Modeling MODIS LST at European scale

Bussalleu, Alonso; Hoogh, Kees de; Hoek, Gerard; Kloog, Itai

doi:10.1289/isee.2022.p-0304

Cited by 1 publication

(1 citation statement)

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“…Furthermore, sensors in the visible region are only utilized during the day as reflectance is the principal technique used to detect snow and ice. It is therefore limited in its ability to observe snow and sea ice due to the nature of its optical sensors (Olsson et al, 2016;Bussalleu et al, 2022).…”

Section: Modis Datamentioning

confidence: 99%

A case study about the forest fire occurred on 05 July 2021 over Khenchela province, Algeria, using space-borne remote sensing

Guehaz,

Sivakumar

2023

Front. Remote Sens.

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In this study, space-borne remote sensing (Landsat-8, MODIS) was employed to evaluate the effects of forest fires occurring on 05 July 2021, over Khenchela province, Algeria. Our objective is to understand the severity of damage caused by the fire and its implications for vegetation and land cover. Utilizing the Normalized Difference Vegetation Index (NDVI) from MODIS data and Landsat-8 imagery, we report changes in vegetation health and land cover. To identify areas affected by forest fires and evaluate the severity of damage, the Normalized Burn Ratio (NBR) and Differenced Normalized Burn Ratio (dNBR) were calculated. Analysis showed that −1825.11 ha (1.21%) of the total area experienced severe burns, 3843.54 ha (2.54%) moderate to high severity burns, 3927.97 ha (2.59%) moderate to low severity burns and 9864.45 ha (6.51%) low severity burns. The area covered by vegetation decreased from 2014 to 2021, indicating a negative trend in vegetation cover over the study period.

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Section: Modis Datamentioning

confidence: 99%