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Iskalni niz: "ključne besede" (sensing) .

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Retrieval of vertical mass concentration distributions
Longlong Wang, Samo Stanič, Klemen Bergant, William Eichinger, Griša Močnik, Luka Drinovec, Janja Vaupotič, Miloš Miler, Mateja Gosar, Asta Gregorič, 2019

Povzetek: Aerosol vertical profiles are valuable inputs for the evaluation of aerosol transport models, in order to improve the understanding of aerosol pollution ventilation processes which drive the dispersion of pollutants in mountainous regions. With the aim of providing high-accuracy vertical distributions of particle mass concentration for the study of aerosol dispersion in small-scale valleys, vertical profiles of aerosol mass concentration for aerosols from different sources (including Saharan dust and local biomass burning events) were investigated over the Vipava valley, Slovenia, a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin. The analysis was based on datasets taken between 1–30 April 2016. In-situ measurements of aerosol size, absorption, and mass concentration were combined with lidar remote sensing, where vertical profiles of aerosol concentration were retrieved. Aerosol samples were characterized by SEM-EDX, to obtain aerosol morphology and chemical composition. Two cases with expected dominant presence of different specific aerosol types (mineral dust and biomass-burning aerosols) show significantly different aerosol properties and distributions within the valley. In the mineral dust case, we observed a decrease of the elevated aerosol layer height and subsequent spreading of mineral dust within the valley, while in the biomass-burning case we observed the lifting of aerosols above the planetary boundary layer (PBL). All uncertainties of size and assumed optical properties, combined, amount to the total uncertainty of aerosol mass concentrations below 30% within the valley. We have also identified the most indicative in-situ parameters for identification of aerosol type.
Ključne besede: valley air pollution, aerosol vertical distributions, lidar remote sensing, in-situ measurements, aerosol identification
DiRROS - Objavljeno: 03.03.2022; Ogledov: 145; Prenosov: 54
URL Celotno besedilo (0,00 KB)

Empirical approach for modelling tree phenology in mixed forests using remote sensing
Koffi Dodji Noumonvi, Gal Oblišar, Ana Žust, Urša Vilhar, 2021

Povzetek: : Phenological events are good indicators of the effects of climate change, since phenological phases are sensitive to changes in environmental conditions. Although several national phenological networks monitor the phenology of different plant species, direct observations can only be conducted on individual trees, which cannot be easily extended over large and continuous areas. Remote sensing has often been applied to model phenology for large areas, focusing mostly on pure forests in which it is relatively easier to match vegetation indices with ground observations. In mixed forests, phenology modelling from remote sensing is often limited to land surface phenology, which consists of an overall phenology of all tree species present in a pixel. The potential of remote sensing for modelling the phenology of individual tree species in mixed forests remains underexplored. In this study, we applied the seasonal midpoint (SM) method with MODIS GPP to model the start of season (SOS) and the end of season (EOS) of six different tree species in Slovenian mixed forests. First, substitute locations were identified for each combination of observation station and plant species based on similar environmental conditions (aspect, slope, and altitude) and tree species of interest, and used to retrieve the remote sensing information used in the SM method after fitting the best of a Gaussian and two double logistic functions to each year of GPP time series. Then, the best thresholds were identified for SOS and EOS, and the results were validated using cross-validation. The results show clearly that the usual threshold of 0.5 is not best in most cases, especially for estimating the EOS. Despite the difficulty in modelling the phenology of different tree species in a mixed forest using remote sensing, it was possible to estimate SOS and EOS with moderate errors as low as <8 days (Fagus sylvatica and Tilia sp.) and <10 days (Fagus sylvatica and Populus tremula), respectively.
Ključne besede: phenology modelling, start of season, end of season, remote sensing, MODIS GPP, vegetation indices, threshold methods
DiRROS - Objavljeno: 23.08.2021; Ogledov: 411; Prenosov: 261
.pdf Celotno besedilo (2,63 MB)

Growing stock monitoring by European National Forest Inventories : historical origins, current methods and harmonisation
Thomas Gschwantner, Iciar Alberdi, Sébastien Bauwens, Susann Bender, Dragan Borota, Michal Bošela, Olivier Bouriaud, Johannes Breidenbach, Janis Donis, Christoph Fischer, Mitja Skudnik, 2022

Povzetek: Wood resources have been essential for human welfare throughout history. Also nowadays, the volume of growing stock (GS) is considered one of the most important forest attributes monitored by National Forest Inventories (NFIs) to inform policy decisions and forest management planning. The origins of forest inventories closely relate to times of early wood shortage in Europe causing the need to explore and plan the utilisation of GS in the catchment areas of mines, saltworks and settlements. Over time, forest surveys became more detailed and their scope turned to larger areas, although they were still conceived as stand-wise inventories. In the 1920s, the first sample-based NFIs were introduced in the northern European countries. Since the earliest beginnings, GS monitoring approaches have considerably evolved. Current NFI methods differ due to country-specific conditions, inventory traditions, and information needs. Consequently, GS estimates were lacking international comparability and were therefore subject to recent harmonisation efforts to meet the increasing demand for consistent forest resource information at European level. As primary large-area monitoring programmes in most European countries, NFIs assess a multitude of variables, describing various aspects of sustainable forest management, including for example wood supply, carbon sequestration, and biodiversity. Many of these contemporary subject matters involve considerations about GS and its changes, at different geographic levels and time frames from past to future developments according to scenario simulations. Due to its historical, continued and currently increasing importance, we provide an up-to-date review focussing on large-area GS monitoring where we i) describe the origins and historical development of European NFIs, ii) address the terminology and present GS definitions of NFIs, iii) summarise the current methods of 23 European NFIs including sampling methods, tree measurements, volume models, estimators, uncertainty components, and the use of air- and space-borne data sources, iv) present the recent progress in NFI harmonisation in Europe, and v) provide an outlook under changing climate and forest-based bioeconomy objectives.
Ključne besede: forest history, natural resources, sustainability, timber volume, sampling, remote sensing, bioeconomy, climate change
DiRROS - Objavljeno: 14.12.2021; Ogledov: 249; Prenosov: 141
.pdf Celotno besedilo (17,73 MB)

Empirical vs. light-use efficiency modelling for estimating carbon fluxes in a mid-succession ecosystem developed on abandoned karst grassland
Koffi Dodji Noumonvi, Mitja Ferlan, 2020

Povzetek: Karst systems represent an important carbon sink worldwide. However, several phenomena such as the CO2 degassing and the exchange of cave air return a considerable amount of CO2 to the atmosphere. It is therefore of paramount importance to understand the contribution of the ecosystem to the carbon budget of karst areas. In this study conducted in a mid-succession ecosystem developed on abandoned karst grassland, two types of model were assessed, estimating the gross primary production (GPP) or the net ecosystem exchange (NEE) based on seven years of eddy covariance data (2013%2019): (1) a quadratic vegetation index-based empirical model with five alternative vegetation indices as proxies of GPP and NEE, and (2) the vegetation photosynthesis model (VPM) which is a light use efficiency model to estimate only GPP. The Enhanced Vegetation Index (EVI) was the best proxy for NEE whereas SAVI performed very similarly to EVI in the case of GPP in the empirical model setting. The empirical model performed better than the VPM model which tended to underestimate GPP. Therefore, for this ecosystem, we suggest the use of the empirical model provided that the quadratic relationship observed persists. However, the VPM model would be a good alternative under a changing climate, as it is rooted in the understanding of the photosynthesis process, if the scalars it involves could be improved to better estimate GPP.
Ključne besede: eddy covariance, carbon flux, GPP, NEE, vegetation indices, remote sensing, satellite data, GPP map
DiRROS - Objavljeno: 03.01.2022; Ogledov: 203; Prenosov: 156
.pdf Celotno besedilo (3,07 MB)

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