No abstract

In 2007, three mature hemi-boreal stands were selected from Järvselja forest district, South-East Estonia to establish one-hectare-large test plots for the international inter-comparison experiment of radiation models (RAMI). All trees with a stem diameter at breast height greater than 4 cm were mapped and measured in the field. In summer 2019, the forests were inventoried again. Here we present a summary of changes that occurred in the forest structure – mainly growth and mortality. In the birch stand basal area G has increased from 23.3 m2 ha-1 to 28.2 m2 ha-1 in the upper layer and the number of trees N has decreased from 654 to 565 ha-1. In the upper layer of spruce stand G has increased from 30.9 m2 ha-1 to 35.4 m2 ha-1 and N has decreased from 774 to 724 ha-1 and N substantially decreased in the lower layers from 912 to 577 ha-1. In the pine stand G has increased from 28.3 m2 ha-1 to 29.1 m2 ha-1 and N decreased from 1116 to 971 ha-1. The three test stands can be used now for validating remote sensing data-based estimates of forest inventory variables at single tree level.

The important variable of horizontal visibility within forest stands is gaining increasing attention in studies and applications involving terrestrial laser scanning (TLS), photographic measurements of forest structure, and autonomous mobility. We investigated distributions of visibility distance, open arc length, and shaded arc length in three mature forest stands. Our analysis was based (1) on tree position maps and TLS data collected in 2013 and 2019 with three different scanners, and (2) on simulated digital twins of the forest stands, constructed with two pattern-generation models incorporating commonly used indices of tree position clumping. The model simulations were found to yield values for visibility almost identical to those calculated from the corresponding tree location maps. The TLS measurements, however, were found to diverge notably from the simulations. Overall, the probability of free line of sight was found to decrease exponentially with distance to target, and the probabilities of open arc length and shaded arc length were found to decrease and increase, respectively, with distance from the observer. The TLS measurements, which are sensitive to forest understory vegetation, were found to indicate increased visibility after vegetation removal. Our chosen visibility prediction models support practical forest management, being based on common forest inventory parameters and on widely used forest structure indices.

This paper focuses on issues related to the calculation of a high-precision fitted geoid model on Estonian territory. Model Est-Geoid2003 have been used in Estonia several years in geodesy and other applications. New data from precise levelling, new global models and terrestrial gravity data give plenty of possibilities for updates and accuracy evaluation. The model is based on a gravimetric geoid. From the gravimetric data gathered, a gravimetric geoid for Estonia was calculated as an approximately 3-km net using the FFT method. After including the new gravimetric data gathered, the gravimetric geoid no longer had any significant tilt relative to the height anomalies derived from GPS-levelling points. The standard deviation between the points was 2.7 cm. The surface of the calculated gravimetric geoid was fitted by high-precision GPS-levelling points. As a result, a height transformation model was determined to reflect the differences between the normal heights of BK77 and the ellipsoidal heights of EUREF-EST97 on Estonian territory. The model was originally called Est-Geoid2003 and is part of the official national geodetic system in Estonia. The model is updated and evaluated here using precise GPS-levelling points obtained from different measurement campaigns. In 2008–2010 the preliminary results from the latest precise levelling sessions became available, leading to a significant increase in the number of precise GPS-levelling points. Both networks are part of the Estonian integrated geodetic network. Using very precise levelling connections from new levelling lines, normal heights of several RGP points were calculated additionally. Misclosure of 300 km polygons are less than 2–3 mm normally. Ealier all precisely levelled RGP points were included into fitting points. Now many new points are available for fitting and independent evaluation. However, the use of several benchmarks for the same RGP point sometimes results in a 1–2 cm difference in normal height. This reveals problems with the stability of older wall benchmarks, which are widely used in Estonia. Even we recognized, that 0.5 cm fitted geoid model is not achievable using wall benchmarks. New evaluation of the model Est-Geoid2003 is introduced in the light of preliminary data from new precise levelling. Model accuracy is recognised about 1.2 cm as rms. Santrauka Akcentuojami klausimai, susiję su tiksliausio Estijos geoido modelio skaičiavimu. Šis modelis Estijoje geodezijoje ir kitose mokslo bei technikos šakose taikomas nuo 2003 metų. Nauji precizinės niveliacijos duomenys, nauji globalieji geopotencialo modeliai ir žemyno gravimetriniai duomenys – prielaidos geoido modeliui atnaujinti ir jo tikslumui įvertinti. Modelio pagrindas – gravimetrinis geoidas. Pagal surinktus gravimetrinius duomenis Estijos geoidas buvo apskaičiuotas greitųjų Furjė tranformacijų (FFT) metodu, sukuriant apie 3 km akių tinklą. Įtraukus naujuosius gravimetrinius duomenis, gravimetrinis geoidas daugiau nebeturi aukščių anomalijų. Vidutinė kvadratinė paklaida – 2,7 cm. Apskaičiuoto gravimetrinio geoido paviršius susietas su aukščių sistema pagal GPS niveliacijos taškus. 2008–2010 m. gavus precizinės niveliacijos duomenis, žymiai padidėjo GPS niveliacijos taškų skaičius bei jų tikslumas, nes precizinės niveliacijos poligonų iki 300 km nesąryšiai gauti mažesni nei 2–3 mm. Įvertinus naujo Estijos geoido modelio tikslumą nustatyta 1,2 cm vidutinė kvadratinė paklaida. Резюме Акцентируются вопросы, касающиеся вычисления точной модели геоида Эстонии. Эта модель применяется в Эстонии с 2003 г. в геодезии и других отраслях науки и техники. Новые данные высокоточной нивеляции, новые глобальные модели геопотенциала, а также гравиметрические данные создают предпосылки для обновления модели геоида и оценки его точности. Модель основана на гравиметрическом геоиде. Модель геоида Эстонии была вычислена быстрым методом Фурье с использованием всех гравиметрических данных и созданием сети 3×3 км. После использования новых гравиметрических данных в геоиде не оказалось значительного превышения высот по сравнению с точками, измеренными методом GPS. Среднеквадратическая погрешность составила 2,7 см. Вычисленная модель геоида была соединена с системой высот по точкам GPSнивелирования. Благодаря новым данным по высокоточной нивеляции, полученным в 2008–2010 гг., значительно увеличилось количество точек GPSнивелирования и тем самым увеличилась точность геоида, так как невязки полигонов нивелирования составляют всего 2–3 мм. Оценив точность нового геоида Эстонии, выявлено среднеквадратическое отклонение в 1,2 см.