Sökning: "Landsat"

Visar resultat 6 - 10 av 91 uppsatser innehållade ordet Landsat.

  1. 6. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Lasse Harkort; [2022]
    Nyckelord :dissolved organic carbon; machine learning; remote sensing; inland waters; water quality; open source data; Earth and Environmental Sciences;

    Sammanfattning : This thesis presents the first attempt to estimate Dissolved Organic Carbon (DOC) in inland waters over a large-scale area using satellite data and machine learning (ML) methods. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were tested to retrieve DOC using a filtered version of the recently published open source AquaSat dataset with more than 16 thousand samples across the continental US matched with satellite data from Landsat 5, 7 and 8 missions. LÄS MER

  2. 7. Spatiotemporal changes in Gothenburg municipality's green space, 1986 to 2019

    Master-uppsats, Göteborgs universitet/Institutionen för geovetenskaper

    Författare :Kristin Blinge; [2021-04-01]
    Nyckelord :NDVI; multitemporal change analysis; incremental change; urbanization;

    Sammanfattning : As the world’s population is becoming increasingly more urban the infrastructure expands to accommodate the inhabitants’ needs. In a dense urban environment green space has an important function since it provides vital ecosystem services, contributes to recreational and cultural values and is essential for biodiversity. LÄS MER

  3. 8. Carta ex Machina: Testing object-based machine learning and unsupervised classification in land use change detection mapping in the semi-arid governorate of Sidi Bouzid, Tunisia

    Kandidat-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Kristian Emil Havnsgaard Paludan; [2021]
    Nyckelord :Change detection; Land use mapping; LANDSAT MSS; LANDSAT TM; GEOBIA; Random Forest classification; ISODATA cluster classification; Object-based classification; Semi-arid agriculture; Irrigation mapping; Earth and Environmental Sciences;

    Sammanfattning : Sidi Bouzid, Tunisia is an inland governorate in Tunisia that has undergone a rapid agricultural and urban development since the Tunisian independence in 1952 from being a rural and largely nomadic region into a hub of irrigated agriculture. In 2010 Mohamed Bouazizi sparked the Tunisian revolution by lighting himself on fire int he city of Sidi Bouzid, with some blaming the inequality and water scarcity created by this rapid expansion in the irrigation farming as an important cause (Bayat, 2017; Malka, 2018). LÄS MER

  4. 9. Topographic controls of drought impact on Swedish primary forests

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Johanna Asch; [2021]
    Nyckelord :Physical geography; ecosystem analysis; primary forest; boreal forest; drought impact; topography; drainage; climate change; random forest; terrain index; Earth and Environmental Sciences;

    Sammanfattning : Anthropogenic climate change has increased the frequency of extreme drought events and leads to “hotter” droughts. Topography controls plant available water and site-specific climatic conditions. Drought sensitivity may therefore vary over short distances between wet and dry locations of the landscape. LÄS MER

  5. 10. Impact of fire and frost drought events on vegetation greenness and albedo in Subarctic Scandinavia

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Elin Backström; [2021]
    Nyckelord :Physical Geography and Ecosystem analysis; Vegetation Greenness; Albedo; Fire; Frost Drought; Earth and Environmental Sciences;

    Sammanfattning : With climate change, the frequency in climate extremes such as drought, heavy rainfalls, and extreme temperatures is predicted to increase. These extremes can potentially stress and damage vegetation over large areas, leading to altered carbon cycle, vegetation greenness, albedo, and shifted species composition. LÄS MER