Andy Hudak - Academia.edu (original) (raw)
Papers by Andy Hudak
Fire Ecology, Apr 29, 2019
Fire Ecology, Aug 26, 2019
Fire Ecology, Dec 5, 2022
Fire Ecology, Aug 9, 2022
Forest Ecology and Management
Geomatics, Natural Hazards and Risk
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
GEDI Satellite laser mission will take 3D data globally from International Space Station. The sen... more GEDI Satellite laser mission will take 3D data globally from International Space Station. The sensor has an improved navigation system to position laser shooting areas accurately. However, the ground validation is still difficult due to the misalignment caused by poor reception of GPS signals under the thick forest. This study introduces a new way to get more accurate ground positioning of trees in tropical forest using 3D data matching technique between airborne and terrestrial data. Our study site is in tropical forest at Robson Creek, Australia. RMSE of XY directions was 0.5 m in and Z direction was 0.6 m, which was impossible to achieve efficiently from the traditional positioning by GPS under dense canopy. The 3D data taken by terrestrial laser is not only useful for capturing structure data for the validation of the waveform analysis of satellite laser but also helps to position accurate ground coordinates in tropical forest through this technique.
International Journal of Wildland Fire
Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated... more Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated in non-oxidising environments. Results are applied to wildland fires where fuels change spatially and temporally, resulting in variable fire behaviour with variable heating. Though historically used, applicability of traditional pyrolysis results to the wildland fire setting is unknown. Pyrolytic and flaming combustion gases measured in wind tunnel fires and prescribed burns were compared using compositional data techniques. CO2 was dominant in both. Other dominant gases included CO, H2 and CH4. Relative amounts of CO, CO2 and CH4 were similar between fire phases (pyrolysis, flaming combustion); relatively more H2 was observed in pyrolysis samples. All gas log-ratios with CO2 in pyrolysis samples were larger than in flaming combustion samples. Presence of live plants significantly affected gas composition. A logistic regression model correctly classified 76% of the wind tunnel samples a...
AGU Fall Meeting Abstracts, Dec 1, 2016
AGU Fall Meeting Abstracts, Dec 1, 2018
AGU Fall Meeting Abstracts, Dec 1, 2020
Forest soil ecosystems include some of the most complex microbial communities on Earth (Fierer et... more Forest soil ecosystems include some of the most complex microbial communities on Earth (Fierer et al. 2012). These assemblages of archaea, bacteria, fungi, and protists play essential roles in biogeochemical cycles (van der Heijden et al. 2008) and account for considerable terrestrial biomass (Nielsen et al. 2011). Yet, determining the microbial composition of forest soils remains a great challenge due in part to their overwhelming diversity and variability. Until recently, studies of microbial diversity in natural systems have relied on clonal cultures. Early environmental gene sequencing, which cloned specific genes to produce a profile of diversity in a natural sample, revealed that the vast majority of microbial diversity had been overlooked using these direct cultivation methods.
Remote Sensing of Environment, 2021
Abstract Increased focus on restoring forest structural variation and spatial pattern in dry coni... more Abstract Increased focus on restoring forest structural variation and spatial pattern in dry conifer forests has led to greater emphasis on forest monitoring strategies that can be summarized across scales. To inform restoration objectives with data sources that can characterize individual trees, groups of trees, and the entire stand, different remote sensing strategies such as aerial and terrestrial light detection and ranging (LiDAR) have been explored. Unfortunately, high equipment and operational costs of aerial systems, along with limited spatial extent of terrestrial scanners, have restricted widespread adoption of these technologies for repeated forest monitoring. This study investigates applications of unmanned aerial system (UAS) imagery for Structure from Motion derived modeling of individual tree and stand-level metrics. Specifically, we evaluate how flight parameters impact UAS extracted height and imputed DBH accuracies against field stem-mapped values. In total, 30 UAS image datasets collected from combinations of three altitudes, two flight patterns, and five camera orientations were assessed. Tree heights were extracted using a variable window function that searched UAS-derived canopy height models, while DBH was sampled from point cloud slices at 1.32–1.42 m using a least squares circle fitting algorithm. The sample trees were then filtered against National Forest Inventory data from the study region to ensure reasonable matching of extracted heights and diameters. The matched values were used to create a height to diameter relationship for predicting missing DBH values. Extracted and imputed tree values were compared against stem-mapped values to determine tree commission and omission rates, the accuracy and precision of extracted tree height, DBH, as well as overstory and understory stand density. Finding that, 1) tree extraction accuracy and correctness was maximized (F-score = 0.77) for nadir crosshatch UAS flight designs; 2) extracted tree height R2 with stem-mapped values was high (R2 ≥ 0.98) for all UAS flight parameters, but the quality (mean error = 0.79 cm) and quantity (~10% of all trees) of extracted DBH values was maximized for lower altitude, nadir crosshatch acquisitions; 3) the distribution of predicted DBH values most closely matched field observed values for off-nadir crosshatch flight designs; 4) using either off-nadir or crosshatch flight designs at lower altitudes maximized correlation (r > 0.70) and accuracy (basal area within 2 m2 ha−1) of stand density estimates. This study demonstrates a novel UAS-based inventory strategy for estimating individual tree structural attributes (i.e., location, height, and DBH) in dry conifer forests, without the need for in situ field observations.
Forest Service Research Data Archive
International Journal of Wildland Fire, 2018
Fire radiative energy density (FRED, Jm-2) integrated from fire radiative power density (FRPD, Wm... more Fire radiative energy density (FRED, Jm-2) integrated from fire radiative power density (FRPD, Wm-2) observations of landscape-level fires can present an undersampling problem when collected from fixed-wing aircraft. In the present study, the aircraft made multiple passes over the fire at ~3min intervals, thus failing to observe most of the FRPD emitted as the flame front spread. We integrated the sparse FRPD time series to obtain pixel-level FRED estimates, and subsequently applied ordinary kriging (OK) and Gaussian conditional simulation (GCS) to interpolate across data voids caused by the undersampling. We compared FRED interpolated via OK and GCS with FRED estimated independently from ground measurements of biomass consumed from five prescribed burns at Eglin Air Force Base, Florida, USA. In four of five burns considered where undersampling prevailed, OK and GCS effectively interpolated FRED estimates across the data voids, improving the spatial distribution of FRED across the b...
Fire Ecology, Apr 29, 2019
Fire Ecology, Aug 26, 2019
Fire Ecology, Dec 5, 2022
Fire Ecology, Aug 9, 2022
Forest Ecology and Management
Geomatics, Natural Hazards and Risk
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
GEDI Satellite laser mission will take 3D data globally from International Space Station. The sen... more GEDI Satellite laser mission will take 3D data globally from International Space Station. The sensor has an improved navigation system to position laser shooting areas accurately. However, the ground validation is still difficult due to the misalignment caused by poor reception of GPS signals under the thick forest. This study introduces a new way to get more accurate ground positioning of trees in tropical forest using 3D data matching technique between airborne and terrestrial data. Our study site is in tropical forest at Robson Creek, Australia. RMSE of XY directions was 0.5 m in and Z direction was 0.6 m, which was impossible to achieve efficiently from the traditional positioning by GPS under dense canopy. The 3D data taken by terrestrial laser is not only useful for capturing structure data for the validation of the waveform analysis of satellite laser but also helps to position accurate ground coordinates in tropical forest through this technique.
International Journal of Wildland Fire
Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated... more Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated in non-oxidising environments. Results are applied to wildland fires where fuels change spatially and temporally, resulting in variable fire behaviour with variable heating. Though historically used, applicability of traditional pyrolysis results to the wildland fire setting is unknown. Pyrolytic and flaming combustion gases measured in wind tunnel fires and prescribed burns were compared using compositional data techniques. CO2 was dominant in both. Other dominant gases included CO, H2 and CH4. Relative amounts of CO, CO2 and CH4 were similar between fire phases (pyrolysis, flaming combustion); relatively more H2 was observed in pyrolysis samples. All gas log-ratios with CO2 in pyrolysis samples were larger than in flaming combustion samples. Presence of live plants significantly affected gas composition. A logistic regression model correctly classified 76% of the wind tunnel samples a...
AGU Fall Meeting Abstracts, Dec 1, 2016
AGU Fall Meeting Abstracts, Dec 1, 2018
AGU Fall Meeting Abstracts, Dec 1, 2020
Forest soil ecosystems include some of the most complex microbial communities on Earth (Fierer et... more Forest soil ecosystems include some of the most complex microbial communities on Earth (Fierer et al. 2012). These assemblages of archaea, bacteria, fungi, and protists play essential roles in biogeochemical cycles (van der Heijden et al. 2008) and account for considerable terrestrial biomass (Nielsen et al. 2011). Yet, determining the microbial composition of forest soils remains a great challenge due in part to their overwhelming diversity and variability. Until recently, studies of microbial diversity in natural systems have relied on clonal cultures. Early environmental gene sequencing, which cloned specific genes to produce a profile of diversity in a natural sample, revealed that the vast majority of microbial diversity had been overlooked using these direct cultivation methods.
Remote Sensing of Environment, 2021
Abstract Increased focus on restoring forest structural variation and spatial pattern in dry coni... more Abstract Increased focus on restoring forest structural variation and spatial pattern in dry conifer forests has led to greater emphasis on forest monitoring strategies that can be summarized across scales. To inform restoration objectives with data sources that can characterize individual trees, groups of trees, and the entire stand, different remote sensing strategies such as aerial and terrestrial light detection and ranging (LiDAR) have been explored. Unfortunately, high equipment and operational costs of aerial systems, along with limited spatial extent of terrestrial scanners, have restricted widespread adoption of these technologies for repeated forest monitoring. This study investigates applications of unmanned aerial system (UAS) imagery for Structure from Motion derived modeling of individual tree and stand-level metrics. Specifically, we evaluate how flight parameters impact UAS extracted height and imputed DBH accuracies against field stem-mapped values. In total, 30 UAS image datasets collected from combinations of three altitudes, two flight patterns, and five camera orientations were assessed. Tree heights were extracted using a variable window function that searched UAS-derived canopy height models, while DBH was sampled from point cloud slices at 1.32–1.42 m using a least squares circle fitting algorithm. The sample trees were then filtered against National Forest Inventory data from the study region to ensure reasonable matching of extracted heights and diameters. The matched values were used to create a height to diameter relationship for predicting missing DBH values. Extracted and imputed tree values were compared against stem-mapped values to determine tree commission and omission rates, the accuracy and precision of extracted tree height, DBH, as well as overstory and understory stand density. Finding that, 1) tree extraction accuracy and correctness was maximized (F-score = 0.77) for nadir crosshatch UAS flight designs; 2) extracted tree height R2 with stem-mapped values was high (R2 ≥ 0.98) for all UAS flight parameters, but the quality (mean error = 0.79 cm) and quantity (~10% of all trees) of extracted DBH values was maximized for lower altitude, nadir crosshatch acquisitions; 3) the distribution of predicted DBH values most closely matched field observed values for off-nadir crosshatch flight designs; 4) using either off-nadir or crosshatch flight designs at lower altitudes maximized correlation (r > 0.70) and accuracy (basal area within 2 m2 ha−1) of stand density estimates. This study demonstrates a novel UAS-based inventory strategy for estimating individual tree structural attributes (i.e., location, height, and DBH) in dry conifer forests, without the need for in situ field observations.
Forest Service Research Data Archive
International Journal of Wildland Fire, 2018
Fire radiative energy density (FRED, Jm-2) integrated from fire radiative power density (FRPD, Wm... more Fire radiative energy density (FRED, Jm-2) integrated from fire radiative power density (FRPD, Wm-2) observations of landscape-level fires can present an undersampling problem when collected from fixed-wing aircraft. In the present study, the aircraft made multiple passes over the fire at ~3min intervals, thus failing to observe most of the FRPD emitted as the flame front spread. We integrated the sparse FRPD time series to obtain pixel-level FRED estimates, and subsequently applied ordinary kriging (OK) and Gaussian conditional simulation (GCS) to interpolate across data voids caused by the undersampling. We compared FRED interpolated via OK and GCS with FRED estimated independently from ground measurements of biomass consumed from five prescribed burns at Eglin Air Force Base, Florida, USA. In four of five burns considered where undersampling prevailed, OK and GCS effectively interpolated FRED estimates across the data voids, improving the spatial distribution of FRED across the b...