Search

In any terrestrial area, but especially in the case of mountainous areas, the spatial distribution of vegetation is conditioned by a series of natural factors such as relief, climatic factors or soils. From another point of view, the distribution of vegetation is different, depending on the phenophases, implicitly on the observation period, during the growing season. In this context, the aim of the work was to analyze the vegetation coverage of the grasslands in the Poiana Rusca Mountains, by applying the Normalized Difference Vegetation Index (NDVI), in five different periods. Five satellite images from the months of March, May, July, August and October were used, on which NDVI was applied, later reclassified according to the obtained values. Quantitatively, the changes produced from one time interval to another were calculated, based on the matrix of transitions, and thus, the changes produced were highlighted. It was found that the highest degree of vegetation coverage of the grasslands was in July, the "peak" of the vegetation season. The application of NDVI for the analysis of vegetation distribution has several advantages: it complements measurements in the field, it is expressed in the form of thematic maps that can be integrated with other geospatial data, it allows the location of "problematic" or risky areas, in terms of vegetation cover.. [ABSTRACT FROM AUTHOR]

The presented paper deals with the targeted application of pre-emergent herbicides. The field experiment was established in 2022 and 2023; two plots sized 26 ha and 30 ha were selected and the accuracy of the application was tested. There were local outbreaks of weeds on selected plots of land, which had to be eliminated before sowing the main crop - soybeans. Both plots were monitored using an unmanned aerial vehicle (UAV) - Mavic 3M with the multispectral camera. After the end of the monitoring, spectral analysis of images taken by UAV was made using the Pix4D software and vegetation indexes were calculated. The weed outbreaks were identified based on multispectral maps using the MagicTooll algorithm. The final application map was prepared in the QGIS program - two zones with and without herbicide application were defined. The application was carried out by the JD 4150i machine (9 sections per 30 m), the regulatory map was transferred to the machine terminal (4600) via the MyJD link. Subsequently, the entire application process was monitored and analysed using the MyJD programme. The accuracy of the application was analysed by comparing the prescription map and the actual dose applied. The accuracy of application was found to be significantly greater than 90%. [ABSTRACT FROM AUTHOR]

The way of land use and implicitly the spatio-temporal distribution of plant species are subject to quantitative and qualitative changes, under the influence of natural and/or anthropogenic factors. Appreciation of the spatio-temporal "mobility" of vegetation can be done through different work protocols, some of which are geomatic methods applied to satellite images. In this context, the purpose of this study is to analyze the trends in the dynamics of vegetation and land use, over a period of approximately 35 years, based on Landsat images and the Normalized Difference Vegetation Index (NDVI), at the level of the southwest area of Romania. The obtained results provide an overview of the land use/land cover at the level of the entire study area, but also highlight the aspects related to the vegetation cover. The research results draw attention to the transformations that have occurred in the vegetation cover of the area of interest, through the reduction or loss of the areas of some plant species or their territorial "inversion", which can produce effects on the biodiversity of the study area. On the other hand, such studies can be considered a starting point in local or regional management strategies. [ABSTRACT FROM AUTHOR]

Using remote sensing functional aspects of the landscape such as energy exchange between vegetation and the atmosphere, surface reflectance or vegetation heat flux can be monitored and evaluated in detail. Multispectral imagery is used to obtain information on the condition of the vegetation and plant growth, as it allows us to obtain information on possible nutrient deficiencies, pest damage or other manifestations of abiotic stress on the plants. Each surface reflects and emits radiation at different wavelengths, making it possible to create spectral curves for each surface. The waveforms of spectral curves differ based on vegetation type or physiological state, they exhibit similar basic features. Vegetation indices are used to process the measured data. In our research we focused on the changes in the values of selected vegetation indices depending on soil moisture. Spectrometer measurements were only made in 2021 on walnut in the irrigated and non-irrigated variants. The Normalized Difference Vegetation Index (NDVI) index is influenced by the chlorophyll content of the leaves. The NDVI value increased after application of irrigation dose. In the non-irrigated variant, the values decreased with decreasing rainfall and at the beginning of August. Measurements of vegetation indices show better canopy physiology in irrigated trees that responded to changes in soil moisture. Leaf physiological condition in the nonirrigated variant was more variable. As a result of the rainfall between 12 July and 27 July, when a total of 18.7 mm of rainfall fell, the condition of the non-irrigated trees began to improve. [ABSTRACT FROM AUTHOR]

The link between precipitation, drought indices, and NDVI is discussed in this paper. The data were processed on the example of the extreme eastern region of Georgia-Kakheti for the period 2016-2020. The study area has landscapes of natural (mixed and deciduous forests) and agriculture (vineyards, orchards, cereals, and vegetables). The NDVI was generated using Sentinel 2 images with a 10 m pixel resolution, and the average monthly NDVI was derived using Arc map 10.8. Drought indices (SPI and SPEI) were calculated according to the daily climate data from five rain gauges located in the study area in program R. Several trends emerged from the results. The correlation between NDVI, precipitation and drought indices vary according to natural and agricultural landscapes. A relatively low correlation was observed between the average monthly NDVI, precipitation and drought indices in the case of forests in Lagodekhi. These areas are relatively humid locations in Kakheti. In the southeast of the region, where arid forests are represented, NDVI was found to be more sensitive to precipitation and, consequently, drought indices. However, in contrast to the previously described locations, SPI and SPEI differed significantly from each other. In the case of agriculture landscapes, this connection is more complex and depends on the crop type and the vegetation period. [ABSTRACT FROM AUTHOR]

As a consequence of climate change, in some regions, more intense rain showers go hand in hand with longer dry periods. The subsequent more and more severe droughts can have devastating effects on many economic and social sectors. Therefore, it is necessary to be able to predict and assess the consequences of these droughts on a local scale, in order to develop policies to cope. Drought assessment needs a lot of detailed and accurate input-data, such as land use, land cover, soil moisture, vegetation, evapotranspiration, etc., often obtained by continuous earth monitoring by satellites. Satellite images are generally converted into indices, of which the Normalized Difference Vegetation Index (NDVI) is one of the most widely used. It was developed for use with Landsat imagery and allows for the classification of satellite images for land use and the assessment of the vegetation's vitality. In this research, a new composite index is presented and compared to the NDVI to be used with Sentinel-2A imagery, having higher resolution and more spectral bands than Landsat. This new composite index can be used to detect water and vegetation. Test results show that this newly developed composite index achieves a better accuracy through Support Vector Machine (SVM) classification than the widely used NDVI. Although further validation is necessary, the results promise a possible amelioration of vegetation related input data for drought assessment and management. [ABSTRACT FROM AUTHOR]

In this paper was used correlations between LST-NDVI, for warmest day, for 2013-2016. Study area, Iasi, is geographically situated on latitude 47 degrees 12 min N to 47 degrees 06 min N and longitude 27 degrees 32 min E to 27 degrees 40 min E. The largest city in eastern Romania is Iași and the seat of Iași county. Land surface temperature, calculated from remote sensing data is used in a lot of fields of science, like: climate change, hydrology, forestry, urban planning, oceanography, agriculture etc. In earlier thermal remote sensing studies, much weight has been placed on using NDVI as the major indicator of urban climate. Results was indicated there is a linear relationship between Land Surface Temperature and Normalized Difference Vegetation Index. The images were taken for the warmest day for period 2013-2016. In that period, the mean temperature raised about 20 Celsius degrees, so as to 2016 the mean temperature was over 30 Celsius degrees and the maximum temperature exceeds 40 Celsius degrees. Analyzing the relationship between Land surface temperature and Normalized difference vegetation index, the R2 fluctuates significantly from over 0.4 to 0.53. For environmental studies and earth, land surface temperature is now considered an important parameter. Modeling for estimating Land Surface Temperature from Landsat thermal imagery can be a good, time saving and effective options for researchers dealing with it. [ABSTRACT FROM AUTHOR]

The presented paper deals with the issue of assessing the condition of winter wheat (Triticum aestivum L.) stand during its development in the spring period. The field experiment was established in 2020; two plots sized 25 ha and 16 ha were selected with a model plant of winter wheat. In the spring period (BBCH 35 and BBCH 51), both plots were monitored using an unmanned aerial vehicle (UAV) and Sentinel 2 satellites. After the end of the monitoring, spectral analysis of pictures taken was made and a basic NDVI vegetation index was calculated. Subsequently, spectral maps with this vegetation indexes were prepared. In the initial stage of model plant growth (BBCH 35), Unmanned aerial vehicles exhibited a greater sensitivity of measured data and was able to detect local damage to the stands. Differences in the measured data between UAV and Sentinel 2 were decreasing with the increasing amount of Triticum aestivum L. biomass, and in the advanced stage of vegetation (BBCH 51), a moderately strong positive correlation (R > 0.65) was found between the data measured by UAV and Sentinel 2. The measured values showed that satellite images were less accurate in detecting the occurrence of plant biomass at the beginning of growth. On the other hand, they can be more effective than UAV with the increasing plant biomass as satellite technologies can cover a considerably large area of earth surface during a single flight. [ABSTRACT FROM AUTHOR]

The study deals with a usage of spectral indices for the ecological control of the state of forestry with particular emphasis on the control of causes and effects of forest fires, their effective detection and prevention. The Karabai tract was selected as an object of study, which is a monoculturally planted pine forest with predominance of Rhinus sylvestris L. and P. pallasiana D. Don, located on the territory of Kherson region, Ukraine. This forestry is known for one of the largest forest fires in Ukraine, which took place in the summer of 2007, and by the results of which, directly at the site, more than 25 km² of forest was destroyed. Google Earth Engine and MapInfo Professional software were used as research tools. In the analysis of the object of study according to the results of the calculation of spectral indices, the following surfaces were constructed: NDVI (Normalized Difference Vegetation Index) – to determine the area and level of damage to the forest; NBRT (Normalized Burn Ratio Thermal) – for indicating the fire and the character of a fire spread; NDWI (Normalized Difference Water Index) – for the diagnosis of the level of aridity of forest areas, which is accordingly a sign of the risk of forest fires in the summer. It was investigated, that the fire occurred in the central part of the forestry war caused by excessive dryness (prolonged absence of rainfall and high air temperatures). It is proved that the fire ruined much more than the mentioned official area, which is caused by the extinction of adjacent burnt vegetated areas. Due to the results of the analysis, a number of forestry measures are proposed to prevent the occurrence of fires. In particular: placement of fire protection strips along the most arid areas of the forestry, placement of fire ponds, etc. [ABSTRACT FROM AUTHOR]

The climatic drought indices are used for evaluation of drought conditions, but also vegetation indices derived from remote sensing images reflect the impact of drought on vegetation vigor. The aim of the study was to confirm suitability of normalized difference vegetation index (NDVI) as a tool for drought assessment in conditions of Slovakia. Verification of the method was done by correlation analysis between monthly NDVI and Z-index during the main growing season (from April to October) in the period from 2000 to 2017. Twelve sites were chosen for calculation of Z-index according to limited climatic parameters. NDVI was derived from remote sensing images at the level of districts where these sites are located. The results showed that the correlations varied between months. The strongest relationship expressing the influence of drought on vegetation vigor was observed mainly from June to August with the level of significance α ≤ 0.01 in most localities. The relationship between NDVI and Z-index was lower at the beginning (April, May) and at the end (October) of growing season. The most important finding is that NDVI can be used for evaluation of drought, but the growth stage of vegetation must be considered. [ABSTRACT FROM AUTHOR]

Variable rate application (VRA) of fertilizers represents specific crop management where N is applied on the basis of information about field yield potential, plant health and quality. The main goal of this study was to assess the influence of nitrogen VRA (VRA-N) on grain yield and nitrogen use efficiency in winter wheat production. The VRA has been realized according application maps only for production and qualitative dose of N. Application maps for individual fields were prepared by SatAgro Company on the basis of analysis of satellite images (Sentinel 2, SPOT). The main output of this analysis was the determination of the amount of the plant biomass on the field using vegetation index NDVI. The principle of fertilization was different for production and qualitative dose. During production application of N, the highest doses were applied on the part of the field with the lowest amount of nitrogen and conversely. Above all during qualitative application, the highest dose of N was applied on the best part of the field. The field experiment with the application maps from SatAgro Company was established in Spearhead Czech, in 2016 and VRA technologies have been tested there on more than 4 000 ha each year since 2012. Measurements of grain yield (GY) and nitrogen use efficiency (NUE) were carried out to study the above goal in 2016 and 2017. In both years of the experiment, the results showed that the VRA-N had significant positive effect on GY and NUE by wheat. The average GY from variants with VRA-N was higher by 200 kg/ha in 2016 and by 317 kg/ha in 2017, compared to the variant where conventional technology was used. Above all, the ratio between the amount of N removed from the field with the winter wheat and the amount of applied N, i.e. NUE, was higher by about 6 % in variant where VRA technology was used. The values NUE showed a positive effect of VRA-N on utilization of N indicating the reduction of the environmental risk of N loss from the agro-ecosystem. [ABSTRACT FROM AUTHOR]

Copernicus is a European Union programme designed to provide a service in delivering free, openly accessible data about the Earth's surface through satellite and in-situ observations. On the other hand, Landsat represents the world's longest standing continuously acquired collection of space-based, moderate-resolution, land remote sensing data for those working in agriculture, geology, forestry, regional planning, education, mapping, and global change research. Although the images of these satellite systems are characterised by coarse resolution, they can be a good source of information and data to provide better observation of certain objects or phenomena of interest to experts and help them in decision-making. This paper presents an analysis of the vegetation indices of urban vegetation in the city of Zagreb, Croatia, during 2017, calculated using Sentinel 2 and Landsat 8 bands. The information and data obtained as the results of interpreting and processing Sentinel 2 and Landsat 8 satellite systems images can be used by experts in forestry and urban planning as a support in making decisions on urban vegetation management. The results obtained were analysed and interpreted. The interpretation of the results was made visually and statistically, and then presented by means of statistical parameters (correlation, regression). Some channels of the Sentinel 2 satellite system have better surface resolution than all the multispectral channels of the Landsat 8 satellite system. However, the Landsat 8 satellite system channels have better surface resolution than some Sentinel 2 satellite system channels. In both cases, a surface resolution is 10 m and higher. So it is not possible to precisely identify certain objects and phenomena of interest in the field, but only to detect them with a certain level of confidence. Therefore, processing that included the channels of both systems was performed. [ABSTRACT FROM AUTHOR]

The information obtained on the basis of remote sensing is contained in cosmic or aerial images which can be interpreted for many purposes. Building these images is based on detecting and registering the electromagnetic energy reflected or issued by the surface of the objects present on the visual field of the sensors, which interacted with the electromagnetic energy issued by a natural source (e.g. Sun, Moon) or an artificial one (e.g. radar). The remote sensing data is public, meaning it can be acquired from anywhere in the world by anyone, with only some restriction. In order to achieve territorial analysis of the study area, acquisition as well as preprocessing, processing and statistical analysis of satellite images are necessary, using specialized programs in the field of remote sensing and geographic spatial data management. The Landsat program is the longest running enterprise for the acquisition of satellite imagery of the Earth. On 23rd July 1972 the Earth Resources Technology Satellite was launched. This was eventually renamed Landsat. Most recently, Landsat 8 was launched, on 11th February 2013. The equipment on the Landsat satellites has acquired millions of images. They were archived in the United States and at Landsat receiving stations around the world and represent a unique resource for global change research and for applications in agriculture, cartography, geology, forestry, regional planning, surveillance and education. The vegetation monitoring process in Caransebes was very much improved by using satellite images, NVDI index and field work. [ABSTRACT FROM AUTHOR]

In earlier studies, we conducted joint assessment of climate change in recent decades and change of vegetation cover in the taiga zone of Russia. We used Normalized Difference Vegetation Index (NDVI) to assess vegetation cover change. We found that shrub vegetation is important indicator of climate change in the Northern regions of Russia. Previously, we assessed change of climate parameters and vegetation cover within different growing seasons (periods of the calendar year when the surface air temperature is above +5°C and +10°C). These are the periods of active growth of the biomass. The differentiation of the growing seasons in our study we performed in manual mode according to the data collected on meteorological stations. For the purposes of extrapolation of the obtained dependencies on areas where meteorological stations are absent, we need a tool that allows to supply the differentiation of growing seasons in the automated mode, using remote sensing data. Normalized Difference Water Index (NDWI) proposed by B. Gao allows to determine beginning of the growing season and beginning of the leaves yellowing. Currently we have designed the technique for automation of differentiation of the growing seasons using NDWI and studied its application. The study was partially supported by the Russian Foundation for basic research (RFBR), research project No. 14-05-00858 A. [ABSTRACT FROM AUTHOR]

We know that various plants and vegetation in general dormant during the winter period in its growth and development, and during the spring vegetation flourishes and is the largest plant growth then. There are several types of standstill of plants, deep winter hibernation, organic or forced and preliminary or summer hibernation. Suppose that during the winter period the plant is not resting completely and that very small changes can register using remote sensing and other geodetic methods. Presenting an analysis of processed NDVI images of various plants during the winter period showing changes on weekly basis and propose new methods for monitoring plant health. Presenting the continuous monitoring of changes with NDVI vegetation index using statistics and analysis of registered activities on the basis of the collected field data. Different plants from around the world will be analyzed which contain also certain number of evergreen plants. Pictures and other geodata were collected during winter period with GoPro camera containing NDVI lens. The previous works are mainly based on the analysis of changes in vegetation activity obtained by using the satellite imagery. [ABSTRACT FROM AUTHOR]

An increase of natural hazard events can be observed, in the last few years, at a global scale. Its impact is more often assessed from a socio-economical point of view and less from an environmental perspective. This paper is focused on the evaluation of the natural hazard events impact on inhabited areas and natural sites, using remote sensing techniques. Study area is extended on two countries: Romania (EU-Country) and Republic of Moldova (EEP-country), and is represented by the entire historical region of Moldavia. Two sample areas from different countries were chosen in order to compare the results of governmental measures taken by each country, in similar natural conditions. The proposed methodology involved the use of satellite imagery, and its processing with MOD13Q1 product, derived from MODIS radio spectrometer, for the drought event of 2007. MOD13Q1 is the catalog name for NDVI vegetation index. The results reveal that the impact in the territory is different in these two countries. In Romania, due to a lack of irrigation infrastructure, the drought effects were more intense than in the Republic of Moldova. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is one of the key parameters of environment quality and environment change. Studies of spatial redistribution of the thermal emission and its relationship with land use of different types are very important for recognition of the urban microclimate. Land use planning on urbanized territories should consider environmental, social and industrial factors in the context of sustainable development goals. Due to this, understanding of role of the urban land use mosaic in formation of urban heat islands is needed to provide control and reduce of the heat islands in arid regions. Yazd city (located in Iran) plays important role in formation of the thermal conditions of surrounding territories. In our study, we used the Temperature Emissivity Separation (TES) algorithm for LST retrieving from the remote sensing data collected by Landsat 5. We produced comparative analysis of land use maps, thermal maps and Normalized Difference Vegetation Index (NDVI) maps of Yazd city. Using the comparative analysis, we made a preliminary assessment of the role of different urban land use types in formation of thermal conditions in Yazd. [ABSTRACT FROM AUTHOR]

Detection of environmental change using satellite imagery and ArcGIS software in an area with agricultural use, affected by atmospheric drought, deforestation and destruction of the irrigation system proved to be important for observing trends in changes over time. Fields Leu-Rotunda and Dabuleni (Plain of Oltenia), located in southern Romania, represent vast stretches of plains, with sandy soil texture of low fertility and high thermal conductivity. The humus content being 0,2-0,9%, and the plants wilting coefficient ranging from 1,1 to 2,1%. The maximum temperature of the air in July 1993 reached 42,8 º C and 69,5 ºC at the surface of the soil in July 2002. The impact of the climatic elements were detected with the help of satellite images, using the statistical and mathematical method (NDVI). The timing was the month of maximum water requirement, the month of July. In the same month, different conditions have been observed with significant differences of affected polygons for the years 1987, 1993, 2006, 2007 and 2009. [ABSTRACT FROM AUTHOR]

In a changing climate and natural manifesting of weather consequence in a mountain slope effluents washout processes of soil and soil cover leads to decreasing productivity of cultures, pollution and degradation of rivers. Therefore agricultural landscapes of the mountain river basins are consider based on adaptive landscape system of agriculture (ALSA) and investigation their changing dynamics. Research of mountain river basin lands used for an agriculture and pastures, observation through satellite images is one of the main purpose of nowadays. For this purpose were chosen Landsat satellite images from different years, comparing these satellite images as a result of the agricultural landscapes dynamic analysis for rational land use, biodiversity investigates and widely used to identify the consequence of natural appearance on the agricultural crops. [ABSTRACT FROM AUTHOR]

In the Iberian Peninsula, precipitation mainly falls during autumn and winter and is marked by large space and time variability. Therefore, the Peninsula has large areas prone to drought. This study aims to analyse spatiotemporal drought patterns in the Iberian Peninsula based on the Vegetation Condition Temperature Index (VTCI) and to investigate the response of land cover types towards droughts during spring and summer seasons from 2001 to 2005 and in 2007 and 2010 (highly dry and wet years). VTCI is a remote sensing drought index and uses information on vegetation activity (Normalized Differenced Vegetation Index - NDVI) and Land Surface Temperature (LST). VTCI overcomes problems that may arise when NDVI is solely used for drought monitoring. The inter-annual VTCI course shows a typical Mediterranean pattern that is particularly influenced by the relief. The land cover types most prone to drought are agricultural surfaces, and the most resilient ones are forests. [ABSTRACT FROM AUTHOR]