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Dive into the research topics where Angela Erb is active.

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Featured researches published by Angela Erb.


Remote Sensing of Environment | 2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Zhuosen Wang; Angela Erb; Crystal B. Schaaf; Qingsong Sun; Yan Liu; Yun Yang; Yanmin Shuai; Kimberly Casey; Miguel O. Román

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.


International Journal of Applied Earth Observation and Geoinformation | 2017

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Zhuosen Wang; Crystal B. Schaaf; Qingsong Sun; Jihyun Kim; Angela Erb; Feng Gao; Miguel O. Román; Yun Yang; Shelley Petroy; Jeffrey R. Taylor; Jeffrey G. Masek; Jeffrey T. Morisette; Shirley A. Papuga

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.


international geoscience and remote sensing symposium | 2016

Evaluation of VIIIRS daily BRDF, Albedo, and NBAR product using the MODIS Collection V006 product and in situ measurements

Yan Liu; Qingsong Sun; Zhuosen Wang; Crystal B. Schaaf; Angela Erb

Bidirectional Reflectance Distribution Function (BRDF), Albedo, and Nadir BRDF Adjusted Reflectance (NBAR) products are being produced for the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi-National Polar-orbiting Partnership (NPP) satellite in order to extend the MODerate resolution Imaging Spectroradiometer (MODIS) record for research and operational users. The VIIRS product is evaluated by comparison with the MODIS Collection V006 BRDF, Albedo, and NBAR products and in situ albedo collected at spatially representative sites. Preliminary results show that VIIRS can provide comparable BRDF, Albedo, NBAR products as with MODIS. Furthermore, the VIIRS, MODIS and in situ albedos agree well at spatially representative evaluation sites. The accuracy of both products therefore meet the requirements for climate and biosphere models and long term monitoring studies.


Remote Sensing in Ecology and Conservation | 2016

Observing ecosystems with lightweight, rapid‐scanning terrestrial lidar scanners

Ian Paynter; Edward Saenz; Daniel Genest; Francesco Peri; Angela Erb; Zhan Li; Kara Wiggin; Jasmine Muir; Pasi Raumonen; Erica Skye Schaaf; Alan H. Strahler; Crystal B. Schaaf


International Journal of Applied Earth Observation and Geoinformation | 2017

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

Qingsong Sun; Zhuosen Wang; Zhan Li; Angela Erb; Crystal B. Schaaf


Remote Sensing of Environment | 2017

Evaluation of the VIIRS BRDF, Albedo and NBAR products suite and an assessment of continuity with the long term MODIS record

Yan Liu; Zhuosen Wang; Qingsong Sun; Angela Erb; Zhan Li; Crystal B. Schaaf; Miguel O. Román; Russell L. Scott; Quan Zhang; Kimberly A. Novick; M. Syndonia Bret-Harte; Shelley Petroy; Mike SanClements


Remote Sensing of Environment | 2017

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

Samiah E Moustafa; Asa K. Rennermalm; Miguel O. Román; Zhuosen Wang; Crystal B. Schaaf; Laurence C. Smith; Lora S. Koenig; Angela Erb


Remote Sensing of Environment | 2018

An algorithm for the retrieval of the clumping index (CI) from the MODIS BRDF product using an adjusted version of the kernel-driven BRDF model

Ziti Jiao; Yadong Dong; Crystal B. Schaaf; Jing M. Chen; Miguel O. Román; Zhuosen Wang; Hu Zhang; Anxin Ding; Angela Erb; Michael J. Hill; Xiaoning Zhang; Alan H. Strahler


Eos | 2016

Coastal Observations from a New Vantage Point

Joseph E. Salisbury; Curtiss O. Davis; Angela Erb; Chuanmin Hu; Charles K. Gatebe; Carolyn Jordan; Zhongping Lee; Antonio Mannino; Colleen B. Mouw; Crystal B. Schaaf; Blake A. Schaeffer; Maria Tzortziou


Remote Sensing of Environment | 2018

Preliminary assessment of 20-m surface albedo retrievals from sentinel-2A surface reflectance and MODIS/VIIRS surface anisotropy measures

Zhan Li; Angela Erb; Qingsong Sun; Yan Liu; Yanmin Shuai; Zhuosen Wang; Peter Boucher; Crystal B. Schaaf

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Crystal B. Schaaf

University of Massachusetts Boston

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Qingsong Sun

University of Massachusetts Boston

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Miguel O. Román

Goddard Space Flight Center

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Yan Liu

University of Massachusetts Boston

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Yanmin Shuai

Goddard Space Flight Center

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Edward Saenz

University of Massachusetts Boston

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Francesco Peri

University of Massachusetts Boston

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Ian Paynter

University of Massachusetts Boston

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