Essays about: "Atmospheric sensing"

Showing result 1 - 5 of 29 essays containing the words Atmospheric sensing.

1. 1. The impact of CO2 fertilisation on foliage in West and East Africa

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Gaetane Demyttenaere; [2023]
   Keywords : Physical geography and ecosystem analysis; CO2 fertilisation; semi-arid ecosystems; remote sensing; Normalised Difference Vegetation Index; Earth and Environmental Sciences;

   Abstract : 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. READ MORE

3. 2. Spatial downscaling of gridded soil moisture products using optical and thermal satellite data: the effects of using different vegetation indices

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Tómas Halldórsson Alexander; [2023]
   Keywords : Physical Geography and Ecosystem Analysis; Remote Sensing; Soil moisture; Downscaling; Vegetation index; Earth and Environmental Sciences;

   Abstract : 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. READ MORE

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

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

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

   Abstract : 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. READ MORE

5. 4. Evaluating forest wildfire effect on tree increment patterns for boreonemoral forests in Sweden: A pilot study using remote sensing

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Joanna Eaton; [2022]
   Keywords : Physical Geography and Ecosystem analysis; Remote sensing; Sentinel-2A; Forest wildfires; dNBR; NDVI; dNDVI; Dendrochronology; Atmospheric science and biogeochemical cycles; Earth and Environmental Sciences;

   Abstract : 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. READ MORE

6. 5. Data-driven Dynamic Baseline Calibration Method for Gas Sensors

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Cheng Yang; [2021]
   Keywords : CO2 gas sensing; drift; dynamic baseline calibration; time series analysis; data-driven modeling; clustering; classification; CO2 gasavkänning; drift; dynamisk baslinjekalibrering; tidsserieanalys; datadriven modellering; kluster; klassificering;

   Abstract : Automatic Baseline Correction is the state-of-the-art calibration method of non-dispersive infrared CO2 sensing, which is the standard CO2 gas monitoring method. In this thesis, we improve it by introducing the dynamic baseline based on environmental data. READ MORE