Detecting geothermal anomalies using Landsat 8 thermal infrared remotely sensed data

Gemitzi, Alexandra; Dalampakis, Paschalis; Falalakis, G.

doi:10.1016/j.jag.2020.102283

Cited by 23 publications

(12 citation statements)

References 19 publications

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“…Within the study period (June-October), NDVI was produced with a linear interpolation between observational dates, and therefore NDVI values were retrieved specifically for those dates when mosquito samples were taken and counted. Concerning Landsat 8 LST, no ready-to-use product exists; therefore, it was computed using the methodology described in [27,28]. Due to the fact that the Landsat 8 acquisitions were not available for the desirable days, MODIS daytime LST (MOD11A1v006 product) at 1 km spatial resolution was used to obtain information on the temporal trend of LST between the Landsat 8 acquisition dates (Figure 2).…”

Section: Mosquito Dna Barcodingmentioning

confidence: 99%

Applying Remotely Sensed Environmental Information to Model Mosquito Populations

et al. 2021

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Vector borne diseases have been related to various environmental parameters and environmental changes like climate change, which impact their propagation in time and space. Remote sensing data have been used widely for monitoring environmental conditions and changes. We hypothesized that changes in various environmental parameters may be reflected in changes in mosquito population size, thus impacting the temporal and spatial patterns of vector diseases. The aim of this study is to analyze the effect of environmental variables on mosquito populations using the remotely sensed Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from Landsat 8, along with other factors, such as altitude and water covered areas surrounding the examined locations. Therefore, a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) model was developed and tested for its ability to predict mosquito populations. The model was applied in NE Greece using mosquito population data from 17 locations where mosquito traps were placed from June to October 2019. All performance metrics indicated a high predictive ability of the model. LST was proved to be the factor with the highest relative importance in the prediction of mosquito populations, whereas the developed model can predict mosquito populations 13 days ahead to allow a substantial window for appropriate control measures.

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Section: Mosquito Dna Barcodingmentioning

confidence: 99%

Applying Remotely Sensed Environmental Information to Model Mosquito Populations

et al. 2021

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“…The Land Surface Temperature (LST) obtained by remote sensing for an entire city seems better suited to describing this variability than the air temperature measured by a relatively coarse network of local weather stations. LST is not the same as air temperature but is closely related to the near-surface air temperature; it is considered a primary factor affecting the energy exchange of the near-surface layers of the atmosphere (Wang et al 2019;Gemitzi et al 2021). It accurately characterizes the thermal environment at the city scale (Guo et al 2016), and it is widely used to assess UHI effect.…”

Section: Introductionmentioning

confidence: 99%

Green or blue bodies to mitigate the urban heat island? The case of a compact European city

Kirschner

Moravec

Macků

2023

Preprint

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An understanding of the complex contributions of several factors to an urban heat island is crucial for the assessment of the impacts of planning on the thermal conditions within cities. This paper investigates the effects of various factors on the land surface temperature (LST) in three zones of Prague, the capital of the Czech Republic. The investigated factors include the normalized diﬀerence vegetation index (NDVI), proximity to lakes larger than 1000 m2 (Lakes), proximity to the river (River), building coverage (BC), and building height (BH). Their interrelationships are explored in a square grid of 30 × 30 m using Landsat-8 data on LST measurements and multiple regression models. The results imply that NDVI significantly reduces LST, followed by the River if within 200 m of it, while the effect of Lakes is negligible. The effect of BH is generally low, though it often also reduces the LST in the outer compact city. BC is a predominant factor in the city, generating a warming effect, which increases with the city’s compactness. The main planning implications are to base urban heat island mitigation strategies on compensating for building coverage with live and dense green bodies in the compact city, promoting vertical development.

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“…Due to the difficulty in quantitatively measuring the surface temperature due to pixel saturation problems or atmospheric attenuation, some studies are based on determining pixel value thresholds by isolating the background temperature found in each image. The anomalous pixel value may be above average plus a standard deviation (σ), as in [ 24 ], above average +2σ [ 25 ], or with multiple thresholds [ 26 ], since a maximum temperature in one image can represent a normality scenario in another [ 16 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of Geothermal Anomalies in Hydrothermal Systems Using ASTER Data: The Caldeiras da Ribeira Grande Case Study (Azores, Portugal)

Uchôa

Viveiros

Tiengo

et al. 2023

Sensors

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Current-day volcanic activity in the Azores archipelago is characterized by seismic events and secondary manifestations of volcanism. Remote sensing techniques have been widely employed to monitor deformation in volcanic systems, map lava flows, or detect high-temperature gas emissions. However, using satellite imagery, it is still challenging to identify low-magnitude thermal changes in a volcanic system. In 2010, after drilling a well for geothermal exploration on the northern flank of Fogo Volcano on São Miguel Island, a new degassing and thermal area emerged with maximum temperatures of 100 °C. In the present paper, using the ASTER sensor, we observed changes in the near-infrared signals (15 m spatial resolution) six months after the anomaly emerged. In contrast, the thermal signal (90 m spatial resolution) only changed its threshold value one and a half years after the anomaly was recognized. The results show that wavelength and spatial resolution can influence the response time in detecting changes in a system. This paper reiterates the importance of using thermal imaging and high spatial resolution images to monitor and map thermal anomalies in hydrothermal systems such as those found in the Azores.

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Detecting geothermal anomalies using Landsat 8 thermal infrared remotely sensed data

Cited by 23 publications

References 19 publications

Applying Remotely Sensed Environmental Information to Model Mosquito Populations

Applying Remotely Sensed Environmental Information to Model Mosquito Populations

Green or blue bodies to mitigate the urban heat island? The case of a compact European city

Detection of Geothermal Anomalies in Hydrothermal Systems Using ASTER Data: The Caldeiras da Ribeira Grande Case Study (Azores, Portugal)

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