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Funded Research

Characterizing surface energy budget of different surface types under varying climatic conditions from AVIRIS and MASTER data

Liang, Shunlin: University of Maryland (Project Lead)
Wang, Dongdong: University of Maryland (Co-Investigator)

Project Funding: 2013 - 2015

NRA: 2011 NASA: HyspIRI Preparatory Airborne Activities and Associated Science and Applications   

Funded by NASA

Abstract:
The land surface responds to climate variability and also modulates the climate through the exchange of energy, matter and momentum. It is well known that the response and modulation largely depend on land cover and plant functional types and their properties. The synergy of the AVIRIS and MASTER data with high spatial and spectral resolutions provides us an unprecedented data resource to study the spatial variability of the land-atmosphere exchange of water, carbon and energy at the ecosystem scale. Scheduled multiple transects at different seasons outlined in the ROSES2011 call for proposals and the high temporal refreshing frequency of the future HyspIRI data will enable us to study the temporal dynamics of such land-atmosphere exchange. We propose to use the HyspIRI-like airborne measurements resulting from the planned campaigns in FY2013 and FY2014 to 1) map the following surface radiation and energy budget components from both AVIRIS and MASTER data: insolation/photosynthetically active radiation (PAR), albedo, net radiations, and evapotranspiration (ET); and 2) quantify the changes in the land-cover-dependent surface radiation and energy budget under varying climatic conditions. We have developed the corresponding algorithms for the multispectral remotely sensed data in the recent years. In this study, these algorithms will be refined and extended to hyperspectral data, and extensively validated using the AVIRIS and MASTER data at many field stations where surface measurements are available. These products will be mainly used for addressing scientific questions in this proposal, but also provided to other investigators for many other applications. They can also be scaled up for validating other coarser resolution radiation energy products. This is a research proposal responding to A26 calling for proposals that utilize AVIRIS measurements, MASTER measurements, or both to address one or more of the HyspIRI science questions . The scientific question we will try to answer is CQ4 How do species, functional type, and biodiversity composition within ecosystems influence the energy, water and biogeochemical cycles under varying climatic conditions? All these algorithms developed in this study can be potentially used for generating the operational surface radiation and energy products from the VSWIR and TIR data of the HyspIRI mission in the future. Since the proposed efforts build on our algorithm development from the previous NASA projects, it is a cost-effective strategy for refining the algorithms and generating the needed products for analysis.

Publications:

He, T., Liang, S., Wang, D., Chen, X., Song, D., Jiang, B. 2015. Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach. Remote Sensing. 7(5), 5495-5510. DOI: 10.3390/rs70505495

He, T., Liang, S., Wang, D., Shi, Q., Goulden, M. L. 2015. Estimation of high-resolution land surface net shortwave radiation from AVIRIS data: Algorithm development and preliminary results. Remote Sensing of Environment. 167, 20-30. DOI: 10.1016/j.rse.2015.03.021

Wang, D., Liang, S., He, T., Shi, Q. 2015. Estimating clear-sky all-wave net radiation from combined visible and shortwave infrared (VSWIR) and thermal infrared (TIR) remote sensing data. Remote Sensing of Environment. 167, 31-39. DOI: 10.1016/j.rse.2015.03.022

Wang, D., Liang, S., He, T., Shi, Q. 2015. Estimation of Daily Surface Shortwave Net Radiation From the Combined MODIS Data. IEEE Transactions on Geoscience and Remote Sensing. 53(10), 5519-5529. DOI: 10.1109/tgrs.2015.2424716

Wang, D., Liang, S., He, T., Yu, Y. 2013. Direct estimation of land surface albedo from VIIRS data: Algorithm improvement and preliminary validation. Journal of Geophysical Research: Atmospheres. 118(22), 12,577-12,586. DOI: 10.1002/2013jd020417

Wang, D., Liang, S., He, T., Yu, Y., Schaaf, C., Wang, Z. 2015. Estimating daily mean land surface albedo from MODIS data. Journal of Geophysical Research: Atmospheres. 120(10), 4825-4841. DOI: 10.1002/2015jd023178


2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Estimation of high-resolution land surface net shortwave radiation from AVIRIS data: Algorithm development and preliminary results   --   (Tao He, Shunlin Liang)   [abstract]

More details may be found in the following project profile(s):