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ID: 61867
Title: Soil Organic Carbon Stocks under different Forest Types in India.
Author: T.P.Singh, R.S.Rawat, V.R.S.Rawat and M.K.Gupta
Editor: Kunal Satyarthi
Year: 2016
Publisher: Indian Council of Forestry Research & Education.
Source: EWRG, CES
Reference: The Indian Forester Vol. 142 (3) 207-212 (2016)
Subject: The Indian Forester
Keywords: Soil organic carbon stock, Forests, Forest types, India.
Abstract: India has stabilized its forest and tree cover which is about 24.01 per cent of its total geographic area. Forests store significant amounts of carbon in its biomass, litter, dead woods and soil; and it has a major role in climate change adaptation and mitigation. Soil carbon is the largest terrestrial carbon pool and it holds a very important role in the carbon cycle. Soil samples were collected from all major forest types in different parts of the country as well as from adjoining non-forest areas for estimating the loss of soil organic carbon due to land conversion. The results of this study indicated that maximum soil organic carbon stock was under tropical moist deciduous forests (1665.65 million tonnes) followed by tropical dry deciduous forests (1572.38 million tonnes) and least under Himalayan dry temperate forests (3.85 million tones.). The total soil organic carbon stocks i.e., 4327.36 million tones and 4680.25 million tonnes were estimated under the forests in the year 1995 and 2007 respectively. The estimate showed that due to increase in forest cover during the assessment period, soil in Indian forests acted as a net sink of 352.89 million tones of soil organic carbon. The maximum increase in soil organic carbon stock during this period was under tropical moist deciduous forests (125.91 million tonnes) and the least increase was under Himalayan dry temperate forests (0.23 million tonnes).
Location: T E 15 New Biology Building
Literature cited 1: Batjes N.H. (1996). Total carbon and nitrogen in the soils of the world.Euro.J.Soil Sci., 47:151-163. Champion H.G. and Seth S.K. (1968).A revised survey of forest types of India. Manager of Publications, Delhi.
Literature cited 2: Chhabra A.and Dadhwal V.K. (2005).Forest soil organic carbon pool-an estimate and review of Indian studies. Indian Forester, 131 (2): 201-214. Dadhwal V.K.and Nayak S.R. (1993).A preliminary estimate of bio-geochemical cycle of carbon for India. Science and Culture, 59 (1&2):9-13.

ID: 61866
Title: Spatio-temporal evaluation of resolution enhancement for passive microwave soil moisture and vegetation optical depth.
Author: A.I.Gevaert, R.M.Parinussa, L.J.Renzullo, A.I.J.M. vanDijk, R.A.M. de jeu
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 235-244 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Soil moisture, Vegetation optical depth, Resolution enhancement, Passive microwave radiometry, Remote sensing.
Abstract: Space-borne passive microwave radiometers are used to derive land surface parameters such as surface soil moisture and vegetation optical depth (VOD).However, the value of such products in regional hydrology is limited by their coarse resolution. In this study, the land parameter retrieval model (LPRM) is used to derive enhanced resolution (~10 km) soil moisture and VOD from advanced microwave scanning radiometer(AMSR-E) brightness temperatures sharpened by a modulation technique based on high-frequency observations. A precipitation mask based on brightness temperatures was applied to remove precipitation artefacts in the sharpened LPRM products. The spatial and temporal patterns in the resulting products are evaluated against field-measured and modeled soil moisture as well as the normalized difference vegetation index (NDVI) over mainland Australia. Results show that resolution enhancement accurately sharpens the boundaries of different vegetation types, lakes and wetlands. Significant changes in temporal agreement between LPRM products and related datasets are limited to specific areas, such as lakes and coastal areas. Spatial correlations, on the other hand, increase over most of Australia. In addition, hydrological signals from irrigation and water bodies that were absent in the low-resolution soil moisture product become clearly visible after resolution enhancement. The increased information detail in the high-resolution LPRM products should benefit hydrological studies at regional scales.
Location: T E 15 New Biology Building
Literature cited 1: Andela, N.Liu, Y.Y., van Dijk,A.I.J.M., de Jeu,R.A.M., McVicar, T.R., 2013.Global Changes in dryland vegetation dynamics (1988-2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data.Biogeosciences 10, 6657-6676, http://dx.doi.org/10.5194/bg-10-6657-2013. Ashcroft, P., Wentz, F.J., 2013.AMSR-E/Aqua L2A Global Swath Spatially-Resampled Brightness Temperatures.Boulder, CO, USA, Version 3.
Literature cited 2: ASRIS, 2011.ASRIS-Australian Soil Resource Information System, [online] Available from: < http://www.asris.csiro.au> (accessed 12.12.14.) Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martinez-Fernandez, J., Llorens, P., Latron, J., Martin, C., Bittelli, M., 2011.Soil moisture estimation through ASCAT and AMSR-Esensors: an intercomparisonand validation study across Europe. Remote Sens.Environ. 115 (12), 3390-3408, http:/dx.doi.org/10.1016/j.rse.2011.08.003.

ID: 61865
Title: DisPATCH as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia.
Author: Yoann Malbeteau, Olivier Merlin, Beatriz Molero, Christoph Rudiger, Stephan Bacon.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 221-234 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Disaggregation, Soil moisture, Validation, SMOS, AMSR-E, DisPATCh.
Abstract: Validating coarse-scale satellite soil moisture data still represents a big challenge, notably due to the large mismatch existing between the spatial resolution (>10km) of microwave radiometers and the representativeness scale (several m) of localized in situ measurements. This study aims to examine the potential of DisPATCh (Disaggregation based on Physical and Theoretical scale Change) for validating SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer-Earth observation system) level-3 soil moisture products. The ~ 40-50 km resolution SMOS and AMSR-E data are disaggregated at 1 km resolution over the Murrumbidgee catchment in Southeastern Australia during a one year period in 2010-2011, and the satellite products are compared with the in situ measurements of 38 stations distributed within the study area. It is found that disaggregation improves the mean difference, correlation coefficient and slope of the linear regression between satellite and in situ data in 77 %, 92 % and 94% of cases, respectively. Nevertheless, the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. Consistently, better results are obtained in the semi-arid than in a temperate zone of the catchment. In the semi-arid Yanco region, disaggregation in summer increases the correlation coefficient from 0.63 to 0.78 and from 0.42 to 0.71 for SMOS and AMSR-E in morning overpasses and from 0.37 to 0.63 and from 0.47 to 0.73 for SMOS and AMSR-E in afternoon overpasses, respectively. DisPATCh has strong potential in low vegetated semi-arid areas where it can be used as a tool to evaluate coarse-scale remotely sensed soil moisture by explicitly representing the sub-pixel variability.
Location: T E 15 New Biology Building
Literature cited 1: Bandara, R., Walker, J.P., Rudiger, C., Merlin, O., 2015.Towards soil property retrieval from space: an application with disaggregated satellite observations.J.Hydrol.522, 582-593 http://linkinghub.elsevier.com/retrieve/pii/S0022169415000359. Bindlish, R., Jackson, T.J., Gasiewski, A.J., Klein, M., Njoku, E.G., 2006.Soil moisture mapping and AMSR-Evalidation using the PSR in SMEX02.Remote Sens.Environ.103, 127-139.
Literature cited 2: Carlson, T.N., Gillies, R.R., Perry, E.M., 1994.A method to make use o thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote Sens.Rev.9 (March (1-2), 161-173, http://dx.doi.org/10.1080/02757259409532220. Chauhan, N.S., Miller, S., Ardanuy, P., 2003. Spaceborne soil moisture estimation at high resolution: a microwave-optical /IR synergistic approach.Int.J.Remote Sens.24 (January (22), 4599-4622, http:dx.doi.org/10.1080/0143116031000156837.

ID: 61864
Title: Impact of sub-pixel heterogeneity on modeled brightness temperature for an agricultural region.
Author: Swapan Kumar Roy, Tracy L.Rowlandson, Aaron A. Berg, Catherine Champagne, Justin R. Adams.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 212-220 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Sub-pixel heterogeneity, Passive microwave remote sensing, Surface soil moisture, Simultaneous heat and water model.
Abstract: Knowledge of sub-pixel heterogeneity, particularly at the passive microwave scale, can improve the brightness temperature (and ultimately the soil moisture) estimation. However, the impact of surface heterogeneity (in terms of soil moisture, soil temperature and vegetation water content) on brightness temperature in an agricultural setting is relatively unknown. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX 12) provided an opportunity to evaluate sub-pixel heterogeneity at the scale of a Soil Moisture Ocean Salinity (SMOS) or the Soil Moisture Active Passive (SMAP) radiometer footprint using field measured data. The first objective of this study was to determine if accounting for surface heterogeneity reduced the error between estimated brightness temperature (Tb) and Tb measured by SMOS. It was found that when accounting for variation in surface soil moisture, temperature and vegetation water content within the pixel footprint, the error between the modelled Tb and the measured Tb was less than if a homogeneous pixel were modeled. The correlation between the surface parameters and the error associated with not accounting for surface heterogeneity were investigated. It was found that there was low to moderate correlation between the error and the coefficient of variance associated with the measured soil moisture, soil temperature and vegetation volumetric water content during the field campaign. However, it was found that the correlation changed depending on the stage of vegetation growth and the amount of time following a precipitation event close to the middle of the field campaign (during which there was rapid growth in vegetation),there was strong correlation between error and the variability in vegetation water content (r = 0.89), moderate correlation with soil moisture (r =0.61) and low correlation with soil temperature (r = 0.26).
Location: T E 15 New Biology Building
Literature cited 1: AAFC, 2010.Soil Landscapes of Canada ver 3.2.SoilLandscapes of Canada Working Group, Agriculture and Agri-Food Canada, http: sis.agr.gc.ca/cansis/nsdb/slc/v3.2/index.html. Allen, R.G.,Pereira, L.S., Raes, D., Smith, M., 1998.Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements.FAO Irrigation and Drainage Paper 56, Rome Italy, pp.161-181.
Literature cited 2: Bevis, M., Businger, S., Herring, T.A., Rocken, C., Anthes, R.A., Ware, R.H., 1992.GPS Meteorology: Remote sensing of atmospheric water vapor using the global position system.J.Geophys.Res 97 (D14), 787-801. Campbell, G.S., Norman, J.M., 2000.An Introduction to Environmental Biophysics, 2nd ed.Springer-Verlag, Inc, New York (Chapters 5, 9).

ID: 61863
Title: Recent advances in (soil moisture) triple collocation analysis.
Author: A.Gruber, C.-H.Su, S.Zweieback, W.Crow, W.Dorigo, W.Wagner.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 200-211 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Soil moisture, Error moisture, Error characterization, Validation, Triple collocation.
Abstract: To date, triple collocation (TC) analysis is one of the most important methods for the global-scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method. Different nations that are used to formulate the TC problem are shown to be mathematically identical. While many studies have investigated issues related to possible violations of the underlying assumptions, only few TC modifications have been proposed to mitigate the impact of these violations. Moreover, assumptions, which are often understood as a limitation that is unique to TC analysis are shown to be common also to other conventional performance metrics. Noteworthy advances in TC analysis have been made in the way error estimates are being presented by moving from the investigation of absolute error variance estimates to the investigation of signal-to-noise ratio (SNR) metrics. Here we review existing error presentations and propose the combined investigation o the SNR (expressed in logarithmic units), the unscaled error variances, and the soil moisture sensitivities of the data sets as optimal strategy for the evaluation of remotely-sensed soil moisture data sets.
Location: T E 15 New Biology Building
Literature cited 1: Bowden, R.J., Turkington, D.A., 1990.InstrumentalVariables, vol.8 Cambridge University Press. Caires, S., Sterl, A., 2003.Validation of ocean wind and wave data using triple collocation. J. Geophys. Res: Oceans (1978-2012), 108.
Literature cited 2: Crow, W., Van den Berg, M., 2010.An improved approach for estimating observation and model error parameters in soil moisture data assimilation. Water Resour.Res.46 Crow,W.T., Berg,A.A., Cosh, M.H., Loew, A.,Mohanty, B.P., Panciera, R., de Rosnay, P., Ryu, D., Walker, J.P., 2012.Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products.Rev.Geophys.50, RG2002, http://dx.doi.org/10.1029/2011RG000372.

ID: 61862
Title: Evaluation of AMSR2 soil moisture products over the contiguous United States using in situ data from the International Soil Moisture Network.
Author: Qiusheng Wu, Hongxing, Liu, Lei Wang, Chengbin Deng.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 187-199 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: AMSR2, Soil moisture, Passive microwave, Remote sensing, International Soil Moisture Network.
Abstract: High quality soil moisture datasets are required for various environmental applications. The launch of the Advanced Microwave Scanning Radiometer2 (AMSR2) onboard the Global Change Observation Mission 1-Water (GCOM-W1) in May 2012 has provided global near-surface soil moisture data, with an average revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very revisit frequency of two days. Since AMSR2 is a new passive microwave system in operation, it is very important to evaluate the quality of AMSR2 products before widespread utilization of the data for scientific research. In this paper, we provide a comprehensive evaluation of the AMSR2 soil moisture products retrieved by the Japan Aerospace Exploration Agency (JAXA) algorithm. The evaluation was performed for a three-year period (July 2012-June 2015) over the contiguous United States. The AMSR2 soil moisture products were evaluated by comparing ascending and descending overpass products to each other as well as comparing them to in situ soil moisture observations of 598 monitoring stations obtained from the International Soil Moisture Network (ISMN).The accuracy of AMSR2 soil moisture product was evaluated against several types of monitoring networks, and for different land cover types and ecoregions. Three performance metrics, including mean difference (MD), root mean squared difference (RMSD), and correlation coefficient (R), were used in our accuracy assessment. Our evaluation results revealed thatAMSR2 soil moisture retrievals are generally lower than in situ measurements. The AMSR2 soil moisture retrievals showed the best agreement with in situ measurements over the Great Plains and the worst agreement over forested areas. This study offers insights into the suitability and reliability represent useful and effective measurements for some regions, further studies are required to improve the data accuracy.
Location: T E 15 New Biology Building
Literature cited 1: Al-Yaari, A., Wigneron, J.P.,Ducharne, A., Kerr, Y.,de Rosnay, P., de Jeu, R., Govind, A., Al Bitar, A.,Albergel ,C., Munoz-Sabater, J., Richaume, P.,Mialon,A., 2014. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates. Remote Sens.Environ.149, 181-195.
Literature cited 2: Abergel, C., Dorigo, W., Reichle,R.H.,Balsamo, G., Derosnay,P., Munoz-Sabater,J.,Isaksen, L., Dejeu,R.,Wagner,W.,2013.Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing.J.Hydrometeorol.14, 1259-1277. Bell, J.E., Palecki, M.A., Baker, C.B., Collins, W.G., Lawrimore, J.H., Leeper, R.D., Hall M.E., Kochendorfer, J., Meyers, T.P., Wilson, T., 2013.U.S.Climate Reference Network soil moisture and temperature observations.J.Hydrometeorol.14,977-988.

ID: 61861
Title: Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data.
Author: D.C.Mason, J.Garcia-Pintado, H.L.Cloke, S.L.Dance.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 178-186 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Soil moisture, Synthetic aperture radar, Hydrologic model.
Abstract: The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30-90 %, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.
Location: T E 15 New Biology Building
Literature cited 1: Aubert, D., Loumagne, C., Oudin, L., 2003.Sequenbtial assimilation of soil moisture and stream flow data in a conceptual rainfall-runoff model.J.Hydrol.280, 145-161. Balenzano, A., Mattia, F., Satalino, G., Davidson, M.W., J., 2011.Dense temporal series of C-band SAR data for soil moisture retrieval over agricultural crops.IEEE.J.STARS 4 (2), 439-450.
Literature cited 2: Barrett, B.W., Dwyer, E., Whelan, P., 2009.Soilmoisture retrieval from active sopaceborne microwave observations: an evaluation of current techniques. Remote Sens.1 (3), 210-242. Beven, K.J., Kirkby, M.J., Siebert, J., 1979.A physically based: variable contributing area model of basin hydrology.Hydrol.Sci.Bull.24, 43-69.

ID: 61860
Title: Aquarius L-band scatterometer and radiometer observations over a Tibetan Plateau site.
Author: Qiang Wang, Rogier van der Velde, Zhongbo Su, Jun Wen
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 P. (B) 165-177 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Aquarius, soil moisture, Observation modeling, Tibetan Plateau.
Abstract: In this paper, the impact of freeze-thaw, soil moisture and vegetation on L-band backscatter and emission is studied using Aquarius scatterometer/radiometer measurements collected from August 2011 to May 2013 over the northeastern part of the Tibetan Plateau. The study are is Maqu region that holds a regional-scale monitoring network consisting of twenty soil moisture/temperature stations, which is selected as one of the core international Calibration/Validation (Cal/Val) sites for NASA ' s Soil Moisture Active Passive (SMAP) mission. Comparisons of Aquarius scatterometer/radiometer measurements with soil moisture recorded by capacitance probes installed at a 5-cm soil depth illustrate that (1) L-band microwave observations are also sensitive to the amount of liquid water in soil below freezing point, and of 0.3 m3m-3.Further effects of vegetation become directly noticeable only within passive microwave observations at moisture levels larger than 0.4 m3m-3. The impact of vegetation is studied in more detail through analysis of the Radar Vegetation Index (RVI).Although seasonal variability is captured, the dynamic range o the RVI is sufficient for a meaningful signal-to-noise. Further vegetation optical depth (T) is estimated using the (T-w) concept by reconstructing the Microwave Polariozation Difference Index (MPDI) derived from Aqurius radiometer data. Peaks in the T estimates are noted in the months January. February and July/August. Evidence suggests that the magnitude of T is a measure for the frost depth when temperatures are below freezing point whereas the behavior of T in the warm season is in line with the vegetation dynamics.
Location: T E 15 New Biology Building
Literature cited 1: Abdel-Messeh, M., Quegan, S., 2001.Relating ERS scatterometer data to global vegetation models. In: ERS-ENVISAT Symposium ' Looking down to Earth in the New Millennium ' , 16-20 October 2000, Norodwijk, The Netherlands Altese, E., Bolognanai, O., Mancini, M., et al., 1996.Retrieving soil moisture over bare soil from ERS 1 synthetic aperture radar data: sensitivity analysis based on a theoretical surface scattering model and field data. Water Resour.Res. 32 (3), 653-661, http:/dx.doi.org/10.1029/95WRO3638.
Literature cited 2: Bindish,R., Jackson, T.J.,Wood ,E.F., et al., 2003.Soil moisture estimates from TRMM microwave imager observations over the Southern United States.IEEE Trans.Geosci.Remote Sens.85 (4),507-515, http: dx.doi.org/10.1016/SOO34-4257 (03) 52-X. Bruscantini, c.a., Crow, W.T., Grings, F., et al., 2014.An observing system simulation experiment for the Aquarius/SAC-D soil moisture product.IEEE Trans.Geosci.Remote Sens.52 (10), 1-9,http:dx.doi.org/10.1109/TGRS.2013.2294915.

ID: 61859
Title: Urban Revolution:Urbanisation Pattern and Environmental Sustainability Analysis of Major Cities in India
Author: Ramachandra T.V., Joshi NV, Bharath H.Aithal, Uttam Kumar, K.Venugopala Rao
Editor: T.V.Ramachandra
Year: 2016
Publisher: EWRG,CES
Source: EWRG, CES
Reference: Urban Revolution:Urbanisation Pattern and Environmental Sustainability Analysis of Major Cities in India (ISTC/BES/TVR/0313-Technical Report) 1-185 (2016)
Subject: Urban Revolution:Urbanisation Pattern and Environmental Sustainability Analysis of Major Cities in India
Keywords: Urban revolution,Urbanisation, Pattern,Environmental sustainability Analysis, Major cities, India
Abstract: In the next half century , ninety percent or more of global population growth will take place in the rapidly urbanizing areas of the developing world.The study during 2013-16,focussed on understanding urban dynamics using spatio-temporal data of 10 cities.Environmental data of 10 major Indian cities have been collected and analysed to estimate the carbon footprint of respective cities.
Location: T E 15 New Biology Building
Literature cited 1: None
Literature cited 2: None

ID: 61858
Title: Evaluation of satellite soil moisture products over Norway using ground-based observations.
Author: A.Griesfeller, W.A.Lahoz, R.A.M.de Jeu, W. Dorigo, L.E.Haugen, T.M.Svendby, W.Wagner.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 155-164 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Cal-val, In situ, Satellite, Soil moisture
Abstract: In this study we evaluate satellite soil moisture products from the advanced SCAT Terometer (ASCAT) and the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) over Norway using ground-based observations from the Norwegian water source an energy directorate. The ASCAT data are produced using the change detection approach of Wagner et al. (1999), and the AMSR-E data are produced using the VUA-NASA algorithm (Owe et al., 2001, 2008).Although satellite and ground-based soil moisture data for Norway have been available for several years, hitherto, such an evaluation has not been performed. This is partly because satellite measurements of soil moisture over Norway are complicated owing to the presence of snow, ice, water bodies, orography, rocks, and a very high coastline-to-area ratio. This work extends the European areas over which satellite soil moisture is validated to the Nordic regions. Owing to the challenging conditions for soil moisture measurements over Norway, the work described in this paper provides a stringent test of the capabilities of satellite and in situ data agree well, with averaged correlation ? values of 0.72 and 0.68 for ASCAT descending and ascending data vs in situ data, and 0.64 and 0.52 for AMSR-E descending and ascending data vs in situ data for the summer/autumn season (1 June-15 October), over a period of 3 years (2009-2011).This level of agreement indicates that, generally, the ASCAT and AMSAR-E soil moisture products over Norway have high quality, and would be useful for various applications, including land surface monitoring, weather forecasting, hydrological modeling, and climate studies. The increasing emphasis on coupled approaches to study the earth system, including the interactions between the land surface and the atmosphere, will benefit from availability of validated an improved soil moisture satellite datasets, including those over the Nordic regions.
Location: T E 15 New Biology Building
Literature cited 1: Albergel, C., Broca, L., Wagner, W., de Rosnay, P., Calvet, J.-C, 2013a.Selection of performance metrics for global soil moisture products: the case of ASCAT product. In: Petropoulos, G.P. (Ed.), Remote Sensing of Energy Fluxes and Soil Moisture Content.CRC Press, Boca Raton, pp.427-444. Albergel, C., Calvet, J.-C, de Rosnay, P., Balsamo, G., Wagner, W., Hasenauer, S., Naeimi, V., Martin, E., Bazile, E., Bouyssel, F., Mahfouf, J.,-F, 2010. Cross-evaluation of modeled and remotely sensed surface soil moisture within situ data in southwestern France.Hydrol.Earth Syst.Sci.14, 2177-2191, http://dx.doi.org/10.5194/hess-14-2177-2010.
Literature cited 2: Albergel, C., De Rosnay, P., Gruhier, C., Munoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., Wagner, W., 2012.Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sens.Environ.118, 215-226. Albergel, C., Dorigo, W., Riechle, R.H, Balsamo, G., De Rosnoy, P., Munoz-Sabater, J., Isaksen, L., De Leu, R., Wagner, W.,2013b.Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing.J.Hydrometeor.14, 1259-1277, http://dx.doi.org/10.1175/JHM-D-12-0161.1.

ID: 61857
Title: Satellite surface soil moisture from SMOS and Aquarius: Assessment for applications in agricultural landscapes.
Author: Catherine Champagne, Tracy Rowandson, Aaron Berg, Travis Burns, Jessika L ' Heureux, Erica Tetlock, Justin R.Adams, Heather McNairn, Brenda Toth, Daniel Itenfisu.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 143-154 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Soil moisture, Passive microwave, SMOS, Aquarius, Calibration, Validation, Agriculture.
Abstract: Satellite surface soil moisture has become more widely available in the past five years, with several missions designed specifically for soil moisture measurement now available, including the Soil Moisture and Ocean Salinity (SMOS) mission and Soil Moisture Active/Passive (SMAP) mission. With a wealth of data now available, the challenge is to understand the skill and limitations of the data so they can be used routinely to support monitoring applications and to better understand environmental change. This used routinely to support monitoring applications and to better understand environmental change. This paper examined two satellite surface soil moisture data sets from SMOS and Aquarius missions against in situ networks in largely agricultural regions of Canada. The data from both sensors was compared to ground measurements on both an absolute and relative basis. Overall, the root mean squared errors for SMOS were less than 0.10 m3 at most sites, and less where the in situ soil moisture was measured at multiple sites within radiometer footprint (sites in Saskatchewan, Manitoba and Ontario). At many sites, SMOS overestimates soil moisture shortly after rainfall events compared to the in situ data; however this was not consistent for each site and each time period. SMOS was found to underestimate drying events compared to the in situ data; however this observation was not consistent from site to site. The Aquarious soil moisture data showed higher root mean squared errors in areas where there were more frequent wetting and drying cycles. Overall, both data sets, and SMOS in particular, showed a stable and consistent pattern of capturing surface soil moisture over time.
Location: T E 15 New Biology Building
Literature cited 1: Adams, J.R., McNairn, H, Berg, A.A, Champagne, C, 2015.Evalutaion of near-surface soil moisture data from an AAFC monitoring network in Moanitoba, Canada: Implications for L-band satellite validation.J.Hydrol.521, 582-592. Al Bitar, A., Leroux, D., Kerr, Y.H., Merlin, O., Richaume, P., Sahoo, A., Wood, E.F., 2012.Evauation of SMOS soil moisture products over continental U.S.using the SCAN/SNOTEL network.IEEE Trans.Geosci.Remote Sens.50, 1572-1586.
Literature cited 2: Albergel, C., Dorigo, W., Balsamo, G., Munoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu,R., Wagner, W., 2013.Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses. Remote Sens.Environ.138, 77-89.

ID: 61856
Title: A comparison of ASCAT and SMOS soil moisture retrievals over Europe and Northern Africa from 2010 to 2013.
Author: Fabio Fascetti, Nazzareno Pierdicca, Luca Pulvirenti, Raffaele Crapolicchio, J.Munoz-Sabater.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 135-142 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Remote sensing, SMOS, ASCAT, Soil moisture.
Abstract: A comparison between ASCAT/H-SAF and SMOS soil moisture products was performed in the frame of the EUMETSAT H-SAF project. The analysis was extended to the whole H-SAF region of interest, including Europe and North Africa, and the period between January 2010 and November 2013 was considered. Since SMOS and ASCAT soil moisture data are expressed in terms o absolute and relative values, respectively, different approaches were adopted to scale ASCAT data to use the same volumetric soil moisture unit. Effects of land cover, quality index filtering, season and geographical area on the matching between the two products were also analyzed. The two satellite retrievals were also compared with other independent datasets, namely the NCEP/NCAR volumetric soil moisture content reanalysis developed by NOAA and the ERA-Interim/Land soil moisture produced by ECMWF. In situ data, available through the International Soil Moisture Network, were also considered as benchmark. The results turned out to be influenced by the way ASCAT data was scaled. Correlation between the two products exceeded 0.6, while the root mean square difference did not decrease below 8%.ASCAT generally showed a fairly good degree of correlation with ERA, while, as expected considering the different kinds of measurement, the discrepancies with respect to local in situ data were large for both satellite products.
Location: T E 15 New Biology Building
Literature cited 1: Al-Yaari, A., Wigneron, J.-P.,Ducharne, A., Kerr,Y.H., Wagner,W., De Lannoyf,G., Reichle, R., Al Bitar, A.Dorigo, W.,Richaume, P., Mialon, A., 2014a.Global-scalecomparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land).Remote Sens.Environ.152, 614-626. Al-Yaari, A., Wigneron, J.P., Ducharne, A., Kerr,Y., de Rosnay, P., de Jeue, R., Govind,A., Al- Bitar,A.,Albergel, C., Munoz-Sabater, J., Richaume,P.,Mialonc, A.,2014b. Gloabal-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to land data assimilation system estimates. Remote Sens Env.149, 181-195.
Literature cited 2: Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., Dee, D., Dutra, E., Pappenberger, F., de Rosnay, P., Munoz-Sabater, J., Stockdale, T., Vitart, F., 2014.ERA-Interim/Land: a global land-surface reanalysis based on ERA-Interim meteorological forcing.Hydrol.Earth Syst.Sci.19, 389-407.doi:10.194/hess-19-389-2015. Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., Dee, D., Dutra, E., Munoz-Sabater, J.Pappenberger, F., de Rosnay, P., Stockdale, T., Vitrat, F., 2015.ERA-Interim/Land: a global land surface reanalysis data set.Hydrol.Earth Syst.Sci.19, 389-407,http//dx.doi.org/10.5194/hess-19-389-2015.

ID: 61855
Title: Global SMOS Soil Moisture Retrievals from the Land Parameter Retrieval Model.
Author: R.van der Schalei, Y.H.Kerr, J.P.Wigneron, N.J.Rodriguez-Fernandez, A.Al-Yaari, R.A.M. de Jeu
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 125-134 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Remote sensing, Passive microwave radiometry, Soil moisture, Soil moisture and ocean salinity (SMOS), Land Parameter Retrieval Model (LPRM).
Abstract: A recent study by Van der Schalie et al. (2015) showed good results for applying the Land Parameter Retrieval Model (LPRM) on SMOS observations over southeast Australia and optimizing and evaluating the retrieved soil moisture (? in m3m-3) against ground measurements from the OzNet sites. In this study, the LPRM parameterization is globally updated for SMOS against modeled ? from MERRA-Land 9MERRA) and ERA-Interim/Land (ERA) over the period of July 2010-December 2010, mainly focusing on two parameters: the single scattering albedo (w and the roughness (h).The Pearson ' s coefficient of correlation (r) increased rapidly when increasing the w up to 0.12 and reached a steady state from thereon, no significant spatial pattern was found in the estimation procedure, and a single value of 0.12 was therefore used globally. The h was defined as a function of ? and varied slightly for the different angle bins, with maximum values of 1.1-1.3 as the angle changes from 42.5? to 57.5?.This resulted in an average r of 0.51 and 0.47, with a bias (m3m-3) -0.02 and -0.01 and unbiased root mean square error (ubrmse in m3m-3) of 0.054 and 0.56 against MERRA (ascending and descending).For ERA this resulted in an r of 0.61 and 0.53, with a bias of -0.03 and an ubrmse 0.055 and 0.059.The resulting parameterization was then used to run LPRM on SMOS observations over the period of July 2010-December 2013 and evaluated against SMOS Level 3 (L3) ? and available in situ measurements from the International Soil Moisture Network (ISMN).The comparison with L3 shows that the LPRM ? retrievals are very similar, with for the ascending set very high r of over 0.9 in large parts of the globe, with an overall average of 0.85 and the descending set performing less with an average of 0.74, mainly due to the negative r over the Sahara. The mean bias is 0.03, with an ubrmse of 0.038 and 0.44.In this study there are three major areas and over high altitudes, which are all known limitations of LPRM. The comparison against situ measurement from the ISMN give very similar results, with average r LPRM. The comparisons against situ measurement from the ISMN give very similar results, with average r for LPRM of 0.65 and 0.61 (0.64 and 0.59 for L3) for the ascending and descending sets, while having a comparable bias and ubrmse over the different networks. This shows that LPRM used on SMOS observations produce ? retrievals with a similar quality as the SMOS L3 product.
Location: T E 15 New Biology Building
Literature cited 1: Albergel, C., De Rosnay, P., Gruhier, C., Munoz-Sabatr, J.,Hasenauer, J., S., Isaksen,L., Kerr, Y.,Wagner, W., 2012.Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sens.Environ.118, 215-226, http://dx.doi.org/10.1016/j.rse.2011.11.017. Albergel, C., Rudiger, C., Pellarin, T., Calvet, J.C., Fritz,N.,Froissard, F., et al., 2008.From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and modelsimulations.Hydropl.Earth Syst..Sci.12, 1323-1337.
Literature cited 2: Balsamo, G., Viterbo, P., Beljaars, A., Van den Hurk, B., Hirschi, M., Betts, A.K., Scipal, K., 2009.A revised hydrology for the ECMWF model: verification from field site to terrestrial water storage and impact in the integrated forecast system.J.Hydrometerol. 10(3) http://dx.doi.org/10.1175/2008JHM1068.1 Batralis, Z., Wagner, W., Naeimi, V., Hasenauer, S., Scipal, K., Bonekamp, H., Figa, J., Anderson., 2007.Initial soil moisture retrievals from the METOP-A.advanced.Scatterometer (ASCAT).Geophy.Res.Lett.34, L20401.

ID: 61854
Title: Soil moisture variability over odra watershed: Comparison between SMOS and GLDAS data.
Author: Jaroslaw Zawadzki, Mateusz Kedzior.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 110-124 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Soil moisture, SMOS, GLDAS, CATDS, The Odra watershed, Regional studies.
Abstract: Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavourable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries-Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118, 861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe. This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012.This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual comparisons. The results obtained using various statistical tools unveil high scientific potential of CATDS SMOS data to study soil moisture over the Odra river watershed. This was also confirmed by reasonable agreement between results derived from CATDS SMOS Ascending and GLDAS datasets. This agreement was achieved mainly by using these data spatially averaged over the whole watershed area, and for observations performed in the period longer than three-day averaging time. Comparisons of separate three-day data in a given pixel position, or at a smaller areas would be difficult because of data gaps. Hence, the results of the work suggest that despite of RFI interferences, SMOS observations can provide effective input for analysis of soil moisture at regional scales. Moreover, it was shown that CATDS SMOS soil moisture data are better correlated with rainfall rate than GLDAS ones.
Location: T E 15 New Biology Building
Literature cited 1: Bircher, S., N.Kerr ,Y., 2013.Validation of SMOS L1C and L2 products and important parameters of the retrieval algorithm in the Skjern River Catchment, Western Denmark, IEEE Trans.Geosci.Remote Sens. 51 (5). Brocca, L., Tullo, T., Melone, F., 2012.Catchment scale soil moistures spatial-temporal variability.J.Hydrol.422-423, 63-75.
Literature cited 2: Brocca, L., Tullo, T., Melone, F., Moramarco, T., Wagner, W., Hasenauer, S., 2010.ASCAT soilwetness index validation through in situ and modeled soil moisture data in central Italy.Remot Sens.Environ. 114 (11), 2745-2755. Brocca, L., Melone, F., Moramarco, T., Morbidelli, R., 2010.Spatial-temporal variability of soil moisture and its estimation across scales. Water Resour.Res.46.

ID: 61853
Title: On the importance of satellite observed soil moisture.
Author: Richard de Jeu
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 45 (B) 107-109 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Importance, satellite, observed, soil, moisture.
Abstract: During the past 15 years, remotely sensed soil moisture data products have matured: while in the beginning of this century a few basic experimental science data products were available, nowadays several completely error characterized operational data products are available. When the first global soil moisture datasets from active (Wagner et al., 1999) and passive (De Jeu, 2003; Njoku et al., 2003) microwave sensors appeared, the usefulness of these datasets was not immediately clear, mainly due to the less appealing characteristics of these datasets compared to, for example, the optical satellite products. These datasets had a felt coarse resolution of approximately 0.25?, low sampling rates, and the quality of the datasets was not yet well defined, which made the data at first sight less useful for environmental applications.
Location: T E 15 New Biology Building
Literature cited 1: De Jeu, R.A.M., 2003, Retrieval of Land Surface Parametrs Using Passive Microwave Observations, PhD Dissertation.VU, Amsterdam, pp.120, ISBN90-9016430-8. De Jeu, R.A.M., Wagner, W.W., Holmes, T.R.H.,Dolman, A.J., van de Giesen, N.C., Friesen, J., 2008.Global soil moisture patterns observed by space borne microwave radiometers and scatterometrs.Surv.Geophys.28, 399-420, http://dx.doi.org/10.100712-008-9044-0.
Literature cited 2: Draper, C.S., Walker, J.P., Steinle, P.J., De Jeu, R.A.M., Holmes, T.R.H., 2009.Evaluation of AMSR-E derived soil moisture over Australia. Remote Sens. Environ, 113, 703-710, http:dx.doi.org/10.1016/j.rse.2008.11.011.