scanning ◽

High Density ◽

Road Surface ◽

Airborne Laser Scanning ◽

Low Density ◽

Surface Wear ◽

Forest Roads ◽

Density Data ◽

The Road ◽

Airborne Laser

Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31–92%) than on low-density data (25–40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.

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Airborne Laser Scanning Cartography of On-Site Carbon Stocks as a Basis for the Silviculture of Pinus Halepensis Plantations

Remote Sensing ◽

10.3390/rs10101660 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1660 ◽

Cited By ~ 5

Author(s):

Rafael Navarro-Cerrillo ◽

Joaquín Duque-Lazo ◽

Carlos Rodríguez-Vallejo ◽

Mª Varo-Martínez ◽

Guillermo Palacios-Rodríguez

Keyword(s):

Laser Scanning ◽

Pinus Halepensis ◽

C Sequestration ◽

Airborne Laser Scanning ◽

Forest Monitoring ◽

Low Density ◽

Airborne Laser ◽

Monitoring Strategies ◽

C Stock ◽

Intervention Scenario

Forest managers are interested in forest-monitoring strategies using low density Airborne Laser Scanning (ALS). However, little research has used ALS to estimate soil organic carbon (SOC) as a criterion for operational thinning. Our objective was to compare three different thinning intensities in terms of the on-site C stock after 13 years (2004–2017) and to develop models of biomass (Wt, Mg ha−1) and SOC (Mg ha−1) in Pinus halepensis forest, based on low density ALS in southern Spain. ALS was performed for the area and stand metrics were measured within 83 plots. Non-parametric kNN models were developed to estimate Wt and SOC. The overall C stock was significantly higher in plots subjected to heavy or moderate thinning (101.17 Mg ha−1 and 100.94 Mg ha−1, respectively) than in the control plots (91.83 Mg ha−1). The best Wt and SOC models provided R2 values of 0.82 (Wt, MSNPP) and 0.82 (SOC-S10, RAW). The study area will be able to stock 134,850 Mg of C under a non-intervention scenario and 157,958 Mg of C under the heavy thinning scenario. High-resolution cartography of the predicted C stock is useful for silvicultural planning and may be used for proper management to increase C sequestration in dry P. halepensis forests.

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Quantification of Lichen Cover and Biomass Using Field Data, Airborne Laser Scanning and High Spatial Resolution Optical Data—A Case Study from a Canadian Boreal Pine Forest

Forests ◽

10.3390/f11060682 ◽

2020 ◽

Vol 11 (6) ◽

pp. 682

Author(s):

Ashley C. Hillman ◽

Scott E. Nielsen

Keyword(s):

High Resolution ◽

Spectral Data ◽

Laser Scanning ◽

Canopy Cover ◽

Jack Pine ◽

Pine Forest ◽

Airborne Laser Scanning ◽

Woodland Caribou ◽

Airborne Laser ◽

Pine Stands

Ground-dwelling macrolichens dominate the forest floor of mature upland pine stands in the boreal forest. Understanding patterns of lichen abundance, as well as environmental characteristics associated with lichen growth, is key to managing lichens as a forage resource for threatened woodland caribou (Rangifer tarandus caribou). The spectral signature of light-coloured lichen distinguishes it from green vegetation, potentially allowing for mapping of lichen abundance using multi-spectral imagery, while canopy structure measured from airborne laser scanning (ALS) of forest openings can indirectly map lichen habitat. Here, we test the use of high-resolution KOMPSAT (Korea Multi-Purpose Satellite-3) imagery (280 cm resolution) and forest structural characteristics derived from ALS to predict lichen biomass in an upland jack pine forest in Northeastern Alberta, Canada. We quantified in the field lichen abundance (cover and biomass) in mature jack pine stands across low, moderate, and high canopy cover. We then used generalized linear models to relate lichen abundance to spectral data from KOMPSAT and structural metrics from ALS. Model selection suggested that lichen abundance was best predicted by canopy cover (ALS points > 1.37 m) and to a lesser extent blue spectral data from KOMPSAT. Lichen biomass was low at plots with high canopy cover (98.96 g/m2), while almost doubling for plots with low canopy cover (186.30 g/m2). Overall the model fit predicting lichen biomass was good (R2 c = 0.35), with maps predicting lichen biomass from spectral and structural data illustrating strong spatial variations. High-resolution mapping of ground lichen can provide information on lichen abundance that can be of value for management of forage resources for woodland caribou. We suggest that this approach could be used to map lichen biomass for other regions.

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