Geostatistical interpolation of SLC-off Landsat ETM+ images

Pringle, M. J.; Schmidt, Michaël; Muir, Jasmine

doi:10.1016/j.isprsjprs.2009.06.001

Cited by 142 publications

(85 citation statements)

References 15 publications

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“…The satellite images that presented cloud cover were discarded. The LANDSAT 7 ETM+ images error scan was corrected previously by applying the Scan Line Corrector technique (SCL-Off) (Pringle et al, 2009). …”

Section: Methodsmentioning

confidence: 99%

Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina

Ferrelli

Cisneros

Delgado

2018

dag

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Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina AbstractThe aim of this work was to study the spatial distribution of Land Surface Temperature (LST) and its relationship with diverse urban land covers and the Normalized Difference Vegetation Index (NDVI). The study area was Monte Hermoso city, which is located in the southwest of Buenos Aires province, Argentina. To obtain the LST and NDVI parameters, satellite images from LANDSAT 5 TM and LANDSAT 7 ETM+ sensors were seasonally processed for the period 2008-2012. Visual interpretation techniques and empirical intervention were applied to design an urban land cover map on which LST and NDVI were analyzed by tracing four transects oriented in latitudinal and longitudinal directions. Each urban cover presented a particular behavior of these parameters. Furthermore, significant results for the relationship between LST and NDVI were observed (with α 0.1 and 0.05) with R 2 , Pearson, and Spearman indices values higher than 0.7. Finally, LST variation in diverse land covers was observed as a consequence of urban growth and the alteration of the vegetation coverage. Therefore, it was concluded that the spatial and temporal variation of LST values may indicate modifications in urban land covers. The information obtained in this study would be a useful tool to guide future urban management studies and policies. Keywords: Land Surface Temperature (LST); Normalized Difference Vegetation Index (NDVI); seasonal distribution; satellite imagery processing; Monte Hermoso Resum. Anàlisi espacial i temporal de la relació TST-NDVI per a l'estudi dels canvis de cobertura del sòl i la seva contribució per a la planificació urbana (Monte Hermoso, Argentina)L'objectiu d'aquesta investigació va ser estudiar la distribució espacial de la temperatura de superfície terrestre (TST), la seva relació amb diferents cobertures del sòl urbà i l'índex de vegetació de diferència (NDVI). L'àrea d'estudi seleccionada va ser la ciutat costanera de Monte Hermoso, localitzada al sud-oest de la província de Buenos Aires (Argentina). Per fer-ho, es van processar imatges satel·litàries LANDSAT 5 TM i 7 ETM + per al període 2008-2012 de manera estacional. Amb aquestes imatges es va calcular la TST i l'NDVI. Posteriorment, es van aplicar tècniques d'interpretació visual i es van fer sortides al camp per dissenyar un mapa de cobertures del sòl urbà. Sobre aquestes, es va analitzar la variació de la TST i l'NDVI mitjançant el traçat de quatre transsectes orientats en sentit latitudinal i longitudinal. Cadascuna d'aquestes cobertures va presentar un comportament particular dels paràmetres calculats. D'altra banda, es van observar resultats significatius de la relació TST-NDVI (amb α de 0,1 i 0,05), amb valors de R 2 , índexs de Pearson i Spearman més grans de 0,7. Finalment, es va evidenciar que el canvi en les cobertures del sòl, producte del creixement urbà, va modificar els valors estacional...

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Section: Methodsmentioning

confidence: 99%

Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina

Ferrelli

Cisneros

Delgado

2018

dag

View full text Add to dashboard Cite

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“…The result showed that Kriging could accurately describe the spatial dependence of gaps (an overall RMSE value of 5 raw DN value). Geostatistical methods (kriging or co-kriging) are commonly used as the most suitable method to fill the data gaps [53,54]. Thus, we used the kriging interpolation technique as the most suitable method for estimating pixel values (DN) for locations that had gaps (no data) in ETM+ raw data [53,54] …”

Section: Pre-processing Of Remote Sensing Datamentioning

confidence: 99%

Estimating and Up-Scaling Fuel Moisture and Leaf Dry Matter Content of a Temperate Humid Forest Using Multi Resolution Remote Sensing Data

2016

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Vegetation moisture and dry matter content are important indicators in predicting the behavior of fire and it is widely used in fire spread models. In this study, leaf fuel moisture content such as Live Fuel Moisture Content (LFMC), Leaf Relative Water Content (RWC), Dead Fuel Moisture Content (DFMC), and Leaf Dry Matter Content (LDMC) (hereinafter known as moisture content indices (MCI)) were calculated in the field for different forest species at 32 sites in a temperate humid forest (Zaringol forest) located in northeastern Iran. These data and several relevant vegetation-biophysical indices and atmospheric variables calculated using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data with moderate spatial resolution (30 m) were used to estimate MCI of the Zaringol forest using Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) methods. The prediction of MCI using ANN showed that ETM+ predicted MCI slightly better (Mean Absolute Percentage Error (MAPE) of 6%-12%)) than MLR (MAPE between 8% and 17%). Once satisfactory results in estimating MCI were obtained by using ANN from ETM+ data, these data were then upscaled to estimate MCI using MODIS data for daily monitoring of leaf water and leaf dry matter content at 500 m spatial resolution. For MODIS derived LFMC, LDMC, RWC, and DLMC, the ANN produced a MAPE between 11% and 29% for the indices compared to MLR which produced an MAPE of 14%-33%. In conclusion, we suggest that upscaling is necessary for solving the scale discrepancy problems between the indicators and low spatial resolution MODIS data. The scaling up of MCI could be used for pre-fire alert system and thereby can detect fire prone areas in near real time for fire-fighting operations.

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“…Además, los parámetros meteorológicos mencionados permitieron ajustar los radiosondeos necesarios para la obtención de la TST (http://atmcorr.gsfc.nasa.gov/). Las imá-genes Landsat 7 fueron corregidas debido al error de escaneo de las imágenes ETM+ aplicando la técnica de interpolación multitemporal SLC-Off (Scan Line Corrector) (USGS 2003, Scaramuzza 2004, Pringle et al 2009). …”

Section: Metodologíaunclassified

Utilización de imágenes satelitales para el estudio de la distribución térmica en distintas coberturas del suelo de la ciudad de Bahía Blanca (Argentina)

2015

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Resumen: El estudio del clima urbano es relevante para conocer el ambiente donde habita la mayor parte de la población. Las ciudades presentan sectores que incluyen estructuras edilicias, espacios verdes, suelos al descubierto, tránsito vehicular, necesidades calóricas de la ciudad y diferentes coberturas de sombras. Actualmente, el cambio climático y sus efectos sobre las ciudades son temas de gran interés científico. Son escasas las investigaciones que interpretan los cambios térmicos que se producen en el interior de las ciudades debido a la densificación de los edificios y como consecuencia de la variabilidad climática. Por tal motivo, el objetivo de este trabajo fue analizar el comportamiento de la Temperatura de Superficie Terrestre (TST) y su relación con las distintas coberturas del suelo en la ciudad de Bahía Blanca, Argentina. Para ello, se analizaron imágenes satelitales Landsat 5 TM y 7 ETM+ con el método monocanal. Además, se realizó un mapa de coberturas del suelo mediante interpretación visual de imágenes satelitales validado por intervención empírica. Posteriormente, se relacionaron los datos de TST con las coberturas del suelo. En el centro de la ciudad, la TST presentó variaciones espaciales heterogéneas según las estaciones del año y las sombras generadas por los edificios. Los mayores valores de TST se localizaron en la periferia (45,1°C) y en urbano muy disperso (46°C) y el menor en el centro de la ciudad (2°C). Las distintas coberturas del suelo generaron menores fluctuaciones de TST en invierno (>5°C) y las mayores en verano (entre 15 y 25°C).Palabras clave: Teledetección, TST, Bahía Blanca, clima urbano, coberturas del suelo. Utilization of satellite images to study the thermal distribution in different soil covers in Bahia Blanca city (Argentina)Abstract: The study of the urban climate is relevant to increase the knowledge about the environment where live most of the world's population. Cities have areas that include buildings, green spaces, un-vegetated soils, transit, among others. Currently, scientists are focusing on the effects of climate change in cities. There is a shortage of studies that analyze the thermal changes that occur in the inner city due to the densification of buildings. For these reasons, the aim of this study was to analyze the spatial distribution of Land Surface Temperature (LST) and its relation with different soil covers in Bahia Blanca city, Argentina. Satellite images from Landsat 5 TM and Landsat 7 ETM+ were analyzed with singlechannel method. Besides, it was made a soil coverage map through visual interpretation of satellite images and it was validated with field trips. LST data were compared with each soil coverage. In downtown, the LST was heterogeneous and presented spatial variations according to the season and the shadows of the buildings. The maximum values of LST were localized in the periphery (45.1°C) and in urban very sparse (46°C) and the minimum in downtown (2°C). Each soil cover had minor fluctuations in the winter (>5°C) and higher in the summe...

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Geostatistical interpolation of SLC-off Landsat ETM+ images

Cited by 142 publications

References 15 publications

Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina

Spatial and temporal analysis of the LST-NDVI relationship for the study of land cover changes and their contribution to urban planning in Monte Hermoso, Argentina

Estimating and Up-Scaling Fuel Moisture and Leaf Dry Matter Content of a Temperate Humid Forest Using Multi Resolution Remote Sensing Data

Utilización de imágenes satelitales para el estudio de la distribución térmica en distintas coberturas del suelo de la ciudad de Bahía Blanca (Argentina)

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