Wszystkie pola: sensing - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Drought Detection by Application of Remote Sensing Technology and Vegetation Phenology
Autorzy:: Uttaruk, Y.
Laosuwan, T.
Powiązania:: https://bibliotekanauki.pl/articles/125427.pdf
Data publikacji:: 2017
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: drought detection
remote sensing
vegetation phenology
Opis:: Drought is a natural phenomenon as it often occurs in the area of Yasothon province, northeastern of Thailand. It causes effects on vegetation condition in the area. Drought information might be useful for local government to prepare for prevention and mitigation plan in the future. For this reason, the primary objective of the research was to conduct the examination of this province to find severe drought years. Firstly, the researcher needed to find Normalized Differences Vegetation Index (NDVI) and Vegetation Condition Index (VCI) by analyzing monthly Landsat data acquired at different periods of time from January to December 2014, 2015, and 2016, covering 4,096 km². Then, the researcher needed to find relationship between VCI and monthly rainfall represented in term of space and time. As results, VCI and its relationship with monthly rainfall were congruent. VCI showed that the drought area was 33.87% or 1,387.32 km² of studied area in 2014, 16.24% or 665.19 km² of studied area in 2015 and 27.95% or 1,144.83 km² of studied area in 2016. Therefore, the most and the least severe drought years were 2014, 2016, and 2015 respectively.
Źródło:: Journal of Ecological Engineering; 2017, 18, 6; 115-121
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Application of Remote Sensing for Temperature Monitoring: the Technique for Land Surface Temperature Analysis
Autorzy:: Laosuwan, T.
Gomasathit, T.
Rotjanakusol, T.
Powiązania:: https://bibliotekanauki.pl/articles/123648.pdf
Data publikacji:: 2017
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: remote sensing
Landsat-8 OLI/TIR data
land surface temperature
Opis:: This research aimed to present the technique for land surface temperature analysis with the data from Landsat-8 Operational Land Imager (OLI) /Thermal Infrared Sensors (TIR) in Meuang Maha Sarakham District, Maha Sarakham Province, Northeast Thailand. The research was conducted as following three steps: 1) Collecting the satellite data in thermal infrared band from Landsat-8 TIR satellite to adjust the value of Top of Atmosphere (ToA) Reflectance and then analyzing the land Surface temperature 2) Collecting multi-band data from Landsat-8 OLI satellite to adjust the value of Top of Atmosphere (ToA) Reflectance and then analyzing values of Normalized Difference Vegetation Index (NDVI), Fractional Vegetation Cover (FVC) and Land surface Emissivity (LSE) 3) Bringing the results of 1) and 2) to analyze the land surface temperature with split window algorithm. The research results indicated that the analysis of the data from Landsat-8 OLI/TIR satellites in 18 March 2015 indicated a mean temperature of 33.57 °C.
Źródło:: Journal of Ecological Engineering; 2017, 18, 3; 53-60
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Integration Remote Sensing and Meteorological Data to Monitoring Plant Phenology and Estimation Crop Coefficient and Evapotranspiration
Autorzy:: Hassan, Diaa Fliah
Abdalkadhum, Aysar Jameel
Mohammed, Rafal J.
Shaban, Amin
Powiązania:: https://bibliotekanauki.pl/articles/2086414.pdf
Data publikacji:: 2022
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: actual evapotranspiration
crop coefficient
remote sensing
vegetation index
Opis:: The water requirements of the wheat crop are represented by the actual evapotranspiration, which depends on the meteorological data of the study area and the amount of water consumed during the season. Estimation of crop coefficients (Kc) and evapotranspiration (ETc) using remote sensing data is essential for decision-making regarding water management in irrigated areas in arid and semi-arid large-scale areas. This research aims to estimate the crop coefficient calculated from remote sensing data and the actual evapotranspiration values for the crop. The FAO Penman-Monteith equation has been used to estimate the reference evapotranspiration from meteorological data. Linear regression analysis was applied by developing prediction equations for the crop coefficient for different growth stages of comparing with the vegetation cover index (NDVI). The results showed that (R2 = 0.98) between field crop coefficient and crop coefficient predicted from (Kc = 2.0114 NDVI-0.147) in addition to (RMSE = 0.92 and (d = 0.97).
Źródło:: Journal of Ecological Engineering; 2022, 23, 4; 325--335
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Colorimetric Parameters Modeling of Test Micro-Ecosystems for Lands Pollution Remote Sensing
Autorzy:: Vуsotska, Olena
Greben, Aleksandr
Kalashnikova, Vasilisa
Klochko, Tetiana
Rakhmetullina, Saule
Kotyra, Andrzej
Mamyrbaev, Orken
Iskakova, Aigul
Powiązania:: https://bibliotekanauki.pl/articles/1839122.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: pollution
system dynamics
colorimetric parameters
remote sensing
Opis:: The paper describes a methodology of determining the toxicity sources, using bioassay based on the wildlife objects that change their colorimetric parameters under the influence of toxic factors. The work explores the dynamism of the colorimetric attributes associated with plant pigments. It can be determined by computer processing of the data obtained from digital remote sensing of the lands affected by toxic pollution by means of such relatively low-cost and straightforward methods as digital photography from an aircraft or a drone. The results obtained do not allow direct measurements but rather serve as a basis for the development and characterization of new biomarkers.
Źródło:: Journal of Ecological Engineering; 2021, 22, 2; 161-168
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Ocena możliwości zastosowania teledetekcyjnych metod pomiaru eutrofizacji śródlądowych zbiorników wodnych
Assessment of the possibility of using remote sensing methods for measuring eutrophication of inland water reservoirs
Autorzy:: Pierzchała, Łukasz
Powiązania:: https://bibliotekanauki.pl/articles/1574486.pdf
Data publikacji:: 2020
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: eutrofizacja
chlorofil a
teledetekcja
monitoring jakości wód
eutrophication
chlorophyll-a
remote sensing
water quality monitoring
Opis:: Rozwój satelitarnych technologii obserwacji powierzchni ziemi stwarza możliwości wdrożenia nowoczesnych narzędzi monitoringu jakości wód powierzchniowych. W niniejszym artkule zaprezentowano wyniki badań, których celem było opracowanie zautomatyzowanej metody pomiaru eutrofizacji wód śródlądowych. Przeanalizowano zalety i ograniczenia przedmiotowej technologii oraz oceniono potencjalne możliwości jej wykorzystania. Podstawowym wskaźnikiem stanu troficznego wód powierzchniowych jest koncentracja chlorofilu-a w wodzie. W ramach przeprowadzonych badań uzyskano silny związek pomiędzy wartościami koncentracji chlorofilu-a określonych na podstawie standardowych metod pomiarowych, a wartościami tego parametru obliczonymi na podstawie satelitarnych danych spektralnych. Przedstawiono także funkcjonalności opracowanego oprogramowania pozwalającego na automatyczny pomiaru eutrofizacji wód śródlądowych za pomocą teledetekcji. Pomimo szeregu ograniczeń technologii, wykazano wysoki potencjał aplikacyjny przedmiotowego rozwiązania.
The development of satellite technologies for observing the earth’s surface creates the possibility of implementing modern tools for surface waters quality monitoring. This article presents the results of the research aimed at developing an automated method for assessment of the eutrophication of inland waters. The advantages and limitations of the technology were analyzed and the potential possibilities of its application were described. The basic indicator of the trophic state of surface waters is the concentration of chlorophyll-a in the water. As result of the research, a strong relationship was obtained between the chlorophyll-a concentration values determined on the basis of standard measurement methods, and the chlorophyll-a values calculated on the basis of satellite spectral data. The functionalities of the developed software for automated measuring eutrophication of inland water using temote sensing were also presented. Despite a number of limitations of the technology, high application potential of the solution has been demonstrated.
Źródło:: Inżynieria Ekologiczna; 2020, 21, 4; 27-32
2081-139X
2392-0629
Pojawia się w:: Inżynieria Ekologiczna
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Use of Spatial Remote Sensing to Study the Temporal Evolution of the Water Retention of Al Massira Dam in Morocco
Autorzy:: Bounif, Mohammed
Rahimi, Abdelmejid
Boutafoust, Rachid
El Mjiri, Ikram
Powiązania:: https://bibliotekanauki.pl/articles/2202368.pdf
Data publikacji:: 2023
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: spatial remote sensing
Al Massira dam reservoir
spectral indices
Landsat
satellite image
Doukkala
irrigated perimeter
Opis:: In Morocco, irrigated agriculture is still very much linked to the climate and the water retention of dams. With climate change, this country is experiencing recurrent drought, which has led to deficits in water inflow from the rivers to the various dams. The Al Massira dam, the area of study, does not escape this trend. This dam is the only surface water source for the irrigated area of Doukkala. Therefore, special attention must be paid to monitoring this resource at this dam. Thus, the proposed study examined the possibilities offered by spatial remote sensing to improve the current information system. It aims to evaluate this dam’s reservoir by exploiting the data generated by using satellite images. The Landsat satellite images were used to assess the area of this dam by adopting an approach combining spectral indices with thresholding. Then, the existing relationship between the area of the dam lake were examined, determined by spatial remote sensing and its water retention measured in situ. The results obtained revealed a strong correlation between the two parameters. Therefore, a study was conducted to find the best model for predicting the dam’s impoundment based on its lake. The second-degree polynomial model showed a better performance. Given the results obtained, it is recommended to use geospatial methods in the current and prospective monitoring and steering system of water resources.
Źródło:: Journal of Ecological Engineering; 2023, 24, 2; 340--349
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Ocena stanu roślinności na zielonych ścianach z wykorzystaniem metod teledetekcyjnych
Condition of vegetation on the green wall with the use of remote sensing methods
Autorzy:: Skarżyński, D.
Pływaczyk, A.
Pęczkowski, G.
Powiązania:: https://bibliotekanauki.pl/articles/399545.pdf
Data publikacji:: 2015
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: teledetekcja
NDVI
ocena stanu roślinności
zielone ściany
pokrycie
remote sensing
evaluation of vegetation condition
green walls
coverage
Opis:: Badania nad możliwością wykorzystania metod teledetekcyjnych w celu oceny stanu roślinności na zielonych ścianach wykonano na modelach doświadczalnych w latach 2010–2011. Analizowano dwa modele różniące się pomiędzy sobą podłożem wegetacyjnym: model retencyjny (MR I) z substratem glebowym oraz model ekonomiczny (ME II) z filcem hydroponicznym. W poszczególnych panelach posadzono rośliny reprezentujące krzewy, byliny oraz trawy. Łącznie na modelach doświadczalnych zastosowano 60 gatunków roślin dobranych w zależności od wystawy ścian. Ocenę kondycji roślin wykonano na podstawie prowadzonych obserwacji terenowych oraz analizy znormalizowanego wskaźnika roślinności NDVI (ang. Normalized Difference Vegetation Index). Stwierdzono, że roślinność na modelu retencyjnym (MR I) posiada znacznie wyższe wartości wskaźnika NDVI w porównaniu z modelem ekonomicznym (ME II). Porównanie procentowego pokrycia paneli modelu retencyjnego (MR I) i ekonomicznego (ME II) przez roślinny wykonano poprzez oddzielenie płaszczyzny tła od powierzchni roślin, ustalając jako kryterium podziału wskaźnik NDVI z przedziału od -1 do 0,2. Wykazano wyraźny kontrast pomiędzy stopniem pokrycia na badanych modelach na poszczególnych elewacjach. Na modelu retencyjnym (MR I) pokrycie paneli roślinami było znacznie większe niż na modelu ekonomicznym (ME II), gdzie rozwój roślin był ograniczony. Rozwój roślinności na modelu retencyjnym (MR I) z wykorzystaniem substratu glebowego w panelach roślinnych był prawidłowy co wskazuje na możliwość stosowania tego typu rozwiązań w warunkach klimatycznych Dolnego Śląska. Roślinność na modelu ekonomicznym (ME II) charakteryzuje gorszy rozwój w całym okresie wegetacyjnym, dlatego też nie jest on zalecany. Badania wykazały, że możliwa jest ocena stanu roślinności na zielonych ścianach z wykorzystaniem metod teledetekcyjnych bazujących na zmodyfikowanym sprzęcie fotograficznym.
Research on the possibility of using remote sensing methods to evaluate condition of vegetation on the green walls were performed on experimental models in 2010–2011. Two models that differ from one another with vegetation layer were analyzed: a retention model (MR I) with substrate soil and an economic model (ME II) with hydroponic felt. In the individual panels plants representing shrubs, perennials and grasses were planted. In total, on experimental models 60 plant species was applied depending on the exhibition of the walls. The evaluation of the plants condition was performed based on field observations and the analysis of Normalized Difference Vegetation Index (NDVI). Evaluation of vegetation condition using remote sensing methods leads to the conclusion that the vegetation on retention model (MR I) have a much higher NDVI index value compared with the economic model (ME II). The comparison of the percent coverage of panels on retention model (MR I) and economic model (ME II) by the plants was done by separating the background plane from the plant surface. As a division criterion NDVI ratio in the range from -1 to 0.2 was taken. The results showed a clear contrast between the level of plant coverage of the examined models for individual facades. On the retention model (MR I) panels plant covering was significantly higher than on an economic model (ME II) where plant growth was limited. The growth of vegetation on the retention model (MR I) using substrate soil in plant panels was normal suggesting the potential use of such solutions in the climatic conditions of Lower Silesia. Vegetation on the economic model (ME II) is characterized by a worse growth throughout the growing season, which is why it is not recommended. The study showed that it is possible to evaluate the conditions of vegetation on the green walls with the use of remote sensing methods based on a modified photographic camera.
Źródło:: Inżynieria Ekologiczna; 2015, 43; 166-171
2081-139X
2392-0629
Pojawia się w:: Inżynieria Ekologiczna
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Cultural Landscape, Floods and Remote Sensing
Autorzy:: Húska, D.
Jurík, L.
Tátošová, L.
Šinka, K.
Jakabovičová, J.
Powiązania:: https://bibliotekanauki.pl/articles/123324.pdf
Data publikacji:: 2017
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: drainage
flood
landscape
river
satellite
Opis:: The dynamics of the cultural landscape is associated with the penetration of people into the natural landscape, the settling and adaptation to the needs of the society and its development. Climate creates the decisive influence, specifically the form of extremely high rainfall causing flooding. Adverse impact on the cultural agricultural landscape is mainly the submersion time. This time depends on the configuration of the terrain, its disposition and the existing drainage ditches in the area, ensuring the drainage of the flood to the recipients. Long-lasting floods have stipulated taking measures for the protection of the area from flooding by building dikes and drainage of the flood from the area. Identifying the extent of extreme floods and zones of permanent waterlogging is currently provided by modern technology which allows recording satellite images in different spectral bands. Within the basic distinguishing signs mainly accruing is used and it is possible to track changes of the extent of flooded areas and thus identify problem areas insufficiently protected against long-term flooding. Consequently, it is possible to solve the concept of exploiting such areas to keep them in the structure of PPF or their reclassification in wetland systems with necessary legislative security. The aim of this paper is to show the possibility of using satellite images in identifying the extent of flooding.
Źródło:: Journal of Ecological Engineering; 2017, 18, 3; 31-36
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Forecasting Oil Crops Yields on the Regional Scale Using Normalized Difference Vegetation Index
Autorzy:: Lykhovyd, Pavlo
Powiązania:: https://bibliotekanauki.pl/articles/1839197.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: regression analysis
remote sensing
soybean
sunflower
winter rape
Opis:: Early prediction of crop yields on large cropland areas is of a great importance for operational planning in the agrarian sector of economy and ensuring food security. Large-scale forecasts became possible owing to the introduction of remote sensing technologies in the systems of precision agriculture, providing the information on crops conditions both on a certain field and large croplands. The study on the forecasting of major oil crop yields, namely, sunflower (Helianthus annuus L), winter rape (Brássica nápus) and soybean (Glycine max), on the regional level in Kherson oblast of Ukraine was conducted using historical yielding data and monthly MODIS Terrain NDVI smoothed time series imagery with 250 m resolution of the period from 2012 to 2019. The statistical data on the crop yields were linked to the corresponding values of monthly NDVI to determine the type of inter-relationship and work out the regression models for the oil crops yield prediction based on the remotely sensed vegetation index. The highest correlation between the yields of the oil crops and NDVI with the best prediction accuracy were obtained by using the index values at the period of April for winter rape, July for sunflower, and August for soybean. The developed regression models have reasonable accuracy with the mean absolute percentage errors of predictions reaching 25.23 percent for sunflower, 18.28 percent for winter rape, and 13.24 percent for soybean. The models are easy in use and might be recommended for introduction in theory and practice of precision agriculture.
Źródło:: Journal of Ecological Engineering; 2021, 22, 3; 53-57
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Porównanie metody Gumińskiego i teledetekcji satelitarnej w aspekcie wyznaczania dat początku okresu wegetacyjnego na obszarze Polski
Comparison of Gumiński and satellite remote sensing methods in terms of determining the dates of the onset of the growing season in Poland
Autorzy:: Bartoszek, K.
Siłuch, M.
Powiązania:: https://bibliotekanauki.pl/articles/401083.pdf
Data publikacji:: 2015
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: teledetekcja satelitarna
okres wegetacji
MODIS
EVI
aktywność fotosyntetyczna
remote sensing
growing season
photosynthetic activity
Opis:: Celem niniejszej pracy było porównanie dat początku okresu wegetacyjnego (OW) na obszarze Polski w okresie 2001–2010, które wyznaczono na podstawie dwóch niezależnych metod. Do wyznaczania dat metodą Gumińskiego wykorzystano średnie miesięczne wartości temperatury powietrza z punktów gridowych rozmieszczonych na terenie kraju. Natomiast do określenia dat początku OW metodą teledetekcji satelitarnej wykorzystano dane pochodzące z NASA LP DAAC, które były wynikiem pomiarów wykonywanych przez wielospektralny skaner MODIS umieszczony na satelitach Terra i Aqua. Wykazana została znaczna zgodność średnich terminów początku OW w Polsce wyznaczonych tymi dwoma metodami, co może sugerować istotny wpływ czynnika termicznego na wzrost aktywności fotosyntetycznej roślinności po okresie zimowym. Obydwie metody potwierdziły, że przeciętnie najwcześniej początek OW występuje w południowo-zachodniej części kraju, natomiast najpóźniej w Polsce Północnej i na obszarach górskich.
The aim of the paper is to compare the dates of the onset of the growing season in Poland in the period 2001–2010, which were determined on the basis of two independent methods. The dates determined by Gumiński method based on gridded monthly mean air temperature over Poland area. In turn, satellite data extracted from NASA LP DAAC product, which were the result of measurements performed with multispectral scanner (MODIS) on the Terra and Aqua satellites. It was demonstrated that the average dates of the onset of the growing season in Poland determined by two methods did not differ significantly. It may suggest a significant impact of thermal factor on the increase in the photosynthetic activity of vegetation after the winter months. Both methods confirmed that the earliest average dates of the onset of the growing season occur in the southwestern part of the country, and the latest in northern Poland and in the mountain areas.
Źródło:: Inżynieria Ekologiczna; 2015, 45; 99-105
2081-139X
2392-0629
Pojawia się w:: Inżynieria Ekologiczna
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Sweet Corn Yield Simulation Using Normalized Difference Vegetation Index and Leaf Area Index
Autorzy:: Lykhovyd, Pavlo
Powiązania:: https://bibliotekanauki.pl/articles/124254.pdf
Data publikacji:: 2020
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: direct measurement
mathematical model
regression analysis
remote sensing
sweet corn
yield prediction
Opis:: The authors determined the accuracy and reliability of yielding models by using the values of two differently obtained indices – the leaf area index (LAI) obtained through direct surface measurements, and the normalized difference vegetation index (NDVI) obtained through spatial remote sensing of crops. The study based on the drip-irrigated sweet corn yielded the data obtained in the field experiment held in the semi-arid climate on darkchestnut soil in the South of Ukraine. The suitability of the LAI and NDVI for the simulation of sweet corn yields was estimated by the regression analysis of the yielding data by correlation (R) and determination (R²) coefficients. Additionally, mathematical models for the crop yields estimation based on the regression analysis were developed. It was determined that LAI is a more suitable index for the crop yield prediction: the R² value was 0.92 and 0.94 against 0.85 for the NDVI-based models.I It was determined that it is better to use the LAI values obtained at the stage of flowering, when R² averaged to 0.94, and the NDVI-based models does not depend on the crop stage (the R² was 0.85 both for the flowering and ripening stages of the plant development). The combined NDVI-LAI model showed that there is no necessity in the complication of the LAI-based model through introduction of the remotely sensed index because of insignificant improvement in the performance (R² was 0.94 and 0.92).
Źródło:: Journal of Ecological Engineering; 2020, 21, 3; 228-236
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Characteristics of Selected Peatland Uses and Soil Moisture Based on TVDI
Autorzy:: Holidi, -
Armanto, M. Edi
Damiri, Nurhayati
Putranto, Dinar Dwi Anugerah
Powiązania:: https://bibliotekanauki.pl/articles/952455.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: remote sensing
land use
drought
fire
South Sumatra
Opis:: The conversion of peatland from forest to non-forest causes environmental damage and increases high land dryness. Mapping of peatland based on dryness is very important to control and prevent fires. This study aims at characterizing peatland based on the level of temperature vegetation dryness index (TVDI) and evaluating the correlation between TVDI value and soil moisture. The research was conducted in August 2018 during the dry season. The area of research located in peat hydrological unit of Sibumbung River – Batok River in Ogan Komering Ilir (OKI) District of South Sumatra Province covering 63,427 ha area that consists of various land uses. The result showed that extreme wet category is found in water bodies and secondary forests that have high density, moderate wet is found in paddy fields and grass, normal area is found in the area covered by low-density trees, moderate dry is found in shrubs and oil palm plantations with good management and extreme dry areas is found in grasses and oil palm with poor cultivation management. There is a correlation between the TVDI value to the soil moisture on 0–10 cm and 10–20 cm and 20–30 cm depth.
Źródło:: Journal of Ecological Engineering; 2019, 20, 4; 194-200
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Soil Salinity Classification Using Machine Learning Algorithms and Radar Data in the Case from the South of Kazakhstan
Autorzy:: Merembayev, Timur
Amirgaliyev, Yedilkhan
Saurov, Sultan
Wójcik, Waldemar
Powiązania:: https://bibliotekanauki.pl/articles/2202157.pdf
Data publikacji:: 2022
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: environmental correlation
soil salinity
machine learning
remote sensing
Opis:: Soil salinity is one of the major impact factors on agriculture in the South of Kazakhstan. Prediction and estimation of soil salinity before planting a season usually helps to plan for the leaching of the salt. In the paper, satellite data such as radar data and machine learning algorithms, were used to classify soil salinity. Numerical results were presented for the Turkestan region, which contains more than 102 points. The machine learning algorithms, including Gaussian Process, Decision Tree, and Random Forest, were compared. The evaluation of the model score was realized by using metrics, such as accuracy, Recall, and f1. In addition, the influence of the dataset features on the classification was investigated using machine learning algorithms. The research results showed that the Gaussian Process model has the best score among considered algorithms. In addition, the results are consistent with the outcome of the Shapley Additive exPlanations (SHAP) framework.
Źródło:: Journal of Ecological Engineering; 2022, 23, 10; 61--67
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environment using Spectral Data and Gis Tools
Autorzy:: Grzywna, H.
Dąbek, P. B.
Olszewska, B.
Powiązania:: https://bibliotekanauki.pl/articles/123280.pdf
Data publikacji:: 2018
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: drought
soil moisture
NDVI
Sentinel-2
satellite data
remote sensing
Opis:: The studies on agricultural droughts require long-term atmospheric, hydrological and meteorological data. On the other hand, today, the possibilities of using spectral data in environmental studies are indicated. The development of remote sensing techniques, increasing the spectral and spatial resolution of data allows using remote sensing data in the study of water content in the environment. The paper presents the results of the analysis of moisture content of soil-plant environment in the lowland areas of river valley using the spectral data from Sentinel-2. The analyses were conducted between February and November 2016. The spectral data were used to calculate the Normalize Differential Vegetation Index (NDVI) which provided the information about the moisture content of the soil-plant environment. The analyses were performed only on grasslands, on 22 objects located in the research area in the Oder river valley between Malczyce and Brzeg Dolny, Poland. The NDVI values were correlated with the hydrological and meteorological parameters. The analyses showed spatial and temporal variability of the moisture conditions in the soil-plant environment showed by the NDVI variability and existence some relationships between the climatic and spectral indices characterizing the moisture content in the environment.
Źródło:: Journal of Ecological Engineering; 2018, 19, 6; 56-64
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Two Decades (2000–2020) Measuring Urban Sprawl Using GIS, RS and Landscape Metrics: a Case Study of Municipality of Prishtina (Kosovo)
Autorzy:: Berila, Albert
Isufi, Florim
Powiązania:: https://bibliotekanauki.pl/articles/1838373.pdf
Data publikacji:: 2021
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: GIS
remote sensing
landscape metrics
urban sprawl
municipality of Prishtina
Opis:: Since the appearance on Earth, human has been constantly operating in nature, exploiting its riches, but also adapting it to its own needs. Both developing and developed countries are constantly concerned about the urbanization process. Urbanization, in order to be positive, must be developed correctly. If such a thing does not happen, then this development will negatively affect both the environment and human health. In order to develop adequate strategies and policies for the most sustainable and effective land use management, it is necessary to quantify, monitor, determine the factors that have influenced this change in land use and the spread mapping of the urban environment. In this study, Landsat satellite images were used to determine the spatial-temporal characteristics of the urban sprawl environment in the Municipality of Prishtina for a period of 20 years (2000-2020). To map the land cover for Prishtina from 2000 to 2020, the Supervised maximum likelihood classification was used using the Landsat ETM + and OLI data archives in ArcGIS 10.5 software. Using landscape metrics and detection techniques after the classification of satellite images, enabled and assisted in the evaluation and analysis of trends and patterns of urban sprawl. The determination of the changes and the analysis made revealed that during the period 2000-2020, in Prishtina, there was an increase of the built areas by 16.46 km2 at the expense of the unbuilt areas. That there has been an increase in urban areas was also confirmed by the results of landscape metrics.
Źródło:: Journal of Ecological Engineering; 2021, 22, 6; 114-125
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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