scholarly journals Extraction of vegetation from Landsat satellite images using rationalized Haar wavelet algorithm

2020 ◽  
Vol 12 (2) ◽  
pp. 45-56
Author(s):  
Kazem Aliabadi ◽  
omid baghani
Keyword(s):  
Satellite Images ◽  
Haar Wavelet ◽  
Rationalized Haar Wavelet ◽  
Landsat Satellite ◽  
Wavelet Algorithm

Multitemporal distribution analysis of Dodonaea viscosa (L.) Jacq. by remote sensing in Durango, Mexico

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Marco, A. Márquez-Linares ◽  
Jonathan G. Escobar--Flores ◽  
Sarahi Sandoval- Espinosa ◽  
Gustavo Pérez-Verdín
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Design Methodology ◽  
Supervised Classification ◽  
Satellite Images ◽  
Ground Cover ◽  
Distribution Analysis ◽  
Dodonaea Viscosa ◽  
Artificial Neural ◽  
Landsat Satellite

Objective: to determine the distribution of D. viscosa in the vicinity of the Guadalupe Victoria Dam in Durango, Mexico, for the years 1990, 2010 and 2017.Design/Methodology/Approach: Landsat satellite images were processed in order to carry out supervised classifications using an artificial neural network. Images from the years 1990, 2010 and 2017 were used to estimate ground cover of D. viscosa, pastures, crops, shrubs, and oak forest. This data was used to calculate the expansion of D. viscosa in the study area.Results/Study Limitations/Implications: the supervised classification with the artificial neural network was optimal after 400 iterations, obtaining the best overall precision of 84.5 % for 2017. This contrasted with the year 1990, when overall accuracy was low at 45 % due to less training sites (fewer than 100) recorded for each of the land cover classes.Findings/Conclusions: in 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, and based on the distribution of D. viscosa, it is likely that in a few years it will have the ability to invade half the study area, occupying agricultural, forested, and shrub areas

EVALUATION OF A MODEL TO ESTIMATE NET RADIATION OVER A DRIP-IRRIGATED OLIVE ORCHARD USING LANDSAT SATELLITE IMAGES

2014 ◽  
pp. 309-314 ◽  
Author(s):  
S. Ortega-Farías ◽  
S. Ortega-Salazar ◽  
R. Aguilar ◽  
D. De la Fuente ◽  
F. Fuentes
Keyword(s):  
Satellite Images ◽  
Net Radiation ◽  
Olive Orchard ◽  
Landsat Satellite

scholarly journals Cambios en el paisaje de menorca desde 1975 hasta 2010 mediante teledetección

2021 ◽  
Vol 3 (5) ◽  
pp. 3305-3318
Author(s):  
Emilio Ramírez-Juidías ◽  
Francisco Víquez-Urraco
Keyword(s):  
United States ◽  
Satellite Images ◽  
Climatic Factors ◽  
The United States ◽  
Strong Increase ◽  
Tourist Attraction ◽  
Territorial Development ◽  
Landscape Development ◽  
Landsat Satellite

La isla de Menorca, Reserva de la Biosfera, ha originado una fuerte atracción turística a consecuencia de su gran riqueza paisajística. En este estudio, se analizaron 265 imágenes Landsat procedentes del United States Geological Service para el periodo 1975-2010, todas examinadas y clasificadas en un determinado lapso de tiempo con el fin de poder caracterizar correctamente el desarrollo territorial espacial y temporalmente.  Los resultados muestran como entre 1975 y 1990 no existe desarrollo del paisaje. Entre 1990 y 2000, hay un gran aumento de la vegetación a consecuencia de la protección recibida por la Unesco. En el periodo 2000-2010, es evidente el efecto del clima en el desarrollo del paisaje.   The island of Menorca, Reserve of the Biosphere, has created a strong tourist attraction due to its rich landscape. In this research, 265 Landsat satellite images from the United States Geological Service were analyzed or the 1975 to 2010 eriod, each of which was examined and classified in a certain period of time in order to characterize right way the territorial development both spatially and temporally.  The results show how between 1975 and 1990 there is virtually no landscape development. Between 1990 and 2000, there is a strong increase of vegetation as a result of the protection received by UNESCO. In the period 2000-2010, it was evident the effect of climatic factors in the landscape development.

scholarly journals Land area increase in Ukrainian part of the Danube delta

2021 ◽  
Author(s):  
V. M. Starodubtsev ◽  
◽  
M. M. Ladyka ◽  
Keyword(s):  
Land Cover ◽  
Satellite Images ◽  
Extreme Event ◽  
Relative Equilibrium ◽  
Danube River ◽  
Danube Delta ◽  
Land Area ◽  
Area Increase ◽  
Landsat Satellite ◽  
Quantitative Indicators

The quantitative indicators of land growth in the Ukrainian part of the Danube delta are considered. Comparison of Landsat satellite images in three key areas of the delta showed that for the period 1975-2020 the area of wetlands at the mouth of the Сhilia channel increased by 1448 hectares due to the accumulation of sediments between the Starostambul and Limba branches and their overgrowth with vegetation. In the area of the Bystroe channel, the area of new lands increased by 1037 hectares due to the artificial deepening of this channel for the Ukrainian ships passage into the Danube River and the deposition of sediments along the coast. A slightly smaller increase in land cover (797 ha) was found in the northern part of the coast of the Ukrainian part of the delta, where saline and carbonate soils are formed. In the future, active land growth is expected in the Musura bay between the mouths of the Starostambul and Sulina branches, ie at the contact of Ukraine and Romania. Some changes in these parameters are expected after a powerful flood in 2021, which will become known after the establishment of a relative equilibrium between the processes of accumulation and erosion after this extreme event.

scholarly journals Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Roberto O. Chávez ◽  
Verónica F. Briceño ◽  
José A. Lastra ◽  
Daniel Harris-Pascal ◽  
Sergio A. Estay
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Microbial Composition ◽  
Mountain Areas ◽  
Pixel Resolution ◽  
Temperature Changes ◽  
Soil Microbial ◽  
Landsat Satellite

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence > 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (>2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

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