Relevant bibliographies by topics / Land Surface Temperatures

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Land Surface Temperatures'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Land Surface Temperatures"

1

Garratt, J. R. "Extreme Maximum Land Surface Temperatures." Journal of Applied Meteorology 31, no. 9 (1992): 1096–105. http://dx.doi.org/10.1175/1520-0450(1992)031<1096:emlst>2.0.co;2.

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Naughton, Joseph, and Walter McDonald. "Evaluating the Variability of Urban Land Surface Temperatures Using Drone Observations." Remote Sensing 11, no. 14 (2019): 1722. http://dx.doi.org/10.3390/rs11141722.

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Urbanization and climate change are driving increases in urban land surface temperatures that pose a threat to human and environmental health. To address this challenge, we must be able to observe land surface temperatures within spatially complex urban environments. However, many existing remote sensing studies are based upon satellite or aerial imagery that capture temperature at coarse resolutions that fail to capture the spatial complexities of urban land surfaces that can change at a sub-meter resolution. This study seeks to fill this gap by evaluating the spatial variability of land surface temperatures through drone thermal imagery captured at high-resolutions (13 cm). In this study, flights were conducted using a quadcopter drone and thermal camera at two case study locations in Milwaukee, Wisconsin and El Paso, Texas. Results indicate that land use types exhibit significant variability in their surface temperatures (3.9–15.8 °C) and that this variability is influenced by surface material properties, traffic, weather and urban geometry. Air temperature and solar radiation were statistically significant predictors of land surface temperature (R2 0.37–0.84) but the predictive power of the models was lower for land use types that were heavily impacted by pedestrian or vehicular traffic. The findings from this study ultimately elucidate factors that contribute to land surface temperature variability in the urban environment, which can be applied to develop better temperature mitigation practices to protect human and environmental health.
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Ignatov, A., and G. Gutman. "Diurnal cycles of land surface temperatures." Advances in Space Research 22, no. 5 (1998): 641–44. http://dx.doi.org/10.1016/s0273-1177(97)01125-3.

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Inamdar, Anand K., and Andrew French. "Disaggregation of GOES land surface temperatures using surface emissivity." Geophysical Research Letters 36, no. 2 (2009): n/a. http://dx.doi.org/10.1029/2008gl036544.

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Kleidon, Axel, and Maik Renner. "An explanation for the different climate sensitivities of land and ocean surfaces based on the diurnal cycle." Earth System Dynamics 8, no. 3 (2017): 849–64. http://dx.doi.org/10.5194/esd-8-849-2017.

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Abstract. Observations and climate model simulations consistently show a higher climate sensitivity of land surfaces compared to ocean surfaces. Here we show that this difference in temperature sensitivity can be explained by the different means by which the diurnal variation in solar radiation is buffered. While ocean surfaces buffer the diurnal variations by heat storage changes below the surface, land surfaces buffer it mostly by heat storage changes above the surface in the lower atmosphere that are reflected in the diurnal growth of a convective boundary layer. Storage changes below the surface allow the ocean surface–atmosphere system to maintain turbulent fluxes over day and night, while the land surface–atmosphere system maintains turbulent fluxes only during the daytime hours, when the surface is heated by absorption of solar radiation. This shorter duration of turbulent fluxes on land results in a greater sensitivity of the land surface–atmosphere system to changes in the greenhouse forcing because nighttime temperatures are shaped by radiative exchange only, which are more sensitive to changes in greenhouse forcing. We use a simple, analytic energy balance model of the surface–atmosphere system in which turbulent fluxes are constrained by the maximum power limit to estimate the effects of these different means to buffer the diurnal cycle on the resulting temperature sensitivities. The model predicts that land surfaces have a 50 % greater climate sensitivity than ocean surfaces, and that the nighttime temperatures on land increase about twice as much as daytime temperatures because of the absence of turbulent fluxes at night. Both predictions compare very well with observations and CMIP5 climate model simulations. Hence, the greater climate sensitivity of land surfaces can be explained by its buffering of diurnal variations in solar radiation in the lower atmosphere.
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Tahooni, A., and A. A. Kakroodi. "RELATIONSHIPS BETWEEN LAND USE/LAND COVER AND LAND SURFACE TEMPERATURE IN TABRIZ FROM 2000 TO 2017." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 19, 2019): 1041–44. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-1041-2019.

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Abstract. Urban Heat Island (UHI) refers to the development of higher urban temperatures of an urban area compared to the temperatures of surrounding suburban and rural areas. Highly reflective urban materials to solar radiation present a significantly lower surface temperature and contribute to reducing the sensible heat released in the atmosphere and mitigating the urban heat island. Many studies of the UHI effect have been based on Land Surface Temperature (LST) measurements from remote sensors. The remotely sensed UHI has been termed the surface urban heat island (SUHI) effect. This study examines Tabriz city land use/land cover (LULC) and LST changes using Landsat satellite images between 2000 and 2017. Maximum likelihood classification and single channel methods were used for LULC classification and LST retrieval respectively. Results show that impervious surface has increased 13.79% and bare soil area has decreased 16.2%. The results also revealed bare soil class LST after a constant trend become increasing. It also revealed the impervious surface LST has a decreasing trend between 2000 and 2011 and has a little change. Using materials that have low absorption and high reflectance decrease the effect of heat island considerably.
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Favrichon, Samuel, Catherine Prigent, and Carlos Jiménez. "A Method to Downscale Satellite Microwave Land-Surface Temperature." Remote Sensing 13, no. 7 (2021): 1325. http://dx.doi.org/10.3390/rs13071325.

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High-spatial-resolution land-surface temperature is required for several applications such as hydrological or climate studies. Global estimates of surface temperature are available from sensors observing in the infrared (IR), but without ‘all-weather’ observing capability. Passive microwave (MW) instruments can also be used to provide surface-temperature measurements but suffer from coarser spatial resolutions. To increase their resolution, a downscaling methodology applicable over different land environments and at any time of the day is proposed. The method uses a statistical relationship between clear sky-predicting variables and clear-sky temperatures to estimate temperature patterns that can be used in conjunction with coarse measurements to create high-resolution products. Different predicting variables are tested showing the need to use IR-derived information on vegetation, temperature diurnal evolution, and a temporal information. To build a true ‘all-weather’ methodology, the effect of clouds on surface temperatures is accounted for by correcting the clear-sky diurnal cycle amplitude, using cloud parameters from meteorological reanalysis. Testing the method on a coarse IR synthetic data at ∼25 km resolution yields a Root Mean Square Deviations (RMSD) between the ∼5 km high-resolution and downscaled temperatures smaller than 1 ∘C. When applied to observations by the Special Sensor Microwave Imager Sounder (SSMIS) at ∼25 km resolution, the downscaling to ∼5 km yields a smaller RMSD compared to IR observations. These results demonstrate the relevance of the methodology to downscale MW land-surface temperature and its potential to spatially enhanced the current ‘all-weather’ satellite monitoring of surface temperatures.
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Ackerley, Duncan, and Dietmar Dommenget. "Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures." Geoscientific Model Development 9, no. 6 (2016): 2077–98. http://dx.doi.org/10.5194/gmd-9-2077-2016.

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Abstract. General circulation models (GCMs) are valuable tools for understanding how the global ocean–atmosphere–land surface system interacts and are routinely evaluated relative to observational data sets. Conversely, observational data sets can also be used to constrain GCMs in order to identify systematic errors in their simulated climates. One such example is to prescribe sea surface temperatures (SSTs) such that 70 % of the Earth's surface temperature field is observationally constrained (known as an Atmospheric Model Intercomparison Project, AMIP, simulation). Nevertheless, in such simulations, land surface temperatures are typically allowed to vary freely, and therefore any errors that develop over the land may affect the global circulation. In this study therefore, a method for prescribing the land surface temperatures within a GCM (the Australian Community Climate and Earth System Simulator, ACCESS) is presented. Simulations with this prescribed land surface temperature model produce a mean climate state that is comparable to a simulation with freely varying land temperatures; for example, the diurnal cycle of tropical convection is maintained. The model is then developed further to incorporate a selection of “proof of concept” sensitivity experiments where the land surface temperatures are changed globally and regionally. The resulting changes to the global circulation in these sensitivity experiments are found to be consistent with other idealized model experiments described in the wider scientific literature. Finally, a list of other potential applications is described at the end of the study to highlight the usefulness of such a model to the scientific community.
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Ackerley, Duncan, Robin Chadwick, Dietmar Dommenget, and Paola Petrelli. "An ensemble of AMIP simulations with prescribed land surface temperatures." Geoscientific Model Development 11, no. 9 (2018): 3865–81. http://dx.doi.org/10.5194/gmd-11-3865-2018.

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Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature, and soil temperature and moisture) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free land experiments are used to perform a set of “AMIP prescribed land” (PL) simulations, which are evaluated against their free land counterparts. The PL simulations agree well with the free land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP prescribed land experiments.
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Chow, Winston T. L., and Bohumil M. Svoma. "Analyses of Nocturnal Temperature Cooling-Rate Response to Historical Local-Scale Urban Land-Use/Land Cover Change." Journal of Applied Meteorology and Climatology 50, no. 9 (2011): 1872–83. http://dx.doi.org/10.1175/jamc-d-10-05014.1.

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AbstractUrbanization affects near-surface climates by increasing city temperatures relative to rural temperatures [i.e., the urban heat island (UHI) effect]. This effect is usually measured as the relative temperature difference between urban areas and a rural location. Use of this measure is potentially problematic, however, mainly because of unclear “rural” definitions across different cities. An alternative metric is proposed—surface temperature cooling/warming rates—that directly measures how variations in land-use and land cover (LULC) affect temperatures for a specific urban area. In this study, the impact of local-scale (&lt;1 km2), historical LULC change was examined on near-surface nocturnal meteorological station temperatures sited within metropolitan Phoenix, Arizona, for 1) urban versus rural areas, 2) areas that underwent rural-to-urban transition over a 20-yr period, and 3) different seasons. Temperature data were analyzed during ideal synoptic conditions of clear and calm weather that do not inhibit surface cooling and that also qualified with respect to measured near-surface wind impacts. Results indicated that 1) urban areas generally observed lower cooling-rate magnitudes than did rural areas, 2) urbanization significantly reduced cooling rates over time, and 3) mean cooling-rate magnitudes were typically larger in summer than in winter. Significant variations in mean nocturnal urban wind speeds were also observed over time, suggesting a possible UHI-induced circulation system that may have influenced local-scale station cooling rates.
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Dissertations / Theses on the topic "Land Surface Temperatures"

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Dicks, Steven E. "Satellite-derived surface temperatures and their relationships to land cover, land use, soils and physiography of North-Central Florida." Gainesville, FL, 1986. http://www.archive.org/details/satellitederived00dick.

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Ellsäßer, Florian [Verfasser]. "Predicting evapotranspiration from drone-recorded land surface temperatures - Method testing and development / Florian Ellsäßer." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2020. http://d-nb.info/1217481508/34.

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Kabsch, Ewa [Verfasser], and H. P. [Akademischer Betreuer] Bähr. "Validation of land surface temperatures from MSG satellite measurements by observations at the ground station near Evora, Portugal / Ewa Kabsch. Betreuer: H.-P. Bähr." Karlsruhe : KIT-Bibliothek, 2009. http://d-nb.info/1013805585/34.

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Jiang, Geng-Ming Li Zhao-Liang. "Retrievals of land surface emissivity and land surface temperature from MSG1-SEVIRI data." Strasbourg : Université Louis Pasteur, 2008. http://eprints-scd-ulp.u-strasbg.fr:8080/848/01/JIANG_Geng_Ming_2007.pdf.

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Jiang, Geng-Ming. "Retrievals of land surface emissivity and land surface temperature from MSG1-SEVIRI data." Université Louis Pasteur (Strasbourg) (1971-2008), 2007. https://publication-theses.unistra.fr/public/theses_doctorat/2007/JIANG_Geng-Ming_2007.pdf.

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Les objectifs de cette thèse sont concentrés sur la détermination de l’émissivité (LSE) et de la température de surface (LST) des surfaces terrestres à partir des données de MSG 1 -SEVIRI. Dans un premier temps l’inter-calibrage des canaux infrarouges 4, 9 et 10 de MSG I -SEVIRI avec les canaux de Terra-MODIS est réalisé. Deux méthodes, la méthode «ray-matching» et une méthode basée sur l’équation transfert radiatif ont été appliqués. Les résultats indiquent que les anomalies de calibrage existent entre les canaux de SEVIRI et de MODIS. L’utilisation des résultats obtenus par la méthode basée sur le transfert radiatif pour recalibrer les données de SEVIRI est recommandée. Ce recalibrage permet de supprimer la surestimation des LSTs obtenues à partir des données de SEVIRI avec une méthode SplitWindow. Les émissivités sont ensuite estimées dans les canaux 4, 7, 9 et 10 sur des grandes étendues spatiales et temporelles en utilisant une méthode basée sur le concept des TISI. Une nouvelle méthode de corrections atmosphériques a été développée, principalement basée sur le modèle de DTC (Diumal Time Cycle), et deux modèles de BRDF, le modèle du Minnaert modifié et le modèle de RossThick-LiSparse-R, ont été évalués. Les températures de surface sont déterminées à partir des données MSGI-SEVIRJ et AATSR. La méthode mono canal simple et la méthode Split Window ont été utilisées. Les algorithmes généralisés de Split Window ont été développés pour les instruments SEVIRI et AATSR en utilisant le code MODTRAN et les profils atmosphériques standards et ont été appliqués avec succès aux déterminations des LST à partir des données de SEVIRI et d’AATSR. Les températures de surface obtenues à partir de SEVERI ont été validées par comparaison directe avec les produits MODIS/Terra LST et les AATSR LST estimées par la Split Window généralisée au-dessus de la péninsule ibérienne et d’une région de l’Egypte et du 1Moyen-est. Les résultats indiquent que les LST SEVIRJ sont conformes au LST extraites des produits MODIS/Terra LST et AATSR LST avec une exactitude comprise entre l-2 K.
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Yang, Jiansheng. "Remote sensing modeling of land surface temperature /." View online ; access limited to URI, 2003. http://0-wwwlib.umi.com.helin.uri.edu/dissertations/dlnow/3112133.

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Dash, Prasanjit. "Land surface temperature and emissivity retrieval from satellite measurements." Karlsruhe : Forschungszentrum Karlsruhe in der Helmholtz-Gemeinschaft, 2005. http://bibliothek.fzk.de/zb/berichte/FZKA7095.pdf.

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Mitchell, Bruce Coffyn. "Urbanization and Land Surface Temperature in Pinellas County, Florida." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3250.

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Since the early 1800's, many studies have recognized increased heat in urban areas, known as the urban heat island (UHI) effect, as one of the results of human modification to the natural landscape. UHI is related to differences in land surface temperature (LST) between rural areas and urban areas where factors of the built environment such as the thermodynamic capacities of materials, structural geometry, and heat generating activities cause increased storage and re-radiation of heat to the atmosphere. This thesis examines the correlation between factors of urbanization and differences in land surface temperature (LST) in the subtropical climate of Pinellas County, Florida using remote sensing techniques. It describes the spatial pattern of LST, analyzes its relationship to factors of urbanization relative to NDVI, percentage of impervious surface, and land use land cover in the study area. It also assesses the effectiveness of remote sensing as an efficient method of identifying LST patterns at the local and neighborhood level for mitigation strategies. Landsat TM thermal band imagery for three dates; April 1986, 2001 and 2009 was processed using Qin's mono-window algorithm (MWA) technique to derive LST levels. This data was compared to in-situ readings, then normalized and statistically analyzed for correlation with vegetation ratio (NDVI) and imperviousness percentages derived using linear spectral mixing/unmixing, and also with land use/land cover classification. The resulting LST spatial pattern is a gradient across the peninsular landscape, from cooler water and wetland areas to a generally warmer interior, interspersed with micro-urban heat islands (MUHIs), corresponding to urban structures and "cool-islands" of parkland and lakes. Correspondence between LST pattern and urban structures and land use demonstrates the suitability of medium resolution remote sensing data and techniques for identifying micro-urban heat islands (MUHIs) for possible mitigation. Mitigation could include relatively low-cost measures like replacement of inefficient asphalt roofs with more reflective and emissive "cool roofs," placement of "street trees" to enhance shade, and replacement of impervious pavements by permeable surfaces. The thesis concludes that Landsat TM imagery processed with the MWA provides an efficient, relatively low-cost method for locating MUHIs. Satellite remote sensing, combined with aerial photography can facilitate neighborhood level analysis for the implementation of low-cost mitigation techniques. Previous studies have demonstrated that these are successful ways to mitigate the UHI effect at the micro-scale level; lowering urban heat and saving energy, and also facilitating the reintegration of natural elements into the urban environment.
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Boonmee, Marvin. "Land surface temperature and emissivity retrieval from thermal infrared hyperspectral imagery /." Online version of thesis, 2007. http://hdl.handle.net/1850/5868.

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Simões, Débora de Souza. "Ambiente físico e meteorológico para análise do risco de geada." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/132123.

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A geada é um fenômeno meteorológico adverso que causa perdas severas ao setor agrícola, em especial no Sul do Brasil. A baixa distribuição espacial da rede de estações meteorológicas dificulta o monitoramento e a previsão do fenômeno. O propósito principal desta tese foi o desenvolvimento de um modelo matemático para quantificar de forma direta e simples a probabilidade do risco de ocorrência de geada tendo como base em dados de fácil obtenção como altitude, latitude, continentalidade e temperatura do ar. O modelo criado, denominado Risco Geral de Geada (RGG), foi idealizado a partir de dois riscos básicos, o risco geográfico e o risco advindo da temperatura mínima do local, ambos com o mesma contribuição para a ocorrência de geada. O risco geográfico de geada (RGeo) foi obtido a partir do somatório dos riscos atribuídos aos fatores geográficos altitude, latitude e continentalidade. Cada um destes fatores contribui de forma diferente para a formação da geada e suas contribuições foram estimadas a partir de um modelo de regressão linear múltipla para a estimativa da temperatura mínima do ar climatológica de inverno no Rio Grande do Sul. No risco de geada associado à temperatura mínima (RTmín) foi feita a atribuição de riscos em um intervalo de temperatura entre 0 e 6°C. O modelo final obtido, válido apenas para o Rio Grande do Sul, foi testado com dados coletados em estações meteorológicas de superfície da mesorregião do Sudeste Rio-grandense, localizadas em Encruzilhada do Sul, Rio Grande e Santa Vitória do Palmar. Dados de temperatura mínima do ar nos meses de junho, julho e agosto, coletados entre os anos de 1961 e 2015, comprovaram a utilidade do modelo RGG para a definição da probabilidade do risco de ocorrência de geada, mesmo diante de incertezas atribuídas a outros fatores não descritos no modelo. Na região de teste também foi avaliada a qualidade de dados orbitais de temperatura da superfície terrestre (TST), obtidos do produto MDY11A1 da passagem noturna do sensor MODIS/AQUA, na detecção de temperaturas baixas relacionadas com a ocorrência de geada. A frequência de dias com TST inferiores a 3°C mostrou coerência tanto com os dados observados em estação meteorológica, quanto com o risco determinado pelo RGG. A coerência entre os resultados obtidos do modelo RGG e os dados reais observados em superfície e obtidos por satélite torna o modelo útil na descrição da probabilidade do risco de ocorrência de geada sobre o Rio Grande do Sul.<br>Frost is an adverse meteorological phenomenon that causes severe losses to the agricultural sector, especially in Southern Brazil. Low spatial distribution of the network of meteorological stations hinders monitoring and forecast phenomenon. The main purpose of this thesis was to develop a mathematical model to measure directly and easily the probability of the risk of frost based on readily available data such as altitude, latitude, continentality and air temperature. The model, called Frost General Risk (RGG), was designed from two basic risk, geographic risk and risk arising out of the local minimum temperature, both with the same contribution to the occurrence of frost. The geographical risk of frost (RGeo) was obtained from the sum of the risks attributed to geographical factors altitude, latitude and continental influence. Each of these factors contributes differently to the formation of frost and their contributions were estimated from a multiple linear regression model to estimate the minimum air temperature winter climatological in Rio Grande do Sul. In the frost risk associated with minimum temperature (RTmín) assigning risk was taken in a temperature range between 0 and 6° C. The final model obtained, valid only for the Rio Grande do Sul, has been tested with data collected from weather stations surface of the middle region of Sudeste Rio-grandense, located in Encruzilhada do Sul, Rio Grande and Santa Vitória do Palmar. Minimum temperature, the air in the months of june, july and august, collected between 1961 and 2015, have proved the usefulness of the model RGG to define the probability of the risk of frost, even in the face of uncertainty attributed to other factors not described in the model. In the test region was also evaluated the quality of satellite data of the land surface temperature (LST), the product obtained MDY11A1 the night passage of MODIS / AQUA sensor to detect low temperatures related to the occurrence of frost. The frequency of days with LST below 3° C showed much consistency with the observed data in weather station, and with the particular risk for the RGG. Consistency between the results obtained from the RGG model and the actual data observed in surface and from satellites makes the model useful in describing the probability of the risk of frost on the Rio Grande do Sul.
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Books on the topic "Land Surface Temperatures"

1

Prata, A. J. Validation data for land surface temperature determination from satellites. Commonwealth Scientific and Industrial Research Organization, 1994.

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Tan, Kok Chooi. Land cover changes and their relationship with land surface temperature using remote sensing technique. Penerbit Universiti Sains Malaysia, 2013.

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Mass, Clifford. A next-generation land surface model for the prediction of pavement temperature. Washington State Dept. of Transportation, 2003.

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Labgaa, Rachid R. A model of the CO2 exchanges between biosphere and atmosphere in the tundra. Earth-Space Research Group, CRSEO -- Ellison Hall, University of California Santa Barbara, 1994.

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Carlson, Toby N. A remotely sensed index of deforestation/urbanization for use in climate models: Annual performance report for the period 1 January 1995 - 31 December 1995. Pennsylvania State University, 1995.

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Carlson, Toby N. A remotely sensed index of deforestation/urbanization for use in climate models: Annual performance report for the period 1 January 1995 - 31 December 1995. Pennsylvania State University, 1995.

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A Validation Study of the SSM/I Temperature Algorithm and Comparison with the CAL/VAL Land Surface Temperatures. Storming Media, 1997.

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Dicks, Steven E. Satellite-derived surface temperatures and their relationships to land cover, land use, soils and physiography of North-Central Florida. 1986.

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United States. National Aeronautics and Space Administration., ed. Land surface temperature measurements from EOS MODIS data. National Aeronautics and Space Administration, 1994.

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Remote Sensing Monitoring of Land Surface Temperature (LST). MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-1427-7.

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Book chapters on the topic "Land Surface Temperatures"

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Jones, P. D. "Land Surface Temperatures — Is the Network Good Enough?" In Long-Term Climate Monitoring by the Global Climate Observing System. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-0323-7_21.

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Taniguchi, Makoto, David R. Williamson, and Adrian J. Peck. "Changes in Surface and Subsurface Temperatures after Clearing Forest in Western Australia." In Subsurface Hydrological Responses to Land Cover and Land Use Changes. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6141-5_10.

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Simó, Gemma, Daniel Martínez-Villagrasa, Maria A. Jiménez, Vicente Caselles, and Joan Cuxart. "Impact of the Surface–Atmosphere Variables on the Relation Between Air and Land Surface Temperatures." In Pageoph Topical Volumes. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11958-4_13.

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Gillespie, Alan. "Land Surface Temperature." In Encyclopedia of Remote Sensing. Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_79.

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Carlson, Toby N. "Recent Advances in Modeling the Infrared Temperature of Vegetation Canopies." In Land Surface Evaporation. Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3032-8_21.

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Yu, Yunyue, Jeffrey P. Privette, Yuling Liu, and Donglian Sun. "Land Surface Temperature: Remote Sensing." In Landscape and Land Capacity. CRC Press, 2020. http://dx.doi.org/10.1201/9780429445552-6.

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Wan, Zhengming, and Zhao-Liang Li. "MODIS Land Surface Temperature and Emissivity." In Land Remote Sensing and Global Environmental Change. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6749-7_25.

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Luo, Ren, Ji Zhou, Jiajia Yang, Lijiao Ai, and Yilong Feng. "Downscaling of Tiangong-2 Land Surface Temperature." In Proceedings of the Tiangong-2 Remote Sensing Application Conference. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3501-3_16.

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Nimish, Gupta, V. Banad Sudeep, and H. Aithal Bharath. "Impacts of Urban Land Use Land Cover Pattern on Land Surface Temperature." In Lecture Notes in Civil Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2545-2_5.

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Dewan, Ashraf M., and Robert J. Corner. "Impact of Land Use and Land Cover Changes on Urban Land Surface Temperature." In Dhaka Megacity. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6735-5_12.

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Conference papers on the topic "Land Surface Temperatures"

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Jinling Quan. "Blending multi-spatiotemporal resolution land surface temperatures over heterogeneous surfaces." In 2017 Joint Urban Remote Sensing Event (JURSE). IEEE, 2017. http://dx.doi.org/10.1109/jurse.2017.7924596.

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Wang Shanshan, Chen Xi, Bao An-ming, and Alishir Kurban. "Satellite sensor data analysis of urban surface temperatures and land use / land cover." In 2010 2nd International Conference on Information Science and Engineering (ICISE). IEEE, 2010. http://dx.doi.org/10.1109/icise.2010.5690556.

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Park, Sunyurp, Johannes J. Feddema, and Stephen L. Egbert. "MODIS land surface temperatures and their relationship with hydroclimatological parameters." In AeroSense 2002, edited by Xavier P. Maldague and Andres E. Rozlosnik. SPIE, 2002. http://dx.doi.org/10.1117/12.459565.

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Kassab, Alain J., Eduardo A. Divo, Minking K. Chyu, and Frank J. Cunha. "Inverse BEM Method to Identify Surface Temperatures and Heat Transfer Coefficient Distributions at Inaccessible Surfaces." In ASME Turbo Expo 2005: Power for Land, Sea, and Air. ASMEDC, 2005. http://dx.doi.org/10.1115/gt2005-68873.

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The purpose of the inverse problem considered in this study is to resolve heat transfer coefficient distributions by solving a steady-state inverse problem. Temperature measurements at interior locations supply the additional information that renders the inverse problem solvable. A regularized quadratic functional is defined to measure the deviation of computed temperatures from the values under current estimates of the heat transfer coefficient distribution at the surface exposed to convective heat transfer. The inverse problem is solved by minimizing this functional using a parallelized genetic algorithm (PGA) as the minimization algorithm and a two-dimensional multi-region boundary element method (BEM) heat conduction code as the field variable solver. Results are presented for a regular rectangular geometry and an irregular geometry representative of a blade trailing edge and demonstrate the success of the approach in retrieving accurate heat transfer coefficient distributions.
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Yu, Yunyue, Dan Tarpley, M. K. Rama Varma Raja, Konstantin Vinnikov, and Mitch D. Goldberg. "Evaluation of satellite land surface temperatures using ground measurements from surface radiation budget network." In Optical Engineering + Applications, edited by Mitchell D. Goldberg, Hal J. Bloom, Philip E. Ardanuy, and Allen H. Huang. SPIE, 2008. http://dx.doi.org/10.1117/12.794227.

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Dantas, A. A. A., and E. Ferreira. "Land Surface Temperatures From Meteosat-9 satellite in Minas Gerais state, Brazil." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5649705.

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Siddiqui, Simil Amir. "Assessment of Urban Heat Islands Based on the Relationship Between Land Surface Temperature and Land Use/Land Cover in Greater Doha." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0108.

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Urban heat islands (UHI) are areas with elevated temperatures occurring in cities compared to surrounding rural areas. This study realizes the lack of research regarding the trends of UHIs in desert countries and focuses on Doha. The research includes twelve months of two-time periods; 2000-2019. ArcGIS software was used to compute the land surface temperature (LST) of the city using Landsat images. Land use/land cover (LULC) maps were computed to show how the city has evolved in 19 years. 30 field samples were used to verify the accuracy of the LULC. Results showed UHI in Doha did not display similar pattern to that of cities in subtropical and temperate regions. Higher temperatures were prevalent in out-skirts comprising of barren and built-up areas with high population and no vegetation. Comparatively, the main downtown with artificially planted vegetation and shade from skyscrapers created cooler microclimates. The overall LST of greater Doha has increased by 0.7°C from 2000 to 2019. Furthermore %LULC of built up, vegetation, barren land, marsh land and water body were 29%, 4.5%, 58.6%, 2.8% and 5% in 2000 and 56.5 %, 8.2%, 33.2 %, 0% and 2.1% in 2019 respectively. Overall, there was an increase in built-up and vegetation decrease in water and barren areas and complete loss of marshland. Highest temperatures were recorded for marshland area in year 2000 and barren and built in year 2019. Transect profiles showed positive correlation between NDBI and LST and a negative correlation between NDVI and LST.
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Boyle, R. J., and R. G. Senyitko. "Effects of Surface Roughness on Turbine Vane Heat Transfer." In ASME Turbo Expo 2005: Power for Land, Sea, and Air. ASMEDC, 2005. http://dx.doi.org/10.1115/gt2005-69133.

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Turbine vane surface temperatures were measured in a linear cascade using an infrared non-contact thermal detector. A thermal barrier coating (TBC) was applied to the vane surface to give a rough surface. The temperature drop across the relatively thick TBC was used to determine heat transfer coefficients. Tests were conducted over a range of Reynolds and Mach numbers, resulting in large variations in hydraulic roughness. The measured heat transfer rates were significantly higher than were expected for a smooth vane. The detector was mounted in a probe holder, and traversed in a manner similar to that used for pneumatic or hot wire probes. The results showed that this approach gave useful information, and should be considered when non-contact surface temperatures are desired.
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Kafer, Pamela Suelen, Silvia Beatriz Alves Rolim, Maria Lujan Iglesias, et al. "Land Surface Temperature Retrieval from Landsat-8 Data: A Comparison Using a Quartz Spectral Library Based on Temperatures." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518135.

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Liu, Xiangyang, Bo-Hui Tang, Hua Wu, Ronglin Tang, Zhao-Liang Li, and Guofei Shang. "A Method for Angular Normalization of Land Surface Temperature Products Based on Component Temperatures and Fractional Vegetation Cover." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8899823.

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Reports on the topic "Land Surface Temperatures"

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Beck, Aaron. RiverOceanPlastic: Land-ocean transfer of plastic debris in the North Atlantic, Cruise No. AL534/2, 05 March – 26 March 2020, Malaga (Spain) – Kiel (Germany). GEOMAR Helmholtz Centre for Ocean Research Kiel, 2020. http://dx.doi.org/10.3289/cr_al534-2.

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Cruise AL534/2 is part of a multi-disciplinary research initiative as part of the JPI Oceans project HOTMIC and sought to investigate the origin, transport and fate of plastic debris from estuaries to the oceanic garbage patches. The main focus of the cruise was on the horizontal transfer of plastic debris from major European rivers into shelf regions and on the processes that mediate this transport. Stations were originally chosen to target the outflows of major European rivers along the western Europe coast between Malaga (Spain) and Kiel (Germany), although some modifications were made in response to inclement weather. In total, 16 stations were sampled along the cruise track. The sampling scheme was similar for most stations, and included: 1) a CTD cast to collect water column salinity and temperature profiles, and discrete samples between surface and seafloor, 2) sediment sampling with Van Veen grab and mini-multi corer (mini-MUC), 3) suspended particle and plankton sampling using a towed Bongo net and vertical WP3 net, and 4) surface neusten sampling using a catamaran trawl. At a subset of stations with deep water, suspended particles were collected using in situ pumps deployed on a cable. During transit between stations, surface water samples were collected from the ship’s underway seawater supply, and during calm weather, floating litter was counted by visual survey teams. The samples and data collected on cruise AL534/2 will be used to determine the: (1) abundance of plastic debris in surface waters, as well as the composition of polymer types, originating in major European estuaries and transported through coastal waters, (2) abundance and composition of microplastics (MP) in the water column at different depths from the sea surface to the seafloor including the sediment, (3) abundance and composition of plastic debris in pelagic and benthic organisms (invertebrates), (4) abundance and identity of biofoulers (bacteria, protozoans and metazoans) on the surface of plastic debris from different water depths, (5) identification of chemical compounds (“additives”) in the plastic debris and in water samples.
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Yanev, Ivan, and Lachezar Filchev. Assessment of the land surface temperature dynamics in the city of Sofia using Landsat satellite data. Prof. Marin Drinov Publishing House of Bulgarian Academy of Sciences, 2018. http://dx.doi.org/10.7546/aerebu.29.18.01.05.

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Desai, Jairaj, Jijo K. Mathew, Woosung Kim, et al. Dashboards for Real-time Monitoring of Winter Operations Activities and After-action Assessment. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317252.

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The Indiana Department of Transportation (INDOT) operates a fleet of nearly 1100 snowplows and spends up to $60M annually on snow removal and de-icing as part of their winter operation maintenance activities. Systematically allocating resources and optimizing material application rates can potentially save revenue that can be reallocated for other roadway maintenance operations. Modern snowplows are beginning to be equipped with a variety of Mobile Road Weather Information Sensors (MARWIS) which can provide a host of analytical data characterizing on-the-ground conditions during periods of wintry precipitation. Traffic speeds fused with road conditions and precipitation data from weather stations provide a uniquely detailed look at the progression of a winter event and the performance of the fleet. This research uses a combination of traffic speeds, MARWIS and North American Land Data Assimilation System (NLDAS) data to develop real-time dashboards characterizing the impact of precipitation and pavement surface temperature on mobility. Twenty heavy snow events were identified for the state of Indiana from November 2018 through April 2019. Two particular instances, that impacted 182 miles and 231 miles of interstate at their peaks occurred in January and March, respectively, and were used as a case study for this paper. The dashboards proposed in this paper may prove to be particularly useful for agencies in tracking fleet activity through a winter storm, helping in resource allocation and scheduling and forecasting resource needs.
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Bowles, David, Michael Williams, Hope Dodd, et al. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2284622.

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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threatened by numerous stressors, most of which originate outside park boundaries. Stream condition and ecosystem health are dependent on processes occurring in the entire watershed as well as riparian and floodplain areas; therefore, they cannot be manipulated independently of this interrelationship. Land use activities—such as timber management, landfills, grazing, confined animal feeding operations, urbanization, stream channelization, removal of riparian vegetation and gravel, and mineral and metals mining—threaten stream quality. Accordingly, the framework for this aquatic monitoring is directed towards maintaining the ecological integrity of the streams in those parks. Invertebrates are an important tool for understanding and detecting changes in ecosystem integrity, and they can be used to reflect cumulative impacts that cannot otherwise be detected through traditional water quality monitoring. The broad diversity of invertebrate species occurring in aquatic systems similarly demonstrates a broad range of responses to different environmental stressors. Benthic invertebrates are sensitive to the wide variety of impacts that influence Ozark streams. Benthic invertebrate community structure can be quantified to reflect stream integrity in several ways, including the absence of pollution sensitive taxa, dominance by a particular taxon combined with low overall taxa richness, or appreciable shifts in community composition relative to reference condition. Furthermore, changes in the diversity and community structure of benthic invertebrates are relatively simple to communicate to resource managers and the public. To assess the natural and anthropo-genic processes influencing invertebrate communities, this protocol has been designed to incorporate the spatial relationship of benthic invertebrates with their local habitat including substrate size and embeddedness, and water quality parameters (temperature, dissolved oxygen, pH, specific conductance, and turbidity). Rigid quality control and quality assurance are used to ensure maximum data integrity. Detailed standard operating procedures (SOPs) and supporting information are associated with this protocol.
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Tweet, Justin S., Vincent L. Santucci, Kenneth Convery, Jonathan Hoffman, and Laura Kirn. Channel Islands National Park: Paleontological resource inventory (public version). National Park Service, 2020. http://dx.doi.org/10.36967/nrr-2278664.

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Channel Island National Park (CHIS), incorporating five islands off the coast of southern California (Anacapa Island, San Miguel Island, Santa Barbara Island, Santa Cruz Island, and Santa Rosa Island), has an outstanding paleontological record. The park has significant fossils dating from the Late Cretaceous to the Holocene, representing organisms of the sea, the land, and the air. Highlights include: the famous pygmy mammoths that inhabited the conjoined northern islands during the late Pleistocene; the best fossil avifauna of any National Park Service (NPS) unit; intertwined paleontological and cultural records extending into the latest Pleistocene, including Arlington Man, the oldest well-dated human known from North America; calichified “fossil forests”; records of Miocene desmostylians and sirenians, unusual sea mammals; abundant Pleistocene mollusks illustrating changes in sea level and ocean temperature; one of the most thoroughly studied records of microfossils in the NPS; and type specimens for 23 fossil taxa. Paleontological research on the islands of CHIS began in the second half of the 19th century. The first discovery of a mammoth specimen was reported in 1873. Research can be divided into four periods: 1) the few early reports from the 19th century; 2) a sustained burst of activity in the 1920s and 1930s; 3) a second burst from the 1950s into the 1970s; and 4) the modern period of activity, symbolically opened with the 1994 discovery of a nearly complete pygmy mammoth skeleton on Santa Rosa Island. The work associated with this paleontological resource inventory may be considered the beginning of a fifth period. Fossils were specifically mentioned in the 1938 proclamation establishing what was then Channel Islands National Monument, making CHIS one of 18 NPS areas for which paleontological resources are referenced in the enabling legislation. Each of the five islands of CHIS has distinct paleontological and geological records, each has some kind of fossil resources, and almost all of the sedimentary formations on the islands are fossiliferous within CHIS. Anacapa Island and Santa Barbara Island, the two smallest islands, are primarily composed of Miocene volcanic rocks interfingered with small quantities of sedimentary rock and covered with a veneer of Quaternary sediments. Santa Barbara stands apart from Anacapa because it was never part of Santarosae, the landmass that existed at times in the Pleistocene when sea level was low enough that the four northern islands were connected. San Miguel Island, Santa Cruz Island, and Santa Rosa Island have more complex geologic histories. Of these three islands, San Miguel Island has relatively simple geologic structure and few formations. Santa Cruz Island has the most varied geology of the islands, as well as the longest rock record exposed at the surface, beginning with Jurassic metamorphic and intrusive igneous rocks. The Channel Islands have been uplifted and faulted in a complex 20-million-year-long geologic episode tied to the collision of the North American and Pacific Places, the initiation of the San Andreas fault system, and the 90° clockwise rotation of the Transverse Ranges, of which the northern Channel Islands are the westernmost part. Widespread volcanic activity from about 19 to 14 million years ago is evidenced by the igneous rocks found on each island.
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