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    Wyświetlanie 1-7 z 7
    Tytuł:
    Exogenous regulation of the potatoes’ adaptive potential when using bio stimulants
    Autorzy:
    Shitikova, Aleksandra V.
    Abiala, Adewale A.
    Tevchenkov, Alexander A.
    Bazhenova, Svetlana S.
    Lazarev, Nikolay N.
    Kurenkova, Evgeniya M.
    Powiązania:
    https://bibliotekanauki.pl/articles/2174370.pdf
    Data publikacji:
    2022
    Wydawca:
    Instytut Technologiczno-Przyrodniczy
    Tematy:
    abiotic stress
    antioxidant
    biopolymer chitosan
    growth regulators
    potato
    N-tester
    near infrared
    normalized difference vegetation index
    NDVI
    Opis:
    Potato from the Solanaceae family is one of the most important crops in the world and its cultivation is common in many places. The average yield of this crop is 20 Mg·ha-1 and it is compatible with climatic conditions in many parts of the world. The experiment studied the possibility of exogenous regulation of the adaptive potential available for four potato cultivars through the use of growth stimulants with different action mechanisms: 24-epibrassinolide (EBL) and chitosan biopolymer (CHT). The results allowed us to establish significant differences in growth parameters, plant height, leaf index, vegetation index, chlorophyll content, and yield structure. Monitoring growth and predicting yields well before harvest are essential to effectively managing potato productivity. Studies have confirmed the empirical relationship between the normalised difference vegetation index (NDVI) and N-tester vegetation index data at various stages of potato growth with yield data. Statistical linear regression models were used to develop an empirical relationship between the NDVI and N-tester data and yield at different stages of crop growth. The equations have a maximum determination coefficient (R2) of 0.63 for the N-tester and 0.74 for the NDVI during the flowering phase (BBCH1 65). NDVI and N-tester vegetation index positively correlated with yield data at all growth stages.
    Źródło:
    Journal of Water and Land Development; 2022, 54; 234--238
    1429-7426
    2083-4535
    Pojawia się w:
    Journal of Water and Land Development
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Land cover change assessment of vaal harts irrigation scheme using multi-temporal satellite sata
    Autorzy:
    Otieno, F. A.
    Ojo, O. I.
    Ochieng, G. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/205331.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    land use change
    vaal harts
    GIS
    normalized difference vegetation index
    NDVI
    VHS
    Opis:
    Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.
    Źródło:
    Archives of Environmental Protection; 2013, 39, 4; 59-70
    2083-4772
    2083-4810
    Pojawia się w:
    Archives of Environmental Protection
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Regional Mapping of Land Surface Temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of South-South Coastal Settlements of Rivers State in Nigeria
    Autorzy:
    Nwaerema, Peace
    Ajiere, Suzan
    Powiązania:
    https://bibliotekanauki.pl/articles/1031686.pdf
    Data publikacji:
    2020
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Regional
    land surface emissivity
    land surface temperature
    normalized difference vegetation index
    population
    urbanization
    Opis:
    This study is the regional mapping of Land Surface temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of south-south coastal settlements of Rivers State in Nigeria. The Google Earth Engine (GEE) of satellite remote sensing origin was used in the study. It was observed that land surface area of the south-south coastal settlements of the region hosting a total population of 3,344,706 persons had undergone severe modification and alteration of vegetal cover by increased human activities especially in the central area. Emissivity in the region increased from the center to the rural settlements with values ranging 0.98 to 0.99 and difference of 0.01 indicating that there was increased modification of the regional land surface. Land surface temperature decreased from the regional center to the rural settlements ranging between 22.12 ºC to 35.99 ºC with a difference of 13.87 ºC. However, LST was scattered in different settlement spots especially in the northern region such as Aleto, Finema (south); Rumuolu, Odogwa, Abara, Umuechem, Rumuola, Ambroda (north) among others. The normalized vegetation index showed -0.54358 to 0.409327 having the difference of 0.952907 indicating greater variation in vegetal cover across the region. Thus, NDVI in the region increased from the regional center to the outskirts of the area. Urbanization in the south-south region of Rivers State had extended severely to the rural settlements. Therefore, it is recommended that policy makers and regional planners should protect the area from adverse vegetal lost and heat effects by implementing regional greening practices.
    Źródło:
    World News of Natural Sciences; 2020, 28; 76-86
    2543-5426
    Pojawia się w:
    World News of Natural Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Detection and classification of vegetation areas from red and near infrared bands of LANDSAT-8 optical satellite image
    Autorzy:
    Nallapareddy, Anusha
    Powiązania:
    https://bibliotekanauki.pl/articles/2097428.pdf
    Data publikacji:
    2022
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    classification
    remote sensing
    soil adjusted vegetation index
    normalized difference vegetation index
    vegetation
    Opis:
    Detection and classification of vegetation is a crucial technical task in the management of natural resources since vegetation serves as a foundation for all living things and has a significant impact on climate change such as impacting terrestrial carbon dioxide (CO2). Traditional approaches for acquiring vegetation covers such as field surveys, map interpretation, collateral and data analysis are ineffective as they are time consuming and expensive. In this paper vegetation regions are automatically detected by applying simple but effective vegetation indices Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) on red(R) and near infrared (NIR) bands of Landsat-8 satellite image. Remote sensing technology makes it possible to analyze vegetation cover across wide areas in a cost-effective manner. Using remotely sensed images, the mapping of vegetation requires a number of factors, techniques, and methodologies. The rapid improvement of remote sensing technologies broadens possi-bilities for image sources making remotely sensed images more accessible. The dataset used in this paper is the R and NIR bands of Level-1 Tier 1 Landsat-8 optical remote sensing image acquired on 6th September 2013, is processed and made available to users on 2nd May 2017. The pre-processing involving sub-setting operation is performed using the ERDAS Imagine tool on R and NIR bands of Landsat-8 image. The NDVI and SAVI are utilized to extract vegetation features automatically by using python language. Finally by establishing a threshold, vegetation cover of the research area is detected and then classified.
    Źródło:
    Applied Computer Science; 2022, 18, 1; 45--55
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Improvement of the Agricultural Yields Forecasting Model Using the Software Product “Land Viewer”
    Ulepszenie modelu prognozy plonów upraw w oprogramowaniu „Land Viewer”
    Autorzy:
    Kolodiy, Pavlо
    Pіdlypna, Maryna
    Powiązania:
    https://bibliotekanauki.pl/articles/385334.pdf
    Data publikacji:
    2020
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    zdjęcia satelitarne
    interfejs programu „Land Viewer”
    znormalizowany wskaźnik różnicy wegetacji
    pictures from satellites
    programmatic interface “Land Viewer”
    Normalized Difference Vegetation Index
    Opis:
    Using the data of the remote sensing the Earth, new opportunities in assessing the state of agricultural crops and yield forecasting have been considered. In addition to the above-ground information, as shown by numerous studies conducted earlier, most parameters of the germination and development of agricultural crops can be restored and used from satellite images. Thanks to the software product “Land Viewer”, which enables pictures to be taken from Landsat 4, 5, 7, 8, Sentinel 2 and Terra satellites, and it will provide improving the model and assessment of the biomass potential of agricultural crops. The data obtained from remote sensing during the cropping season, show the information on the condition of agricultural crops sown according to the vegetation stages (photosynthesis process) in crops. At various levels of development, in terms of the Normalized Difference Vegetation Index (NDVI), the seasonal pattern of crops photosynthesis is well reflected, which is associated with the above-ground biomass. The results have been presented in the current model of crop yield forecasting. The improved forecasting model enables significant increases in the economic efficiency of the research, and ensure the accuracy of the data on the physiological processes of agricultural crops, yields, and efficiency of obtaining the data on the research object.
    Jak pokazują liczne badania, większość parametrów kiełkowania oraz stan rozwoju upraw rolnych można określić na podstawie zdjęć satelitarnych. W artykule wskazano nowe możliwości oceny stanu upraw rolnych i prognozowania plonów z użyciem danych teledetekcyjnych. Zastosowano do tego celu oprogramowanie „Land Viewer”, które umożliwia wykorzystanie zdjęć z satelitów Landsat 4, 5, 7, 8, Sentinel 2 i Terra oraz poprawę modelu i ocenę potencjału biomasy upraw rolnych. Dane uzyskane za pomocą teledetekcji podczas sezonu upraw dostarczają informacji o stanie roślin na różnych etapach wegetacji (proces fotosyntezy). Na różnych poziomach rozwoju, ocenianego na podstawie znormalizowanego wskaźnika różnicy wegetacji (NDVI), dobrze odzwierciedla się sezonowość fotosyntezy upraw, co jest związane z biomasą nadziemną. Wyniki zostały przedstawione w obecnie stosowanym modelu prognozowania plonów. Ulepszony model prognozowania pozwala na znaczne zwiększenie efektywności ekonomicznej badań, a także zapewnia większą dokładność danych o procesach fizjologicznych upraw rolnych, plonach oraz wydajności produkcji w obiekcie badawczym.
    Źródło:
    Geomatics and Environmental Engineering; 2020, 14, 1; 59-67
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Use of remote sensing as an indicator of the urban heat island effect: the case of the municipality of Guelma (north-east of Algeria)
    Autorzy:
    Khallef, Boubaker
    Powiązania:
    https://bibliotekanauki.pl/articles/24201205.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
    Tematy:
    Landsat 8
    LST
    land surface temperature
    NDVI
    normalized difference vegetation index
    NDBI
    Guelma
    Algeria
    temperatura powierzchni ziemi
    znormalizowany różnicowy wskaźnik wegetacji
    Kalima
    Algieria
    Opis:
    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.
    Źródło:
    Geomatics, Landmanagement and Landscape; 2023, 3; 61--72
    2300-1496
    Pojawia się w:
    Geomatics, Landmanagement and Landscape
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Change on detection of vegetation cover and soil salinity using GIS technique in Diyala Governorate, Iraq
    Autorzy:
    Adeeb, Haneen Q.
    Al-Timimi, Yaseen K.
    Powiązania:
    https://bibliotekanauki.pl/articles/35519874.pdf
    Data publikacji:
    2021
    Wydawca:
    Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
    Tematy:
    differencing image
    normalized difference
    vegetation index
    NDVI
    salinity index
    GIS
    Iraq
    Opis:
    Soil salinity is one of the most important problems of land degradation, that threatening the environmental, economic and social system. The aim of this study to detect the changes in soil salinity and vegetation cover for Diyala Governorate over the period from 2005 to 2020, through the use of remote sensing techniques and geographic information system. The normalized difference vegetation index (NDVI) and salinity index (SI) were used, which were applied to four of the Landsat ETM+ and Landsat OLI satellite imagery. The results showed an increase in soil salinity from 7.27% in the period 2005–2010 to 27.03% in 2015–2020, as well as an increase in vegetation from 10% to 24% in the same period. Also the strong inverse correlation between the NDVI and the SI showed that vegetation is significantly affected and directly influenced by soil salinity changes
    Źródło:
    Scientific Review Engineering and Environmental Sciences; 2021, 30, 1; 148-158
    1732-9353
    Pojawia się w:
    Scientific Review Engineering and Environmental Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-7 z 7

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