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1

The Use of Remote Sensing Techniques in the Analysis of the Influence of Forest Ecosystems over the Precipitation

Herbei Mihai Valentin, Badaluta-Minda Codruta

Rocznik Ochrona Środowiska

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2024

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Tom 26

296--304

EN

The processing of remote sensing images and their integration into a Geographic Information System (GIS) to analyse and manage an area represents a modern approach that is increasingly used. In the present paper, a predominantly mountainous area was studied and analysed, located in Hunedoara County – Romania, near the city of Hateg and the Retezat Mountains. A satellite scene from 09.24.2019 from the RapidEye remote sensing system was retrieved, processed and subjected to complex remote sensing analyses. These remote sensing data were analysed and processed, and based on them a series of specific indices were calculated and interpreted, namely, for the characterisation of the vegetation: NDVI (Normalised Difference Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), NDRE (Normalised Difference Red Edge Index), SAVI (Soil Adjusted Vegetation Index), MSAVI (Modified Soil Adjusted Vegetation Index), CI Green (Chlorophyll Index Green), CI Red Edge (Red Edge Chlorophyll Index), RTVI core (Red Edge Triangular Vegetation Index), SR (Simple Ratio), Red Edge SR (Red Edge Simple Ratio), LAI (Leaf Area Index).

2

Application of UAV and ground measurements for urban vegetation cooling benefits assessment, Wilanów Palace case study

Trzeciak Michał, Sikorska Daria

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2024

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Vol. 33, No. 1

53--68

EN

This research at the Wilanów Palace, Warsaw, assesses urban greenery’s cooling impacts in a cultural heritage site using remote sensing and on-site measurements, highlighting vegetation’s importance in urban climate control. The study combines soil temperature data, UAV thermal imagery, leaf area index (LAI), LiDAR, and NDVI analyses. Findings demonstrate a strong link between vegetation density and temperature: UAV land surface temperature (LST) ranged from 26.8° to 47.5°C, peaking at 72°C, while ground-based temperatures were between 19.5° and 29.2°C, lowest in dense vegetation areas. The statistical analysis confirmed significant temperature differences across vegetation types, with higher LAI areas showing lower temperatures. These results validate the cooling effect of dense vegetation, emphasizing green spaces’ significance in urban climate regulation within cultural heritage sites. The study informs sustainable urban design and conservation, underlining the critical role of vegetation in improving urban microclimates.

3

Wielosensorowy lotniczy system teledetekcyjny MultiSen-1PL na potrzeby precyzyjnego rolnictwa i leśnictwa

Sieczkiewicz Marta, Jedynak Łukasz, Wyczałek Ireneusz, Strzeliński Paweł, Wyczałek-Jagiełło Michał

Przegląd Geodezyjny

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2024

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R. 96, nr 2

25--30

PL

W celu zlokalizowania dokładnych i aktualnych danych dotyczących wzrostu i kondycji roślin na potrzeby precyzyjnego rolnictwa lub leśnictwa niezbędne jest prowadzenie okresowych badań terenowych. Na ich podstawie podejmowane są decyzje co do zakresu i intensywności działań wzmacniających i/lub ochronnych. Aby ułatwić i zautomatyzować proces pozyskiwania danych, rozwijane są zobrazowania satelitarne wykraczające poza zasięg światła widzialnego, zwłaszcza w kierunku podczerwieni (NIR) lub mikrofal (SWIR), a ostatnio także w paśmie czerwieni krawędziowej (RE). Ze względu na rozdzielczość przestrzenną 10-20 metrów dane satelitarne nie są wystarczająco przydatne dla ograniczonych przestrzennie pól lub drzewostanów. Podjęto zatem wysiłki, aby wykorzystać doświadczenia satelitarne dla danych pozyskiwanych z pułapu lotniczego. W pracy przedstawiono zaprojektowany, zbudowany i przetestowany system rejestracji składający się z zestawu kamer oraz skanera laserowego o parametrach filtrowania fal dostosowanych do wymagań indeksów roślinności, wykorzystywanych do analizy danych obrazowych na potrzeby rolnictwa i leśnictwa. Wyniki wdrożenia systemu pokazują, że klasyfikacja oparta na uzyskanych w ten sposób danych teledetekcyjnych zapewnia prowadzenie analiz poprzez inwentaryzację i parametryzację roślinności. W celu analizy zdrowotności drzewostanów wyznaczono wskaźniki NDVI i LAI oraz stopień defoliacji. Dla obszarów rolniczych wdrożono procedurę oceny i weryfikacji stanu upraw poprzez analizę wskaźników NDVI, NDRE, GNDVI oraz wysokości plonów, w celu określenia przestrzennej zmienności kondycji roślin, a także jakości i predykcji plonów. Uzyskane wstępne wyniki potwierdziły spełnienie oczekiwań wobec wielosensorowego systemu pozyskiwania danych teledetekcyjnych, któremu nadano nazwę MultiSen-PL.

EN

In order to locate accurate and up-to-date data on plant growth and health for precision agriculture or forestry, it is necessary to conduct periodic field surveys. On their basis, decisions are made regarding the scope and intensity of strengthening and/or protective actions. To facilitate and automate the data acquisition process, satellite imagery is being developed that goes beyond the range of visible light, especially in the infrared (NIR) or microwave (SWIR) direction, and recently also in the red edge (RE) band. Due to the resolution of 10-20 meters, satellite data is not useful enough for spatially limited fields or forest stands. Therefore, efforts were made to take advantage of satellite experiences for data obtained from the plane level. The work presents the designed, built and tested registration system consisting of a set of cameras and a laser scanner with wave filtering parameters adapted to the requirements of vegetation indices, used to analyze image data for agriculture and forestry. The results of the system implementation show that the classification based on the remote sensing data obtained in this way ensures analysis through the inventory and parameterization of vegetation. In order to analyze the health of forest stands, the NDVI, NDRE and LAI indexes as well as the degree of defoliation were determined. For agricultural areas, a procedure for assessing and verifying the condition of crops was implemented by analyzing the NDVI, NDRE, GNDVI and yield indicators in order to determine the spatial variability of plant condition, as well as the quality and prediction of yields. The obtained preliminary results confirmed that the expectations for the multi-sensor remote sensing data acquisition system, named MultiSen-1PL, were met.

4

The Impact of Pre-Crops on the Formation of Water Balance in Winter Wheat Agrocenosis and Soil Moisture in the Steppe Zone

Pichura Vitalii, Potravka Larysa, Domaratskiy Yevhenii, Nikonchuk Nataliia, Samoilenko Mykola

Journal of Ecological Engineering

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2024

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Vol. 25, nr 3

253--271

EN

Under climate change, the issue of selection and correction of crop cultivation systems in the zone of moisture deficit and risky farming to ensure profitability of production is still topical. In particular, crop rotations are a practice aimed at increasing resistance of soil systems to abiotic and biotic stresses in the zone of moisture deficit. Therefore, the purpose of the research is to identify spatio-temporal regularities of vegetative formation of water balance in winter wheat agrocenoses depending on a pre-crop according to the unified BBCH scale. Spatio-temporal processes of vegetation and water balance formation in winter wheat agrocenosis depending on a pre-crop according to the unified BBCH scale were examined on the basis of the data of decoded satellite image series of the spacecraft Sentinel and calculation of the NDWI and the NDVI values. The research was conducted in the natural-climatic conditions of the Steppe zone of Ukraine, in the territory of Yelanets district, Mykolaiv region, during the vegetative phase of winter wheat variety Driada 1: autumn 2021 and winter, spring and the beginning of summer 2022. It was established that activeness of water balance formation in winter wheat agrocenosis with pea as a pre-crop according to seasonal-phenological stages of plant growth is 3.0–9.0 times higher than with a grain crop (spring barley) and sunflower as pre-crops. In particular, with pea as a pre-crop, the NDVI vegetation of winter wheat plants is 1.6–1.7 times more intensive, the rate of moisture supply NDWI in the plant leaf at the macro-stages BBCH 10–61 is 1.54 and 1.82 times higher, productivity is 1.43–1.56 times higher. We observed a 30.5–34.3% reduction in water consumption for the formation of a ton of winter wheat grain with pea as a pre-crop in comparison with other pre-crops that resulted in an increase in productive moisture reserves at the end of vegetation in a meter soil layer by 20%. It was established that using pea as a pre-crop has economic and environmental benefits that manifest themselves in increasing resistance of soil systems, a reduction in environmental pollution and a rise in profitability of production.

5

Enhancing Semi-Arid Ecosystem Resilience in Jordan Using Controlled Grazing–A Short and Long-Term Assessment

Sawalhah Mohammad N., Alshdaifat Mustafa F., Al-Kofahi Salman D., Almasaeid Oday M.

Journal of Ecological Engineering

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2024

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Vol. 25, nr 5

29--42

EN

Grazing management strategies in arid ecosystems are of critical importance to regulate plant regeneration, improve forage quality, and ensure sustainable utilization of rangelands. This study examined the impacts of controlled grazing management on vegetation dynamics (gain/loss) and land cover changes over a 17-year period (2006–2022) at the Royal Botanic Garden, Jordan. Climatic factors, including precipitation and temperature, were analyzed alongside the Normalized Difference Vegetation Index (NDVI) to assess vegetation health and greenness. Autoregression models were used to investigate annual temporal trends between vegetation biodiversity indices and climatic factors. To assess the impact of controlled grazing on vegetation biodiversity, the study period was divided into four periods: the initial period (period 0: 2006–2007) which represented the pre-dating-controlled grazing period, followed by three subsequent periods: period 1 (2008–2012), period 2 (2013–2017), and period 3 (2018–2022). Land cover analysis using yearly averaged NDVI values was assessed, including five distinct classes: water body, barren soil, herbaceous and shrub, open forest, and closed forest. The study identified short-term changes during period 1 and long-term changes during periods 2 and 3. The results revealed a significant annual temporal trend only in NDVI (P<0.001), indicating dynamic changes in vegetation health over the whole study period. A positive influence of controlled grazing on vegetation dynamics and biomass production was observed. During period 3, controlled grazing has led to a significant (P<0.05) increase in vegetation biomass compared to earlier periods (214.4 ton in period 3 compared to 97.1 and 106.8 ton in periods 1 and 2, respectively). NDVI also showed significantly higher values during the later periods of controlled grazing, emphasizing its positive impact on long-term vegetation health. Furthermore, the study showed interesting trends in plant groups and species, with short-term controlled grazing leading to increased species richness and significant changes in vegetation indices. Over the study period, controlled grazing influenced land cover dynamics, with significant decreases in barren soil (from 66.7% to 9.8%) and increases in herbaceous and shrubland areas (33.2% to 89.6%). The study concluded that controlled grazing significantly shapes plant communities, fostering dynamic changes in species and groups over time. The study provides valuable insights into the ecological impact of controlled grazing management. The obtained f indings revealed vegetation resilience to short-term climate variations, with sustained vegetation health under grazing. Grazing management strategies in arid ecosystems are of critical importance to regulate plant regeneration, improve forage quality, and ensure sustainable utilization of rangelands. This study examined the impacts of controlled grazing management on vegetation dynamics (gain/loss) and land cover changes over a 17-year period (2006–2022) at the Royal Botanic Garden, Jordan. Climatic factors, including precipitation and temperature, were analyzed alongside the Normalized Difference Vegetation Index (NDVI) to assess vegetation health and greenness. Autoregression models were used to investigate annual temporal trends between vegetation biodiversity indices and climatic factors. To assess the impact of controlled grazing on vegetation biodiversity, the study period was divided into four periods: the initial period (period 0: 2006–2007) which represented the pre-dating-controlled grazing period, followed by three subsequent periods: period 1 (2008–2012), period 2 (2013–2017), and period 3 (2018–2022). Land cover analysis using yearly averaged NDVI values was assessed, including five distinct classes: water body, barren soil, herbaceous and shrub, open forest, and closed forest. The study identified short-term changes during period 1 and long-term changes during periods 2 and 3. The results revealed a significant annual temporal trend only in NDVI (P<0.001), indicating dynamic changes in vegetation health over the whole study period. A positive influence of controlled grazing on vegetation dynamics and biomass production was observed. During period 3, controlled grazing has led to a significant (P<0.05) increase in vegetation biomass compared to earlier periods (214.4 ton in period 3 compared to 97.1 and 106.8 ton in periods 1 and 2, respectively). NDVI also showed significantly higher values during the later periods of controlled grazing, emphasizing its positive impact on long-term vegetation health. Furthermore, the study showed interesting trends in plant groups and species, with short-term controlled grazing leading to increased species richness and significant changes in vegetation indices. Over the study period, controlled grazing influenced land cover dynamics, with significant decreases in barren soil (from 66.7% to 9.8%) and increases in herbaceous and shrubland areas (33.2% to 89.6%). The study concluded that controlled grazing significantly shapes plant communities, fostering dynamic changes in species and groups over time. The study provides valuable insights into the ecological impact of controlled grazing management. The obtained f indings revealed vegetation resilience to short-term climate variations, with sustained vegetation health under grazing.

6

Spatiotemporal Mapping of Agricultural and Meteorological Drought in Wasit Province Based on GIS and Remote Sensing Data

Said Lubna W., Aziz Nadia A., Hussein Luay Y.

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 6

115--122

EN

One of the most common natural hazards that can endanger life and property is drought, which can happen under a variety of weather and environmental circumstances. This study aims to monitor the agricultural and metrological drought in the Wasit Province using remote sensing data. Landsat 8 images were used to create the agriculture drought maps based on the NDVI for the years 2013, and 2023. Additionally, SPI-12 was used for the same years to evaluate the meteorological drought. The findings demonstrated that while SPI readings in 2023 were lower, the SPI-12 in 2013 indicated near-normal drought types. Two types of drought have been identified: moderate and slight. The result shows that, for the year 2013 the percentage of moderate drought is 31%, slight drought 64%, and no drought 3.9% from the total area. While, in 2023 the percentage of moderate drought is 47%, slight drought 49%, and no drought 3.2% from the total area. It is noticed that in 2023, the moderate drought class increased by about 16%. Government planners may find this results valuable when developing and managing drought consequences.

7

Mapping Environmental Impacts in North-Western Algeria through Multivariate Spatio-Temporal Analysis Using Remote Sensing and Geographic Information System

Mahcer Ikram, Baahmed Djelloul, Chemirik Cherifa Hanene Kamelia, Nedjai Rachid

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 5

42--60

EN

The interactions between the normalised difference vegetation index (NDVI), the normalised difference built-up index (NDBI), and land surface temperature (LST) are complex. The assessment of land use/land cover (LULC) changes in the North-western region of Algeria between 1995 and 2021 confirms the direct influence of these factors on surface thermal processes. The use of new information technologies, particularly remote sensing coupled with GIS, favourably contributes to the processing of a large volume of data and to the use of specific methods aimed at confirming and/or disproving the hypotheses put forward. The application of LULC classification methods clearly highlights the magnitude of transformations, predominantly in favour of intensified urbanisation over the past two decades. Indeed, agricultural lands have experienced a reduction of 17.45%, while urbanised areas have nearly doubled. This phenomenon can, in part, be attributed to the mass migration of populations from inland areas to the coast, not only due to climate change: secondary for political problems between 1990 and 2001. Similarly, barren lands have increased by 10.45%. These changes have real implications for ecosystems (mainly loss of biodiversity) and the climate (pollution, GHG emissions, and rising ambient temperatures). The estimation of average LST from multiple satellite scenes reveals an increasing trend, rising from 36.6 °C in 1995 to 40.35 °C in 2021. The direct relationship between LST and NDVI and between LST and NDBI confirms the close association between land use change and increasing surface temperatures. The Pearson coefficient between LST and NDVI showed a negative correlation, ranging between -0.52 and -0.47, while it was positively correlated between LST and NDBI, with values around 0.66. The emergence of hotspots in the region, confirmed by the results of analysis employing the Getis-Ord G* method, is marked by clearly increasing spatial envelopes. This phenomenon is associated with a distinct reduction in vegetation cover density, coupled with an increased vulnerability to drought conditions. These initial results argue in favour of preserving green and blue networks and, more largely, ecosystems.

8

Assessment of the Impact of Covid-19 Related Containment on the Normalized Vegetation Index – A Remote Sensing Study of the Korifla Sub Watershed, Morocco

Eddefli Fatimazahra, Tayebi Mohamed, Salih Sara

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 6

1--9

EN

This study analyzes the impact of containment due to the COVID-19 pandemic on the vegetation cover of the Korifla sub-watershed, based on remote sensing data and spatial analysis. The aim of this study was to analyze the impact of the containment imposed in response to the COVID-19 pandemic on the vegetation cover and to highlight significant changes in the distribution of normalized difference vegetation index (NDVI) before and after the containment period, as well as to identify the areas most affected by these changes. The results highlight significant fluctuations in the distribution of vegetation cover, including a decrease in water area and variations in the categories of bare soil, sparse, medium-dense and dense vegetation. Using NDVI as an indicator of vegetation health, changes before and after the confinement period were highlighted. These results highlight the impact of anthropogenic disturbances such as confinement on plant ecosystems, and underline the importance of continuously monitoring vegetation cover for sustainable natural resource management and biodiversity preservation. With climatic conditions in Morocco stagnating in the two years following containment, the climatic factor is now set aside, and the focus shifts to the impact of reduced human activity.

9

Examining and predicting the influence of climatic and terrestrial factors on the seasonal distribution of ozone column depth over Tehran province using satellite observations

Borhani Faezeh, Ehsani Amir Houshang, McGuirk Savannah L., Shafiepour Motlagh Majid, Mousavi Seyed Mohsen, Rashidi Yousef, Mirmazloumi Seyed Mohammad

Acta Geophysica

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2024

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Vol. 72, no. 2

1191--1226

EN

When combined with conducive atmospheric conditions, air pollution caused by fossil fuel consumption associated with transportation, industry and electricity production for households, create and sustain continuous pollution over the megalopolis of Tehran, Iran. In conjunction with daily meteorological forecasts, remote sensing can be used to identify and predict days with hazardous levels of air pollution, providing an opportunity for air quality alert systems to be triggered and warnings circulated to reduce health risks to citizens of Tehran province. Combining remotely sensed ozone column density (OCD) data from the Sentinel-5 TROPOMI sensor with NASA Giovanni data concerning meteorological parameters (temperature (T), wind speed (WS) and specific humidity (SH)), geographical parameters and population data, this study considers the drivers and effects of ozone pollution on the urban climate and vegetation condition (normalized difference vegetation index (NDVI)) of 16 counties in Tehran province, Iran during 12 months (i.e., January 2021 to December 2021). Future monthly forecasts of the OCD, climatic and terrestrial factors in 2022 are also presented. Google Earth Engine and the NASA Giovanni platforms were employed for the processing and analysis of data using an interpolation technique. Additionally, a Box-Jenkins ARIMA and Exponential Smoothing (ETS) models were compared and tailored to generate monthly forecasts of OCD, T, WS, SH and NDVI. The highest and lowest OCD was obtained in June and December 2021, with a concentration of 0.14277 mol/m2 and 0.12383 mol/ m2, respectively. However, the annual average OCD was higher in the cities of Shahriar and Pakdasht in March, with values of 0.13237 mol/m2 and 0.13244 mol/m2, respectively. The lowest OCD recorded was 0.13105 mol/m2, in Shemiranat city, in the north of Tehran. The results indicate a positive correlation between OCD and NDVI, and a negative correlation between OCD, SH, WS and T. A strong seasonal trend in OCD was identified for all cities, but across the entire province, altitude and population size were the most significant explanatory variables for spatial variations in OCD. This research demonstrates that an effective OCD monitoring and forecasting model may be generated from remote sensing and meteorological variables. The implementation and utilization of these models are of paramount importance as they offer vital information to authorities for continuous air quality monitoring and strategic planning, particularly for days with hazardous air pollution. By effectively implementing the OCD model, it has the potential to directly contribute to improved health outcomes in major cities across Iran.

10

Pomiary zapotrzebowania nawozowego kukurydzy za pomocą aktywnego czujnika azotu

Kubiak-Siwińska Katarzyna, Kotlarz Jan

Pomiary Automatyka Robotyka

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2023

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R. 27, nr 3

13--18

PL

Azot jest ważnym makroskładnikiem biomasy, ponieważ odgrywa istotną rolę w procesach metabolicznych, produkcji białek, syntezie aminokwasów, enzymów, hormonów oraz jest składnikiem chlorofilu. Ocena jego niedoborów w uprawach kukurydzy jest przedmiotem badań naukowych. W artykule zaprezentowano wyniki pomiarów w kontrolowanych warunkach laboratoryjnych wskaźników teledetekcyjnych kukurydzy uprawianej w wariantach nawożenia 0-150 kg·N/ha. Zaproponowana metoda oceny niedoboru azotu z wykorzystaniem sensora Crop Circle pozwala na autonomiczne sterowanie precyzyjnym nawożeniem doglebowym w projektowanym rozwiązaniu robota polowego.

EN

Nitrogen is an important macronutrient of biomass because it plays an important role in metabolic processes, protein production, amino acid synthesis, enzymes, hormones and is a component of chlorophyll. The assessment of its deficiencies in maize crops is the subject of scientific research. The article presents the results of measurements in controlled laboratory conditions of remote sensing indices of maize cultivated in fertilization variants of 0-150 kg·N/ha. The proposed method of assessing nitrogen deficiency using the Crop Circle sensor allows for autonomous control of precise soil fertilization in the designed solution of a field robot.

11

Seasonality and long-term trends of NDVI values in different land use types in the eastern part of the Baltic Sea basin

Klimavičius Laurynas, Rimkus Egidijus, Stonevičius Edvinas, Mačiulytė Viktorija

Oceanologia

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2023

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No. 65 (1)

171--181

EN

This study analyses changes in Normalized Difference Vegetation Index (NDVI) values in the eastern Baltic region. The main aim of the work is to evaluate changes in growing season indicators (onset, end time, time of maximum greenness and duration) and their relationship with meteorological conditions (air temperature and precipitation) in 1982–2015. NDVI seasonality and long-term trends were analysed for different types of land use: arable land, pastures, wetlands, mixed and coniferous forests. In the southwestern part of the study area, the growing season lasts longest, while in the northeast, the growing season is shorter on average by 10 weeks than in the other parts of the analysed territory. The air temperature in February and March is the most important factor determining the start of the growing season and the air temperature in September and October determines the end date of the growing season. Precipitation has a much smaller effect, especially at the beginning of the growing season. The effect of meteorological conditions on peak greenness is weak and, in most cases, statistically insignificant. At the end of the analysed period (1982–2015), the growing season started earlier and ended later (in both cases the changes were 3–4 weeks) than at the beginning of the study period. All these changes are statistically significant. The duration of the growing season increased by 6–7 weeks.

12

Modelling causality between agricultural and meteorological drought indices in the Corong River basin, East Java Indonesia

Affandy Nur A., Iranata Data, Anwar Nadjadji, Maulana Mahendra A., Prastyo Dedy D., Jaelani Lalu M., Suryadi F. X.

Journal of Water and Land Development

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2023

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no. 58

178--188

EN

The Lamongan Regency is an area in East Java, Indonesia, which often experiences drought, especially in the south. The Corong River basin is located in the southern part of Lamongan, which supplies the irrigation area of the Gondang Reservoir. Drought monitoring in the Corong River basin is very important to ensure the sustainability of the agricultural regions. This study aims to analyse the causal relationship between meteorological and agricultural drought indices represented by standardised precipitation evapotranspiration index (SPEI) and standard normalisation difference vegetation index (NDVI), using time series regression. The correlation between NDVI and SPEI lag 4 has the largest correlation test results between NDVI and SPEI lag, which is 0.41. This suggests that the previous four months of meteorological drought impacted the current agricultural drought. A time series regression model strengthens the results, which show a causal relationship between NDVI and SPEI lag. According to the NDVI-SPEI-1 lag 4 time series model, NDVI was influenced by NDVI in the previous 12 periods, and SPEI-1 in the last four periods had a determinant coefficient value of 0.4. This shows that the causal model between SPEI-1 and NDVI shows a fairly strong relationship for drought management in agricultural areas (irrigated areas) and is considered a reliable and effective tool in determining the severity and duration of drought in the study area.

13

Application of the Research on Spatio-Temporal Differentiation of a Vegetation Index in Evaluating Sunflower Hybrid Plasticity and Growth-Regulators in the Steppe Zone of Ukraine

Pichura Vitalii, Domaratskiy Yevhenii, Potravka Larisa, Biloshkurenko Oleksandra, Dobrovol'skiy Andrey

Journal of Ecological Engineering

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2023

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Vol. 24, nr 6

144--165

EN

The purpose of the study was to establish dependence of sunflower productivity on hybrid plasticity under the climatic conditions of the Steppe zone and effectiveness of growth-regulators on the basis of the analysis of differentiation of a vegetation index. The research on the development and productivity of different sunflower hybrids under the natural-climatic conditions of the Steppe zone of Ukraine was conducted in the years of 2019 (medium-wet), 2020 (dry) and 2021 (wet). Spatio-temporal differentiation of the vegetation of sunflower hybrids was established on the basis of calculation of a normalized difference vegetation index (NDVI) using the data of the decoded space images of Sentinel 2. Cartographic and grapho-analytical materials reflecting the reaction of plants to natural-climatic conditions and multifunctional growth-regulators were obtained. The dependence of the reaction of sunflower hybrids to multifunctional growth-regulators on their plasticity in response to the natural-climatic conditions of the Steppe zone was established. There was a weak reaction to application of growth-regulators of the sunflower hybrids Oplot and P64HE133 which are characterized by a high level of plasticity in response to the natural-climatic conditions of the Steppe zone. It was proven that the application of the biological preparation Helafit Combi exceeded the level of agrocenoses productivity in comparison with the chemical preparation ArchitectТМ by 1.1-5.4%. It was established that foliar treatment with growth-regulators led to a decline in water uptake by the sunflower hybrids by 1.2–10.0% in the dry year, by 3.8–8.6% in the medium-wet year and by 3.7%–21.9% in the wet year. There was a significant reduction in the level of water uptake by the hybrid Hector – by 7.7–10.0% and the hybrid 8KH477KL – by 1.2–21.9%. The research results are the basis for forecasting the development of sunflower hybrid crops with further measurement of the crop productivity that allows establishing a probable level of efficiency of sunflower hybrid production by agricultural producers under the climatic conditions of the Steppe zone.

14

Use of remote sensing as an indicator of the urban heat island effect: the case of the municipality of Guelma (north-east of Algeria)

Khallef Boubaker

Geomatics, Landmanagement and Landscape

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2023

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no. 3

61--72

EN

The main objective of this study is to show which of the LST-NDVI and LST-NDBI relationships can determine the most accurate index that can be used as an indicator of the effects of urban heat islands in the municipality of Guelma, using Landsat data. 8 OLI/TIRS and the geographic information system. The application of the calculation formulas made it possible to extract the Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built up Index (NDBI) of the municipality of Guelma for the four seasons of 2019. This calculation led to the determination of the relationship between all three indicators. The results obtained show a strong correlation between the LST and the NDBI for the four seasons of the year. They suggest that the NDBI is an accurate indicator of the heat island effect in Guelma. This indicator can serve as a tool for future urban planning by those in charge of this department. However, there is currently and urgent need to strengthen strategies for reducing the effects of urban heat islands in order to preserve the quality of urban life of the inhabitants and by setting up emergency programs.

15

A study of vegetation cover dynamics using landsat images: case of the beni haroun watershed (Algeria)

Roukia Namous, Abdelaziz Louamri, Khallef Boubaker

Geomatics, Landmanagement and Landscape

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2023

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no. 4

315--328

EN

Conducting a diachronic study of vegetation cover helps to assess its transformations over a period of time, allowing for a comprehensive assessment of the factors influencing these transformations. The purpose of this research is to analyze the vegetation cover spatio-temporal changes within Beni Haroun watershed, located in the northeast region of Algeria. Based on remote sensing data, two satellite images for the years 2009 and 2020 from Landsat 7 ETM+ and Landsat 8 OLI/TIRS were downloaded. The Normalized Difference Vegetation Index was employed to remotely detect and monitor the changes of the vegetation cover. It was calculated for both chosen dates, and the results were classified into four classes (no vegetation, sparse vegetation, moderate vegetation, dense vegetation), each representing a different vegetation density. The obtained maps showed a regression of the vegetation cover. The NDVI values have decreased from 0.77 in 2009 to 0.58 in 2020. Spatial patterns in the classified NDVI maps illustrated reduced vegetation cover demonstrated by an expansion of the no vegetation class: 35,3479 ha in 2009 and 56,7916 ha in 2020. The final map of the change detection depicted a predominance of the negative change throughout Beni Haroun watershed, in consequence of various controlling factors, including climate and human interventions.

16

Monitoring of Land Surface Temperature from Landsat Imagery: A Case Study of Al-Anbar Governorate in Iraq

Morsy Salem, Ahmed Shaker

Geomatics and Environmental Engineering

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2023

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Vol. 17, no. 3

61--81

EN

Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST estimation and monitoring of the main part of Al-Anbar Governorate in Iraq is presented using Landsat imagery from five years (2005, 2010, 2015, 2016 and 2020). Images of the years 2005 and 2010 were captured by Landsat 5 (TM) and the others were captured by Landsat 8 (OLI/TIRS). The Single Channel Algorithm was applied to retrieve the LST from Landsat 5 and Landsat 8 images. Moreover, the land use/land cover (LULC) maps were developed for the five years using the maximum likelihood classifier. The difference in the LST and normalized difference vegetation index (NDVI) values over this period was observed due to the changes in LULC. Finally, a regression analysis was conducted to model the relationship between the LST and NDVI. The results showed that the highest LST of the study area was recorded in 2016 (min = 21.1°C, max = 53.2°C and mean = 40.8°C). This was attributed to the fact that many people were displaced and had left their agricultural fields. Therefore, thousands of hectares of land which had previously been green land became desertified. This conclusion was supported by comparing the agricultural land areas registered throughout the presented years. The polynomial regression analysis of LST and NDVI revealed a better coefficient of determination (R2) than the linear regression analysis with an average R2 of 0.423.

17

Remote Sensing and Meteorological Indexes of Drought Using Open Short Time-Series Data in Doukkala Region, Morocco

Ait Ayad Nada, Ait Ayad Alaaeddine, El Khalidi Khalid, Habib Adnane, Charif Abdelmounim

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 2

1--10

EN

Over time, drought affects all regions of Morocco, especially in the arid climate region, which has negative consequences on agriculture, economic and environmental. The present study aims to describe the intensity of drought in Morocco and more specifically their impact on the distribution of vegetation. Spatial and temporal remote sensing data are used to monitor drought in the Doukkala region of Morocco, using a set of Landsat images, including Landsat 5 (ETM), and Landsat 7 (ETM+) captured during the period 1964–2014. This was determined based on remote sensing parameters: temperature condition index (TCI), vegetation condition index (VCI) and vegetation health index (VHI). The Normalized Difference Vegetation Index (NDVI) was determined for the years 1966, 1984, 1988, 2000 2006 and 2009, in order to identify the vegetation categories and quantify the vegetation density in the Doukkala region. The NDVI obtained was analyzed using the SPI (Normalized Precipitation Index) based on the rainfall data of the years 1966, 1984, 1988, 2000 2006 and 2009. The results obtained showed that the correlation between NDVI and SPI indicated negative values or less than 1. The calculation of VHI showed low values (VHI < 40%) in one part of the studied area that indicate severe to extreme drought conditions, while in the other part the VHI showed high values (VHI > 40%), which mainly reflect favorable conditions for crop development (no drought). The results of this study can be used for monitoring and evaluation of the drought for sustainable management of the area.

18

Monitoring Land Use and Land Cover Changes Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Ait El Haj Fatiha, Ouadif Latifa, Akhssas Ahmed

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 1

272--286

EN

The study of land use and land cover change (LULC) is essential for the development of strategies, monitoring and control of the ecosystem. The present study aims to describe the dynamics of land cover and land use, and specially the impact of certain climatic parameters on the distribution of vegetation and land cover. For this study, multi-temporal remote sensing data are used to monitor land cover changes in Morocco, using a set of Landsat images, including Landsat 7 (ETM+), Landsat 5 (TM), and Landsat 8 (OLI), captured during the period 2000–2020, those changes were determined by adopting the maximum likelihood (ML) classification method. The classification results show good accuracy values in the range of 90% (2000), 80% (2007), 82% (2010), 93% (2020). The LU/LC change detection showed a decrease of agricultural and forest areas in the order of 5% between the year 2000 and 2020, and an increase of bare soil of 5% to 6%, and a notable change in urban area from 97.31 ha (0.03%) in 2000 to 2988.2637 ha (0.82%) in 2020. The overall results obtained from LULC show that the vegetation cover of the study area has undergone major changes during the study period. In order to monitor the vegetation status, an analysis of the precipitation-vegetation interaction is essential. The normalized difference vegetation index (NDVI) was determined from 2000 to 2020, to identify vegetation categories and quantify the vegetation density in the Lakhdar sub-basin. The obtained NDVI was analyzed using climatic index SPI (Normalized Precipitation Index) based on rainfall data from five stations. The correlation study between NDVI and SPI indices shows a strong linear relation between these two indicators especially while using an annual index SPI12 however, the use of NDVI index based on remote sensing provides a significant result while assessing vegetation. The results of our study can be used for vegetation monitoring and sustainable management of the area, since it is one of the largest basins in the country.

19

Contribution to the Modeling of the Organic Matter of Moroccan Forest Soils within the Context of Global Change – Case Study of the Central Plateau

Dallahi Youssef, Malaainine Mohamed El Imame, Hbiak Ishak, Boujraf Amal, Abidine Mohamed Mahmoud, Orlando Collins Ashianga, Meliho Modeste, El Mderssa Mohamed, Minoubi Abdenaim

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 8

261--271

EN

Organic matter is a major component of soil. It is of considerable ecological importance given its role in determining soil health, influencing ecosystem productivity and climate. For this reason, it is essential to carry out studies to evaluate its dynamics in natural ecosystems. In this study, the authors aimed to explore the dynamics of soil organic matter (SOM) in forest ecosystems of the Central Plateau in Morocco, as well as to investigate the potential of spectral vegetation indices in modeling SOM. To this end, the soil samples for analysis were collected from 30 sites across three vegetation types, including cork oak, Barbary thuja and scrub (matorral). In addition, the normalized difference vegetation index (NDVI) was extracted from Landsat 8 images to be used to model SOM using linear regression. The obtained results showed a weak, although statistically significant (α < 0.05), correlation between NDVI and SOM at 0.45. In addition, only the scrub type showed a statistically significant (α < 0.05) relationship between its corresponding SOM and NDVI, and was therefore retained for modeling. Vegetation type had a statistically strong influence (α <0.01) on SOM, with cork oak and garrigue ecosystems having the highest and lowest SOM contents with 5.61% and 2.36%, respectively. In addition, the highest SOM contents were observed under slightly acidic pH soils on mild, warm slopes at high altitude sites, while the lowest were found in lowland areas with predominantly weakly evolved soil.

20

Fury of nature: evaluating the impact of hailstorm on vegetation using sentinel 2 data at Moran, India

Neog Rituraj

Acta Geophysica

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2023

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Vol. 71, no. 6

3025--3039

EN

The primary objective of the study is to analyze the impact assessment of hailstorms on vegetation in the Moran region of Assam. The experiments employed sentinel-2A data of December, 2022 and January, 2023 for the computation of the NDVI, GNDVI, and MSAVI indices and their temporal dynamics. Further, LandScan gridded (1 k × 1 km) population data of 2021 have been used to portray the population affected in the study area. The result evidenced a significant decline in the mean NDVI (Normalized Difference Vegetation Index), GNDVI (Green Normalized Difference Vegetation Index), and MSAVI (Modified Soil Adjusted Vegetation Index) from the pre-hailstorm to the post-hailstorm period. The above indices declined from 0.270, 0279 and 0.416 in pre-hailstorm (24 December, 2022) period to 0.257, 0.269 and 0.410 in post-hailstorm period (3 January, 2023). Similarly, the area under healthy vegetation decreased from 72.06 and 103.55 sq km in 2022 to 60.74 and 96.35 sq km in 2023, based on GNDVI and MSAVI, respectively. The hailstorm affected the majority of villages as well as the population lying to the east of the NH-37, i.e., the Charaideo district of Assam. The Villages such Bagtali Sonowal, Demorukinar Changmai, Hatkhola gaon and Mout gaon experienced maximum damage to vegetation. Overall, 125.355 and 132.07 sq km of area considering both assessments (MSAVI & GNDVI with population) with a total population of about 131,342 are severely affected by hailstorm phenomena.