Sökning: "Atmospheric sensing"
Visar resultat 1 - 5 av 32 uppsatser innehållade orden Atmospheric sensing.
1. The impact of CO2 fertilisation on foliage in West and East Africa
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Anthropogenic impact on terrestrial ecosystems continues to grow as we further enhance atmospheric Carbon Dioxide (CO₂) concentrations. The changing climatic conditions and direct influence of CO₂ on vegetation has a big impact on ecosystem functions. LÄS MER
2. Spatial downscaling of gridded soil moisture products using optical and thermal satellite data: the effects of using different vegetation indices
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Soil moisture (SM) plays an important role in the exchange of heat and water between the surface and atmosphere, impacting water and energy cycles and the climate. Satellite remote sensing offers a global-scale estimation of SM; however, the coarse resolutions of satellite SM products, typically ranging from 25-50 km, are unsuitable for regional analysis. LÄS MER
3. Tidig detektering avgranbarkborreangrepp med hjälp avfjärranalys via Sentinel-2
Kandidat-uppsats, Högskolan i Gävle/DatavetenskapSammanfattning : Granbarkborre är en av Sveriges mest destruktiva skadeinsekter som angriper granskog. Insekten har medfört förödande konsekvenser för granskog, framför allt sedan2018 där stora arealer granskog nästan har eliminerats. Insekten trivs i varmt ochtorrt klimat. LÄS MER
4. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : 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
5. Evaluating forest wildfire effect on tree increment patterns for boreonemoral forests in Sweden: A pilot study using remote sensing
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : The release of anthropogenic greenhouse gases (GHGs) has substantially increased the global mean surface air temperature. Increases in global mean surface air temperature will lead to warmer and drier conditions, promoting more frequent, long-lasting, intense forest wildfires. LÄS MER