2018
DOI: 10.3390/rs10010105
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Disaggregation of Landsat-8 Thermal Data Using Guided SWIR Imagery on the Scene of a Wildfire

Abstract: Thermal data products derived from remotely sensed data play significant roles as key parameters for biophysical phenomena. However, a trade-off between spatial and spectral resolutions has existed in thermal infrared (TIR) remote sensing systems, with the end product being the limited resolution of the TIR sensor. In order to treat this problem, various disaggregation methods of TIR data, based on the indices from visible and near-infrared (VNIR), have been developed to sharpen the coarser spatial resolution … Show more

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Cited by 18 publications
(4 citation statements)
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“…Band 5, the Near Infrared (NIR) band, plays a crucial role in assessing vegetation moisture content, contributing to a comprehensive analysis of vegetation [27]. Bands 6 and 7, Shortwave Infrared 1 and Shortwave Infrared 2, respectively, delve into studies related to geology and vegetation, with SWIR 2 having the capability to penetrate through atmospheric conditions [28]. Collectively, these seven bands provide a diverse dataset enabling applications such as land cover classification, vegetation monitoring and the detection of environmental changes.…”
Section: Phase 2: Novel Data Collection and Spectral Bandsmentioning
confidence: 99%
“…Band 5, the Near Infrared (NIR) band, plays a crucial role in assessing vegetation moisture content, contributing to a comprehensive analysis of vegetation [27]. Bands 6 and 7, Shortwave Infrared 1 and Shortwave Infrared 2, respectively, delve into studies related to geology and vegetation, with SWIR 2 having the capability to penetrate through atmospheric conditions [28]. Collectively, these seven bands provide a diverse dataset enabling applications such as land cover classification, vegetation monitoring and the detection of environmental changes.…”
Section: Phase 2: Novel Data Collection and Spectral Bandsmentioning
confidence: 99%
“…The OLI has 30-m resolution for surface reflectance and the TIRS has 100 m spatial resolution for brightness temperature (Table 1). The United States Geological Survey processes TIR data with 30 m spatial resolution through resampling [24]. To calculate the variables of Landsat-8 data, we used L2 data and top-of-canopy reflectance data, referring to the surface reflectance data-applied atmospheric correction of OLI data used to remove atmospheric effects, which is important for land surface observations [25,26].…”
Section: Landsat-8 Datamentioning
confidence: 99%
“…Podatki daljinskega zaznavanja imajo kljub številnim prednostim, kot je na primer zajemanje podatkov večjega območja (regije), tudi slabosti (Zawadzka, Corstanje, Harris in Truckell 2019). Ena izmed največjih težav omenjenih podatkov je prostorska resolucija termičnih kanalov, ki je običajno nezadostna za izdelavo kvalitetnih ocen na lokalni ravni (Cho, Kim in Kim 2018). To omejitev lahko zaobidemo z uporabo statistične metode izboljševanja prostorske ločljivosti (ang.…”
Section: Uvodunclassified