Preprints
Filtering by Subject: Forest Sciences
How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass?
Published: 2022-01-10
Subjects: Forest Management, Forest Sciences
Spaceborne lidar sensors have potential to improve the accuracy of forest above-ground biomass (AGB) estimates by providing direct measurements of 3D structure of forests over large spatial scales. The ICESat-2 (Ice, Cloud and land Elevation Satellite 2), launched in 2018, provides a good coverage of the boreal forest zone and has been previously shown to provide good estimates of forest canopy [...]
Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass in heterogenous landscapes
Published: 2021-12-14
Subjects: Environmental Monitoring, Environmental Sciences, Forest Sciences, Research Methods in Life Sciences
Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest aboveground biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering – that is, excluding returns from LiDAR point clouds based on simple height thresholds – is a common practice meant to [...]
rassta: Raster-Based Spatial Stratification Algorithms
Published: 2021-11-17
Subjects: Agriculture, Ecology and Evolutionary Biology, Forest Sciences, Life Sciences
Spatial stratification of landscapes allows for the development of efficient sampling surveys, the inclusion of domain knowledge in data-driven modeling frameworks, and the production of information relating the spatial variability of response phenomena to that of landscape processes. This work presents the rassta package as a collection of algorithms dedicated to the spatial stratification of [...]
Airborne laser scanning proxies of canopy light transmission in forests
Published: 2021-10-29
Subjects: Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Software Engineering, Statistics and Probability
Reliable estimates of canopy light transmission are critical to understanding the structure and function of vegetation communities but are difficult and costly to attain by traditional field inventory methods. Airborne laser scanning (ALS) data uniquely provide multi-angular vertically resolved representation of canopy geometry across large geographic areas. While previous studies have proposed [...]
Bridging knowledge gaps with hybrid machine-learning forest ecosystem models (ML-FEMs): inferential simulation of past understory light regimes
Published: 2021-10-29
Subjects: Artificial Intelligence and Robotics, Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences
Soil moisture is a key limiting factor of plant productivity in boreal and montane regions, producing additional climate feedbacks through evaporation, regeneration, mortality, and respiration. Understory solar irradiation – the primary driver of surface temperature and evaporative demand – remains poorly represented in vegetation models due to a lack of 3-D canopy geometry. Existing models are [...]
Simulated decline of a northern forest due to anthropogenic controls on the regeneration-mortality balance
Published: 2021-10-29
Subjects: Biodiversity, Biogeochemistry, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences
The population structure of forests is shaped by balancing the opposing forces of regeneration and mortality, each of which influence C turnover rates and are sensitive to climate. Regeneration underlies the migrational potential of forests to climatic change and remains underserved in modeling studies. Our objective was to test the hypothesis that warming may reduce tree regeneration rates while [...]
Emergence of anthropogenic fire regimes in the southern boreal of Canada
Published: 2021-10-29
Subjects: Biogeochemistry, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Plant Sciences
While radiative forcing and thus land surface temperatures have been shown to positively correlate with fire severity, precipitation, and lightning strike frequency, the effects of human activity on fire regimes remain difficult to disentangle from geophysical drivers given co-variation between these factors. Here, I analyze fire regimes in the 1919-2012 period across Canada and compare national [...]
The carbon cycle of southeast Australia during 2019-2020: Drought, fires and subsequent recovery
Published: 2021-05-13
Subjects: Atmospheric Sciences, Environmental Monitoring, Environmental Sciences, Forest Sciences, Physical Sciences and Mathematics
2019 was the hottest and driest year on record for southeast Australia leading to bushfires of unprecedented extent. Ecosystem carbon losses due to drought and fire are believed to have been substantial, but have not been well quantified. Here, we utilize space-based measurements of trace gases (TROPOspheric Monitoring Instrument XCO, Orbiting Carbon Observatory 2 XCO2) and up-scaled GPP (FluxSat [...]
Impacts of a regional multi-year insect defoliation event on seasonal runoff ratios and instantaneous streamflow characteristics
Published: 2020-10-27
Subjects: Forest Sciences, Hydrology, Terrestrial and Aquatic Ecology, Water Resource Management
Repeated moderate severity forest disturbances can cause short- and long-term shifts in ecosystem processes. Prior work has found that stand-replacing disturbances (e.g., clear-cutting) increases streamflow in temperate forests, but streamflow responses to repeated moderate severity disturbances are more equivocal. This study examined a moderate disturbance caused by an unexpected population [...]
Transitioning Machine Learning from Theory to Practice in Natural Resources Management
Published: 2020-10-22
Subjects: Agriculture, Computer Sciences, Environmental Education, Environmental Sciences, Environmental Studies, Forest Management, Forest Sciences, Natural Resources and Conservation, Natural Resources Management and Policy, Water Resource Management
Advances in sensing and computation have accelerated at unprecedented rates and scales, in turn creating new opportunities for natural resources managers to improve adaptive and predictive management practices by coupling large environmental datasets with machine learning (ML). Yet, to date, ML models often remain inaccessible to managers working outside of academic research. To identify [...]
Range-based intensity normalization of ALS data over forested areas using a sensor tracking method from multiple returns
Published: 2020-07-10
Subjects: Education, Engineering, Environmental Monitoring, Environmental Sciences, Forest Management, Forest Sciences, Life Sciences, Natural Resources Management and Policy, Other Forestry and Forest Sciences, Physical Sciences and Mathematics
Airborne laser scanning (ALS) point-clouds are used in forest inventory to map properties of the resource. In most cases, only the (x,y,z) coordinates of the point cloud are used to build predictive models of forest structure. Despite being recorded and provided by data suppliers, the intensity values associated with each point are rarely used as an input to such models because raw intensity [...]
Probabilistic soil moisture dynamics of water- and energy-limited ecosystems
Published: 2020-05-17
Subjects: Agriculture, Agronomy and Crop Sciences Life Sciences, Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Forest Sciences, Hydrology, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Statistical Models, Statistics and Probability
This paper presents an extension of the stochastic ecohydrological model for soil moisture dynamics at a point of Rodriguez-Iturbe et al. (1999) and Laio et al. (2001). In the original model, evapotranspiration is a function of soil moisture and vegetation parameters, so that the model is suitable for water-limited environments. Our extension introduces a dependence on maximum evapotranspiration [...]
Concepts of space, time and scale
Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Social and Behavioral Sciences
Concepts of space, time and scale as well as their underpinning theories are crucial for understanding geospatial data. Space can be defined as a boundless, three-dimensional (3D) extent in which objects and events occur and have relative position and direction. Space has been considered to be absolute, meaning that it exists permanently and independently regardless of any matter in space. [...]
Fundamental laws and principles in geoinformation science
Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Social and Behavioral Sciences
Scientific laws are empirical statements, based on repeated experiments or observations, that describe or predict a range of natural phenomena. There are scientific laws and law-like statements also in the field of geoinformation sciences. Based on the Tobler’s first law of geography, “everything is related to everything else, but near things are more related than distant things”. This first law [...]
Individual tree detection and characterization using 3D remote sensing
Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Remote Sensing, Social and Behavioral Sciences
Here, we will cover individual tree detection and characterization using 3D remote sensing. Simply, it means that point clouds are collected over a forested area using airborne laser scanning (ALS) or created using photogrammetric image interpretation and further used to detect individual trees using different algorithms. After the tree detection, the attributes of interest are predicted for each [...]