Essays about: "Optical remote sensing"

Showing result 1 - 5 of 28 essays containing the words Optical remote sensing.

  1. 1. Monitoring deforestation in the Serranía de Chiribiquete in northern Colombian Amazon using time series analysis of satellite data

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Yuyang Qian; [2023]
    Keywords : Physical Geography and Ecosystem analysis; CCDC; Forest loss; Landsat; Sentinel-1; Change detection; NNP; FARC; Earth and Environmental Sciences;

    Abstract : Deforestation monitoring is of significant importance for the ecosystem, climate change,and policy-making. The availability of optical and synthetic aperture radar (SAR) satellite remote sensing images, along with the development of time series change detection methods, has contributed to the increasing popularity of time series analysis in forest disturbance monitoring. READ MORE

  3. 2. Water quality monitoring with Sentinel 2 in small watercourses : Investigating the measurability of phosphorus using proxy data

    University essay from Stockholms universitet/Institutionen för naturgeografi

    Author : Caroline Morin; [2023]
    Keywords : Optical remote sensing; Sentinel 2; Phosphorus; Total suspended matter; Turbidity;

    Abstract : Inland water has for a long time showed vast stress due to eutrophication, mainly caused by increased levels of phosphorus. Applying remote sensing as a tool for monitoring water parameters has long been used. READ MORE

  4. 3. 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

  5. 4. Development of a Level-0 Geoprocessing Platform for a Multispectral Remote Sensing Payload

    University essay from KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanik

    Author : Sergio Santiago Bernabeu Peñalba; [2022]
    Keywords : Infrared imagery; VIS; NIR; LWIR; geoprocessor; geolocation; quaternions; Aistech Space; image processing; ORB; RANSAC; Sentinel; Landsat; Infraröda bilder; VIS; NIR; LWIR; geoprocessor; geolokalisering; kvarternioner; Aistech Space; bildbehandling; ORB; RANSAC; Sentinel; Landsat;

    Abstract : This thesis presented an overview of the development of a geolocating algorithm as part of a geoprocessor for raw satellite imagery. This algorithm was devised for and limited by the specifications of a state-of-the-art multispectral telescope designed by Aistech Space, hosted onboard the Guardian spacecraft, which will observe Earth through the visible, near infrared, and thermal infrared bands of the electromagnetic spectrum. READ MORE

  6. 5. Exploring Diversity of Spectral Data in Cloud Detection with Machine Learning Methods : Contribution of Near Infrared band in improving cloud detection in winter images

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

    Author : Nakita Sunil Oza; [2022]
    Keywords : Remote sensing; Multispectral imaging; Cloud detection; Data diversity; Deep learning; Fjärranalys; Multispektral bildbehandling; Molndetektion; Datadiversitet; Djupinlärning;

    Abstract : Cloud detection on satellite imagery is an essential pre-processing step for several remote sensing applications. In general, machine learning based methods for cloud detection perform well, especially the ones based on deep learning as they consider both spatial and spectral features of the input image. READ MORE