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An Investigation of The Forests of Pernik Province (Western Bulgaria) by The Use of The Perpendicular Vegetation Index (PVI)

Grigorov Borislav

Civil and Environmental Engineering Reports

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2022

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Vol. 32, no. 4

96--104

EN

The current research represents a pilot study for application of the Perpendicular Vegetation Index (PVI) for an area with forests in Bulgaria. It is the first of its kind when it comes to forest studying in the country to the best knowledge of the author. When it comes to soil background Landsat images and other spectral data may be used for monitoring forest territories as well. The study area is Pernik Province which is located in the western parts of Bulgaria. The main aim is to investigate the PVI for the forests of Pernik Province. The index has been calculated by the application of Landsat 8 bands. The PVI has been processed for several months of different years. The main focus is both on the beginning and the end of the growing season when there are significant changes in leaf biomass. The results are promising and show typical vegetation features in the beginning of the growing season (April), a well-developed vegetation (July) and a steadily decreasing biomass in November.

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Geospatial solutions for evaluating the impact of the Tigray conflict on farming

Demissie Biadgilgn, Nyssen Jan, Annys Sofe, Negash Emnet, Gebrehiwet Tesfakiros, Abay Fetien, Wolf Eleonore

Acta Geophysica

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2022

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Vol. 70, no 3

1285--1299

EN

Military conflicts strongly affect agricultural activities. This has strong implications for people’s livelihoods when agriculture is the backbone of the economy. We assessed the effect of the Tigray conflict on farming activities using freely available remote sensing data. For detecting greenness, a normalized difference vegetation Index (NDVI) was analyzed in Google Earth Engine (GEE) using Sentinel 2 satellite images acquired in the pre-war (2020) and during war (2021) spring seasons. CHIRPS data were analyzed in GEE to understand the rainfall conditions. The NDVI of 2020 showed that farmlands were poorly covered with vegetation. However, in 2021, vegetation cover existed in the same season. The NDVI changes stretched from −0.72 to 0.83. The changes in greenness were categorized as increase (2167 km2 ), some increase (18,386 km2 ), no change (1.6 km2 ), some decrease (8269 km2 ), and decrease (362 km2 ). Overall, 72% of the farmlands have seen increases in green vegetation before crops started to grow in 2021. Scattered patches with decreases in vegetation cover correspond to irrigation farms and spring-cropping rain-fed farms uncultivated in 2021. There was no clear pattern of changes in vegetation cover as a function of agro-climatic conditions. The precipitation analysis shows less rainfall in 2021 as compared to 2020, indicating that precipitation has not been an important factor. The conflict is most responsible for fallowing farmlands covered with weeds in the spring season of 2021. The use of freely accessible remote sensing data helps recognizing absence of ploughing in crisis times.

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Application of NOAA AVHRR satellite images for studying various environmental and climatic conditions in Polish forests

Bochenek Z., Ziółkowski D., Bartold M.

Geoinformation Issues

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2015

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Vol. 7, no. 1(7)

29--37

EN

The main objective of the presented work is to make an evaluation of the applicability of low-resolution satellite data for studying the condition of Polish forests being under impact of various climatic and environmental factors. NOAA AVHRR images were used in the work; vegetation indices derived from these images were combined with meteorological parameters obtained from weather stations. Six forest study areas representing different climatic and environmental conditions were used in the research work. The results of the study revealed that there are statistical relationships between remote sensing based indices derived for forest areas from low-resolution satellite data and temperature information characterizing climatic conditions, especially in the first part of the growing season. These findings were confirmed both in the spatial context – in various climatic zones – and in the temporal context.

PL

Głównym celem prezentowanej pracy jest ocena możliwości wykorzystania niskorozdzielczych obrazów satelitarnych do badania kondycji drzewostanów w polskich lasach, będących pod wpływem różnych czynników klimatycznych i środowiskowych. W pracy zostały wykorzystane obrazy satelitarne NOAA AVHRR; wskaźniki roślinności określone na podstawie tych obrazów zostały porównane z parametrami meteorologicznymi otrzymanymi z naziemnych stacji pogodowych. Badania przeprowadzono dla 6 obszarów leśnych reprezentujących różne warunki klimatyczne i środowiskowe. Wyniki prac wykazały, iż istnieją statystyczne zależności pomiędzy wskaźnikami roślinności określanymi na podstawie niskorozdzielczych obrazów satelitarnych a temperaturą powietrza charakteryzującą warunki klimatyczne, zwłaszcza w pierwszej części okresu wegetacyjnego. Wnioski te zostały potwierdzone w aspekcie przestrzennym – w różnych strefach klimatycznych oraz w aspekcie czasowym.

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Comparison of several vegetation indices calculated on the basis of a seasonal SPOT XS time series, and their suitability for land cover and agricultural crop identification

Mróz M., Sobieraj A.

Technical Sciences / University of Warmia and Mazury in Olsztyn

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2004

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nr 7

39-66

EN

The fact that many vegetation indices have been proposed over last decades made specialists search for the most suitable vegetation index for a given remote sensing application. In this paper several vegetation indices have been compared and analyzed based on multispectral SPOT images taken for the same season (2003) and agricultural test area (Żuławy Wiślane). The suitability of vegetation indices was examined in terms of their further use for land cover/crop identification. The results show that there are no significant differences between simple and advanced indices, either for different land cover types or crops.

PL

Znaczna liczba zaproponowanych dotychczas w literaturze wskaźników roślinności skłania do poszukiwania najlepszego, najbardziej odpowiedniego wskaźnika do danego zastosowania teledetekcji. Porównano i zanalizowano wybrane wskaźniki obliczone na podstawie obrazów satelitarnych SPOT XS z jednego sezonu wegetacyjnego (2003) dla obszaru Żuław Wiślanych. Użyteczność wskaźników zbadano z punktu widzenia ich przydatności w identyfikacji upraw rolniczych i form pokrycia terenu. Wyniki wskazują, że nie ma znaczących różnic między prostymi i zaawansowanymi wskaźnikami roślinności, ani dla różnych typów pokrycia terenu, ani odmiennych upraw rolniczych.