PILOT STUDY ON THE RETRIEVAL OF DBH AND DIAMETER DISTRIBUTION OF DECIDUOUS FOREST STANDS USING CAST SHADOWS IN UAV-BASED ORTHOMOSAICS

One fundamental metric to characterize trees and forest stands is the diameter at breast height (DBH). However, the vertical geometry of tree stems hampers a direct measurement by means of orthographic aerial imagery. Nevertheless, the DBH in deciduous forest stands could be measured from UAV-based imagery using the width of a stem´s cast shadow projected on the ground. Here, we compare in-situ measured DBH of 100 trees with the DBH visually interpreted from cast-shadows derived in UAV-based aerial imagery. Then, based on simulated datasets, we determine suitable DBH sampling sizes for a robust and efficient retrieval of stand diameter distributions. The UAV-based DBH estimation resulted in an r2 of 0.74, RMSE of 7.61 cm, NRMSE of 12.8 % and approximately unbiased results. According to our simulations it can be assumed that a sample size of 25–50 individual DBH measurements per forest stand allows estimating reliable diameter distributions. The presented pilot study gives a first insight on the potential of such an approach for operational assessments of diameter distribution in deciduous forest stands and might be particularly interesting for stands in difficult terrain situations. The presented approach can be extended to estimate the basal area, timber stock or biomass

A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990-2018

The Tibetan Plateau is a unique, biodiverse ecosystem with an important role in the climate and hydrological system of Asia. Its vegetation supports important functions including fodder provision, erosion prevention and water retention. Assessing vegetation trends of the Tibetan Plateau is crucial to understand effects of recent climate and land-use changes. Most existing vegetation trend products covering the entire Tibetan Plateau have a coarse spatial grain and cover short temporal ranges. This hampers their applicability in studies conducted at local scales where land-use decisions take place and at time scales where climate changes become apparent. Here, we present vegetation trend products for the entire Tibetan Plateau at a spatial resolution of 30 m for the time period 1990–2018. These products include results of a modified Mann-Kendall trend test applied to annual Landsat-based NDVI mosaics, composed from all satellite observations acquired during the vegetation periods as well as NDVI difference images. These data can be valuable to many researchers including for example wildlife ecologists, rangeland experts and climate change researchers

Monitoring solifluction movement in space and time: A semi-automated high-resolution approach

Solifluction is the slow downslope movement of soil mass due to freeze-thaw processes. It is widespread on hillslopes in Polar and Alpine regions and contributes substantially to sediment transport. As solifluction lobe movement is in the order of millimeters to centimeters per year, it is difficult to measure with high spatial and temporal resolution and accuracy. In this study we developed a semi-automated approach to monitor movement using unmanned aerial vehicles, image co-alignment, and COSI-Corr (Co-registration of Optically Sensed Images and Correlation) to track slope movement from orthophotos. The method was applied on yearly images acquired between 2017 and 2021 of three solifluction lobes with different degrees of vegetation cover along an elevational gradient in Turtmann Valley, Swiss Alps. We found movement patterns across all three lobes with highest movement rates at the solifluction lobes center and lowest rates at lobe fronts. Overall, at the highest elevations (2560 m) lobe movement rates were highest with up to 14.0 cm yr−1 and intermediate elevations (2417 m) had the lowest values up to 2.9 cm yr−1. The lobe at the lowest elevation (2170 m) showed intermediate movement rates with up to 4.9 cm yr−1 for single years. Our monitoring approach provides yearly, spatially extensive movement estimates across the complete spatial extent of a lobe for each 1 cm2 of its surface, strongly increasing measurement resolution in comparison to traditional solifluction monitoring approaches using point measurements. In comparison to previous close-range remote sensing approaches, the use of a co-alignment procedure for the acquired drone data enabled a time-saving field setup without Ground Control Points (GCPs). The resulting high co-registration accuracy enabled us to detect solifluction movement if it exceeds 5 mm with sparse vegetation cover. Dense vegetation cover limited feature-tracking but detected movement rates and patterns are in the same order of magnitude and matched previous measurements using classical total station measurements at the lowest, mostly vegetated lobe. This study demonstrates the use of drone-based Digital Elevation Models (DEMs) and orthophotos in a semi-automated method which reaches the high spatiotemporal resolution necessary to detect subtle movements of solifluction lobes at yearly intervals at the sub-centimeter scale. This provides new insights into solifluction movement and how much it contributes to sediment transport. Therefore, our semi-automated approach has a great potential to uncover the fundamental processes and better understand solifluction movement

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Avances en teledetección para la prevención y detección temprana de Xylella fastidiosa en el marco de los proyectos H2020 POnTE y XF-ACTORS.

Informational article of the tasks carried out in WP6 of POnTE and WP3 of XF-ACTORS in a professional Spanish magazin

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives