" Models and observations show that the Arctic is experiencing the most rapid changes in global n... more " Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1–25 km) for the past decade (2000–2010). In this paper, we provide: (1) a review of previous validation of MODIS/AATSR L2; (2) a description of the
processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max:
−1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions."
Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditio... more Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditions or mapping rock glaciers and debris-covered glaciers. We explore the potential of thermal imaging and in particular thermal inertia mapping in mountain cryospheric research, focusing on the relationships between ground surface temperatures and the presence of ice-debris landforms on one side and land surface temperature (LST) and apparent thermal inertia (ATI) on the other. In our case study we utilize ASTER daytime and nighttime imagery and in-situ measurements of near-surface ground temperature (NSGT) in the Mediterranean Andes during a snow-free and dry observation period in late summer. Spatial patterns of LST and NSGT were mostly consistent with each other both at daytime and at nighttime. Daytime LST over ice-debris landforms was decreased and ATI consequently increased compared to other debris surfaces under otherwise equal conditions, but NSGT showed contradictory results, which underlines the complexity and possible scale dependence of ATI in heterogeneous substrates with the presence of a thermal mismatch and a heat sink at depth. While our results demonstrate the utility of thermal imaging and ATI mapping in a mountain cryospheric context, further research is needed for a better interpretation of ATI patterns in complex thermophysical conditions.
Tenth International Conference on Permafrost (TICOP), Jan 1, 2012
Permafrost is one of the essential climate variables addressed by the Global Terrestrial Observin... more Permafrost is one of the essential climate variables addressed by the Global Terrestrial Observing System (GCOS). Remote sensing data provide area-wide monitoring of e.g. surface temperatures or soil surface status (frozen or thawed state) in the Arctic and Subarctic, where ground data collection is difficult and restricted to local measurements at few monitoring sites. The task of the ESA Data User Element (DUE) Permafrost project is to build-up an Earth observation service for northern high-latitudinal permafrost applications with extensive involvement of the international permafrost research community (www.ipf.tuwien.ac.at/permafrost). The satellite-derived DUE Permafrost products are Land Surface Temperature, Surface Soil Moisture, Surface Frozen and Thawed State, Digital Elevation Model (locally as remote sensing product and circumpolar as non-remote sensing product) and Subsidence, and Land Cover. Land Surface Temperature, Surface Soil Moisture, and Surface Frozen and Thawed State will be provided for the circumpolar permafrost area north of 55° N with 25 km spatial resolution. In addition, regional products with higher spatial resolution were developed for five case study regions in different permafrost zones of the tundra and taiga (Laptev Sea [RU], Central Yakutia [RU], Western Siberia [RU], Alaska N-S transect, [US] Mackenzie River and Valley [CA]). This study shows the evaluation of two DUE Permafrost regional products, Land Surface Temperature and Surface Frozen and Thawed State, using freely available ground truth data from the Global Terrestrial Network of Permafrost (GTN-P) and monitoring data from the Russian-German Samoylov research station in the Lena River Delta (Central Siberia, RU). The GTN-P permafrost monitoring sites with their position in different permafrost zones are highly qualified for the validation of DUE Permafrost remote sensing products. Air and surface temperatures with high-temporal resolution from eleven GTN-P sites in Alaska and four sites in Siberia were used to match up LST products. Daily average GTN-P borehole- and air temperature data for three Alaskan and six Western Siberian sites were used to evaluate surface frozen and thawed. First results are promising and demonstrate the great benefit of freely available ground truth databases for remote sensing derived products.
The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (... more The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (25 km resolution) scales include weekly and monthly averages from 2000 to 2010 from which annual averages can also be calculated. The LST processing integrates the LST level 2 products from MODIS and AATSR distributed by NASA and ESA, respectively. Post-processing functions supply University Waterloo-level-3 weekly and monthly LST products for regional (1 km) and pan-Arctic (25 km) scales. Thepan-Arctic product, with a spatial resolution of 25 km, is produced by spatial averaging of 1-km observations.
MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products.
Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest.
Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds.
Knowledge about the freeze/thaw state of the surface is of major importance for climate modelling... more Knowledge about the freeze/thaw state of the surface is of major importance for climate modelling, hydrology and numerous other applications. In this study, a freeze/thaw state detection algorithm using the ASCAT scatterometer is compared to Land Surface Temperature (LST) from MODIS as well as to a product derived from ENVISAT ASAR data. Good agreement with the LST product was found over the study area in Northern Siberia with disagreement below 22% for all 8-day periods of 2007. SAR derived surface status can, if sufficient sampling is available, provide similar results as with ASCAT but even with higher spatial detail.
The task of the ESA Data User Element (DUE) Permafrost project is to build up an Earth Observatio... more The task of the ESA Data User Element (DUE) Permafrost project is to build up an Earth Observation service for permafrost applications with extensive involvement of the permafrost research community. The DUE Permafrost remote sensing products are ‘Land Surface Temperature’ (LST), ‘Surface Soil Moisture’ (SSM), ‘Frozen/ Thawed Surface Status’ (Freeze/Thaw), ‘Terrain’, ‘Land Cover’ (LC), and ‘Surface Waters’. A major component is the evaluation of the DUE Permafrost products to test their scientific validity for high-latitude permafrost landscapes. There are no standard evaluation methods for this range of remote sensing products, specifically not for these latitudes. Evaluation experiments and inter-comparison is done on a case-by-case basis, adding value and experience in validating products for these regions. A significant challenge in the evaluation of remote sensing products for high-latitude permafrost landscapes are the very sparse ground data. We rely on ground data provided by the Users and by international programmes. The primary international programme is the Global Terrestrial Network for Permafrost (GTN-P) initiated by the International Permafrost Association (IPA). Leading projects are the networks of the ‘Circumpolar Active Layer Monitoring’ (CALM) and the ‘Thermal State of Permafrost’ (TSP). Prime sites for testing methods and scaling are the long-term Russian-German Samoylov Station in the Lena River Delta (Arctic Siberia), and the tundra and taiga-tundra transition regions in Western Siberia (RU). The results of the first evaluations of LST, SSM and Freeze/ Thaw using GTN-P and User’s data show the usability of the DUE Perma-frost products for high-latitude permafrost landscapes.
The DUE Permafrost remote sensing products will be adapted as drivers, validation data and as newly available external input data for permafrost and climate models.
Thermal remote sensing of soil moisture in vineyards is a challenge. The
grass-covered soil, in a... more Thermal remote sensing of soil moisture in vineyards is a challenge. The grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and thermal inertia calculated from the drop of surface temperature during a clear sky night over a vineyard in the Niagara region. We utilized data from two sensors, an airborne thermal camera (height ≈ 500 m a.g.l.) and a handheld thermal gun (height ≈ 1 m a.g.l.), to explore the effects of different field of views and the high inter-row temperature variability. Spatial patterns of soil moisture correlated more with estimated thermal inertia than with surface temperature recorded at sunrise or sunset. Despite the coarse resolution of airborne thermal inertia images, it performed better than estimates from the handheld thermal gun. Between-row variation was further analyzed using a linear mixed-effects model. Despite the limited spatial variability of soil properties within a single vineyard, the magnitudes of the model coefficients for soil moisture and mechanical resistance are encouraging indicators of the utility of thermal inertia in vineyard management.
International Journal of Applied Earth Observation and Geoinformation, 2011
Principal component analysis has been applied to remote sensing data to identify spatiotemporal p... more Principal component analysis has been applied to remote sensing data to identify spatiotemporal patterns in a time series of images. Thermal inertia is a surface property that relates well to shallow surface thermal and physical properties. Mapping thermal inertia requires quantifying surface energy balance components and soil heat flux, both of which are difficult to measure remotely. This article describes a method to map soil thermal inertia using principal component analysis applied to a time series of thermal infrared images and it also assesses how sensitive this method is to the time intervals between images. Standardized principal component analysis (SPCA) was applied to thermal infrared images captured at half-hour intervals during a complete diurnal cycle. Shallow surface thermal properties accounted for 45%, 82% and 66% of the spatiotemporal variation in surface temperature observed during the heating phase, cooling phase and over the total diurnal cycle respectively. The remaining 55%, 18% and 34% of the variation was attributed to transient effects such as shadows, surface roughness and background noise. Signals related to thermal inertia explained 18% of total variation observed in a complete diurnal cycle and 7% of variation in the cooling series. The SPCA method was found useful to separate critical information such as timing and amplitude of maximum surface temperature variation from delays related to differential heating induced by micro-topography. For the field conditions experienced in this study, decreased temporal resolution when sampling intervals were greater than an hour significantly reduced the quality of results.
Surface crusts represent a major limitation for reclamation projects in arid regions.With the adv... more Surface crusts represent a major limitation for reclamation projects in arid regions.With the advancements in spatial and radiometric resolution, infrared thermography is a potential technique for non-destructive characterization of soil crusts. The objective of this study is to evaluate time-resolved thermography, within the context of the composition by XRD, and configuration, by X-ray CT, of intact soil crust samples. Three samples were obtained from Dara region, west Gulf of Suez, the Eastern Egyptian Desert, representing the surface crusts formed in the Dara piedmont plain and Dara dry valley, as well as bedrock specimen found deep in Dara piedmont plain soil profiles. A step-heating test was applied to all samples with duration of 420 min. Temperate–time plots indicate that surface temperature reached an approximate temperature of 60 °C for all three samples after being heated for 270 min, the minimum surface temperature (58.3 °C) was obtained for the bedrock specimen because of large quartz content (64%) and weak development of pore space (1.3% of total volume). The slope of the early linear phase of temperature plotted against the square root of time was found to be steeper in the case of Dara piedmont plain and valley crust specimens (3.82, 3.84, respectively) than the slope obtained by scanning the bedrock specimen (3.32). Remarkably, despite the differences in composition of surface crust found in the Dara piedmont plain and valley, their surface temperature patterns were found to be similar. The similarity in thermal response is explained by the overlap in estimated thermal inertia range from the XRD and X-ray CT data. This final result demonstrates that the results of time-resolved thermography technique are not self-exploratory and ancillary data such as X-ray CT is needed for interpretation.
" Models and observations show that the Arctic is experiencing the most rapid changes in global n... more " Models and observations show that the Arctic is experiencing the most rapid changes in global near-surface air temperature. We developed novel EASE-grid Level 3 (L3) land surface temperature (LST) products from Level 2 (L2) AATSR and MODIS data to provide weekly, monthly and annual LST means over the pan-Arctic region at various grid resolutions (1–25 km) for the past decade (2000–2010). In this paper, we provide: (1) a review of previous validation of MODIS/AATSR L2; (2) a description of the
processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max:
−1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions."
Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditio... more Remote sensors face challenges in characterizing mountain permafrost and ground thermal conditions or mapping rock glaciers and debris-covered glaciers. We explore the potential of thermal imaging and in particular thermal inertia mapping in mountain cryospheric research, focusing on the relationships between ground surface temperatures and the presence of ice-debris landforms on one side and land surface temperature (LST) and apparent thermal inertia (ATI) on the other. In our case study we utilize ASTER daytime and nighttime imagery and in-situ measurements of near-surface ground temperature (NSGT) in the Mediterranean Andes during a snow-free and dry observation period in late summer. Spatial patterns of LST and NSGT were mostly consistent with each other both at daytime and at nighttime. Daytime LST over ice-debris landforms was decreased and ATI consequently increased compared to other debris surfaces under otherwise equal conditions, but NSGT showed contradictory results, which underlines the complexity and possible scale dependence of ATI in heterogeneous substrates with the presence of a thermal mismatch and a heat sink at depth. While our results demonstrate the utility of thermal imaging and ATI mapping in a mountain cryospheric context, further research is needed for a better interpretation of ATI patterns in complex thermophysical conditions.
Tenth International Conference on Permafrost (TICOP), Jan 1, 2012
Permafrost is one of the essential climate variables addressed by the Global Terrestrial Observin... more Permafrost is one of the essential climate variables addressed by the Global Terrestrial Observing System (GCOS). Remote sensing data provide area-wide monitoring of e.g. surface temperatures or soil surface status (frozen or thawed state) in the Arctic and Subarctic, where ground data collection is difficult and restricted to local measurements at few monitoring sites. The task of the ESA Data User Element (DUE) Permafrost project is to build-up an Earth observation service for northern high-latitudinal permafrost applications with extensive involvement of the international permafrost research community (www.ipf.tuwien.ac.at/permafrost). The satellite-derived DUE Permafrost products are Land Surface Temperature, Surface Soil Moisture, Surface Frozen and Thawed State, Digital Elevation Model (locally as remote sensing product and circumpolar as non-remote sensing product) and Subsidence, and Land Cover. Land Surface Temperature, Surface Soil Moisture, and Surface Frozen and Thawed State will be provided for the circumpolar permafrost area north of 55° N with 25 km spatial resolution. In addition, regional products with higher spatial resolution were developed for five case study regions in different permafrost zones of the tundra and taiga (Laptev Sea [RU], Central Yakutia [RU], Western Siberia [RU], Alaska N-S transect, [US] Mackenzie River and Valley [CA]). This study shows the evaluation of two DUE Permafrost regional products, Land Surface Temperature and Surface Frozen and Thawed State, using freely available ground truth data from the Global Terrestrial Network of Permafrost (GTN-P) and monitoring data from the Russian-German Samoylov research station in the Lena River Delta (Central Siberia, RU). The GTN-P permafrost monitoring sites with their position in different permafrost zones are highly qualified for the validation of DUE Permafrost remote sensing products. Air and surface temperatures with high-temporal resolution from eleven GTN-P sites in Alaska and four sites in Siberia were used to match up LST products. Daily average GTN-P borehole- and air temperature data for three Alaskan and six Western Siberian sites were used to evaluate surface frozen and thawed. First results are promising and demonstrate the great benefit of freely available ground truth databases for remote sensing derived products.
The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (... more The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (25 km resolution) scales include weekly and monthly averages from 2000 to 2010 from which annual averages can also be calculated. The LST processing integrates the LST level 2 products from MODIS and AATSR distributed by NASA and ESA, respectively. Post-processing functions supply University Waterloo-level-3 weekly and monthly LST products for regional (1 km) and pan-Arctic (25 km) scales. Thepan-Arctic product, with a spatial resolution of 25 km, is produced by spatial averaging of 1-km observations.
MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products.
Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest.
Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds.
Knowledge about the freeze/thaw state of the surface is of major importance for climate modelling... more Knowledge about the freeze/thaw state of the surface is of major importance for climate modelling, hydrology and numerous other applications. In this study, a freeze/thaw state detection algorithm using the ASCAT scatterometer is compared to Land Surface Temperature (LST) from MODIS as well as to a product derived from ENVISAT ASAR data. Good agreement with the LST product was found over the study area in Northern Siberia with disagreement below 22% for all 8-day periods of 2007. SAR derived surface status can, if sufficient sampling is available, provide similar results as with ASCAT but even with higher spatial detail.
The task of the ESA Data User Element (DUE) Permafrost project is to build up an Earth Observatio... more The task of the ESA Data User Element (DUE) Permafrost project is to build up an Earth Observation service for permafrost applications with extensive involvement of the permafrost research community. The DUE Permafrost remote sensing products are ‘Land Surface Temperature’ (LST), ‘Surface Soil Moisture’ (SSM), ‘Frozen/ Thawed Surface Status’ (Freeze/Thaw), ‘Terrain’, ‘Land Cover’ (LC), and ‘Surface Waters’. A major component is the evaluation of the DUE Permafrost products to test their scientific validity for high-latitude permafrost landscapes. There are no standard evaluation methods for this range of remote sensing products, specifically not for these latitudes. Evaluation experiments and inter-comparison is done on a case-by-case basis, adding value and experience in validating products for these regions. A significant challenge in the evaluation of remote sensing products for high-latitude permafrost landscapes are the very sparse ground data. We rely on ground data provided by the Users and by international programmes. The primary international programme is the Global Terrestrial Network for Permafrost (GTN-P) initiated by the International Permafrost Association (IPA). Leading projects are the networks of the ‘Circumpolar Active Layer Monitoring’ (CALM) and the ‘Thermal State of Permafrost’ (TSP). Prime sites for testing methods and scaling are the long-term Russian-German Samoylov Station in the Lena River Delta (Arctic Siberia), and the tundra and taiga-tundra transition regions in Western Siberia (RU). The results of the first evaluations of LST, SSM and Freeze/ Thaw using GTN-P and User’s data show the usability of the DUE Perma-frost products for high-latitude permafrost landscapes.
The DUE Permafrost remote sensing products will be adapted as drivers, validation data and as newly available external input data for permafrost and climate models.
Thermal remote sensing of soil moisture in vineyards is a challenge. The
grass-covered soil, in a... more Thermal remote sensing of soil moisture in vineyards is a challenge. The grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and thermal inertia calculated from the drop of surface temperature during a clear sky night over a vineyard in the Niagara region. We utilized data from two sensors, an airborne thermal camera (height ≈ 500 m a.g.l.) and a handheld thermal gun (height ≈ 1 m a.g.l.), to explore the effects of different field of views and the high inter-row temperature variability. Spatial patterns of soil moisture correlated more with estimated thermal inertia than with surface temperature recorded at sunrise or sunset. Despite the coarse resolution of airborne thermal inertia images, it performed better than estimates from the handheld thermal gun. Between-row variation was further analyzed using a linear mixed-effects model. Despite the limited spatial variability of soil properties within a single vineyard, the magnitudes of the model coefficients for soil moisture and mechanical resistance are encouraging indicators of the utility of thermal inertia in vineyard management.
International Journal of Applied Earth Observation and Geoinformation, 2011
Principal component analysis has been applied to remote sensing data to identify spatiotemporal p... more Principal component analysis has been applied to remote sensing data to identify spatiotemporal patterns in a time series of images. Thermal inertia is a surface property that relates well to shallow surface thermal and physical properties. Mapping thermal inertia requires quantifying surface energy balance components and soil heat flux, both of which are difficult to measure remotely. This article describes a method to map soil thermal inertia using principal component analysis applied to a time series of thermal infrared images and it also assesses how sensitive this method is to the time intervals between images. Standardized principal component analysis (SPCA) was applied to thermal infrared images captured at half-hour intervals during a complete diurnal cycle. Shallow surface thermal properties accounted for 45%, 82% and 66% of the spatiotemporal variation in surface temperature observed during the heating phase, cooling phase and over the total diurnal cycle respectively. The remaining 55%, 18% and 34% of the variation was attributed to transient effects such as shadows, surface roughness and background noise. Signals related to thermal inertia explained 18% of total variation observed in a complete diurnal cycle and 7% of variation in the cooling series. The SPCA method was found useful to separate critical information such as timing and amplitude of maximum surface temperature variation from delays related to differential heating induced by micro-topography. For the field conditions experienced in this study, decreased temporal resolution when sampling intervals were greater than an hour significantly reduced the quality of results.
Surface crusts represent a major limitation for reclamation projects in arid regions.With the adv... more Surface crusts represent a major limitation for reclamation projects in arid regions.With the advancements in spatial and radiometric resolution, infrared thermography is a potential technique for non-destructive characterization of soil crusts. The objective of this study is to evaluate time-resolved thermography, within the context of the composition by XRD, and configuration, by X-ray CT, of intact soil crust samples. Three samples were obtained from Dara region, west Gulf of Suez, the Eastern Egyptian Desert, representing the surface crusts formed in the Dara piedmont plain and Dara dry valley, as well as bedrock specimen found deep in Dara piedmont plain soil profiles. A step-heating test was applied to all samples with duration of 420 min. Temperate–time plots indicate that surface temperature reached an approximate temperature of 60 °C for all three samples after being heated for 270 min, the minimum surface temperature (58.3 °C) was obtained for the bedrock specimen because of large quartz content (64%) and weak development of pore space (1.3% of total volume). The slope of the early linear phase of temperature plotted against the square root of time was found to be steeper in the case of Dara piedmont plain and valley crust specimens (3.82, 3.84, respectively) than the slope obtained by scanning the bedrock specimen (3.32). Remarkably, despite the differences in composition of surface crust found in the Dara piedmont plain and valley, their surface temperature patterns were found to be similar. The similarity in thermal response is explained by the overlap in estimated thermal inertia range from the XRD and X-ray CT data. This final result demonstrates that the results of time-resolved thermography technique are not self-exploratory and ancillary data such as X-ray CT is needed for interpretation.
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Papers by Aiman Soliman
processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max:
−1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions."
MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products.
Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest.
Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds.
The DUE Permafrost remote sensing products will be adapted as drivers, validation data and as newly available external input data for permafrost and climate models.
grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and thermal inertia calculated from the drop of surface temperature during a clear sky night over a vineyard in the Niagara region. We utilized data from two sensors, an airborne thermal camera (height ≈ 500 m a.g.l.) and a handheld thermal gun (height ≈ 1 m a.g.l.), to explore the effects of different field of views and the high inter-row temperature variability. Spatial patterns of soil moisture correlated more with estimated thermal inertia than with surface temperature recorded at sunrise or sunset. Despite the coarse resolution of airborne thermal inertia images, it performed better than estimates from the handheld thermal gun. Between-row variation was further analyzed using a linear mixed-effects model. Despite the limited spatial variability of soil properties within a single vineyard, the magnitudes of the model coefficients for soil moisture and mechanical resistance are encouraging indicators of the utility of thermal inertia in vineyard management.
processing chain of L3 products; (3) an assessment of the 25 km products uncertainty, and; (4) a quantification of the bias introduced by over-representing clear-sky days in MODIS L3 products. In addition, we generated uncertainty maps by comparing L3 products with LST from passive microwave sensors (AMSR-E and SSM/I) and the North American Regional Reanalysis (NARR). Results show a close correspondence between MODIS and AATSR monthly products with a mean-difference (MD) of −1.1 K. Comparing L3 products with NARR indicates a close agreement in summer and a systematic bias in winter, which is entirely negative with respect to MODIS L3 (MD: −3.6, Min: −6.8, Max:
−1 K). Comparing monthly averaged MODIS L3 to NARR clear-sky to quantify over-representing clear-sky days indicates a decrease of winter and an increase of summer difference compared to NARR all-sky. Finally, we provide suggestions to improve LST retrieval over Arctic regions."
MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products.
Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest.
Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds.
The DUE Permafrost remote sensing products will be adapted as drivers, validation data and as newly available external input data for permafrost and climate models.
grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and thermal inertia calculated from the drop of surface temperature during a clear sky night over a vineyard in the Niagara region. We utilized data from two sensors, an airborne thermal camera (height ≈ 500 m a.g.l.) and a handheld thermal gun (height ≈ 1 m a.g.l.), to explore the effects of different field of views and the high inter-row temperature variability. Spatial patterns of soil moisture correlated more with estimated thermal inertia than with surface temperature recorded at sunrise or sunset. Despite the coarse resolution of airborne thermal inertia images, it performed better than estimates from the handheld thermal gun. Between-row variation was further analyzed using a linear mixed-effects model. Despite the limited spatial variability of soil properties within a single vineyard, the magnitudes of the model coefficients for soil moisture and mechanical resistance are encouraging indicators of the utility of thermal inertia in vineyard management.