Project Funding: 2012 - 2015

NRA: 2011 NASA: Terrestrial Ecology   

Funded by NASA

Abstract:
Vegetation vertical structure has been identified by the ecosystem community at large, and by scientific panels, such as the NRC Decadal Survey, as the highest science priority, and lidar is universally acknowledged as the most accurate means of deriving that structure. The loss of the lidar segment from the DESDynI mission has left the ecosystem community with no planned structure observations other than what the ICESAT-2 (I2) mission will obtain, to be used by themselves, or in fusion with the DESDynI radar segment (DESDynI-R) and other data sources. Two decades of experience with waveform sampling lidar have given us a clear knowledge of what is achievable from spaceborne waveform lidar, allowing us to inform space mission development and determine the implications of such missions on science priorities for terrestrial ecology. Unfortunately, there is no comparable background information for the single photon-counting lidar (SPL) technology of the ATLAS instrument on the ICESAT-2 mission. As a consequence there is tremendous uncertainty about its capabilities as deployed in space, and the role such observations can play, either alone, or in fusion with other sensors, in the study of ecosystems and the carbon cycle. This uncertainty leads to a set of basic questions that must be addressed regarding the efficacy of SPL and which form the central basis of our proposed research. The overall goal of our study is to explore the efficacy of SPL for deriving ecosystem structure. In particular, we seek to answer the following questions: 1) What methods are most appropriate for retrieval of canopy height and vertical structure using SPL? 2) What accuracies are likely achievable for the estimation of ecosystem structure from ICESAT-2 and how will these vary as a function of environmental and canopy conditions? 3) What are the impacts of the difference in expected performance of ICESAT-2/DESDynI-R vs. the original DESDynI mission on biomass estimation and habitat characterization? Our methodological approach is to first determine how the wealth of existing waveform and discrete lidar, and the very limited airborne SPL data may be used to simulate spaceborne SPL. Given its very low energy return, the performance of SPL is hypothesized to vary strongly with canopy cover and other environmental gradients. To explore this issue more fully, we propose to acquire new SPL data using a proven commercial SPL system over a strong gradient in the Sierra Nevada where the researchers have existing lidar and field data. These data sets will allow us to develop and test algorithms for estimating canopy height and canopy structure, and to understand the potential dependency of algorithm efficacy on canopy architecture, among others. These algorithms will then provide us with sets of simulated structure retrievals, from which ICESAT-2 performance may be assessed geographically. Our proposed research falls into five major categories of activities: (1) identify appropriate methods of simulating MPC space observations using existing waveform, discrete return and MPC airborne lidar data sets; (2) acquire new MPC data across a strong geographic environmental gradient in the Sierra Nevada; (3) develop and test algorithms for retrieving canopy height and vertical structure from MPC; (4) assess the expected performance of MPC data from I2 and understand how this performance varies as a function of geographic canopy and environmental variability; (5) test I2-like data sets, by themselves, and in fusion with other remote sensing data to assess impacts on biomass estimation and habitat characterization relative to Decadal Survey recommendations as proposed for DESDynI. Ultimately, our research will help define the efficacy of MPC for the retrieval of ecosystem structure, and in doing so provide direct guidance to the Terrestrial Ecology program on the carbon and ecosystem science achievable during the I2/DESDynI-R era.

Publications:

Tang, H., Dubayah, R., Brolly, M., Ganguly, S., Zhang, G. 2014. Large-scale retrieval of leaf area index and vertical foliage profile from the spaceborne waveform lidar (GLAS/ICESat). Remote Sensing of Environment. 154, 8-18. DOI: 10.1016/j.rse.2014.08.007

Tang, H., Ganguly, S., Zhang, G., Hofton, M. A., Nelson, R. F., Dubayah, R. 2016. Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States. Biogeosciences. 13(1), 239-252. DOI: 10.5194/bg-13-239-2016

Swatantran, A., Tang, H., Barrett, T., DeCola, P., Dubayah, R. 2016. Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar. Scientific Reports. 6(1). DOI: 10.1038/srep28277

Tang, H., Swatantran, A., Barrett, T., DeCola, P., Dubayah, R. 2016. Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar. Remote Sensing. 8(9), 771. DOI: 10.3390/rs8090771

Gwenzi, D., Lefsky, M. A. 2014. Modeling canopy height in a savanna ecosystem using spaceborne lidar waveforms. Remote Sensing of Environment. 154, 338-344. DOI: 10.1016/j.rse.2013.11.024

Gwenzi, D., Lefsky, M. A. 2014. Prospects of photon counting lidar for savanna ecosystem structural studies. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XL-1, 141-147. DOI: 10.5194/isprsarchives-XL-1-141-2014

Montesano, P. M., Nelson, R. F., Dubayah, R. O., Sun, G., Cook, B. D., Ranson, K. J. R., Naesset, E., Kharuk, V. 2014. The uncertainty of biomass estimates from LiDAR and SAR across a boreal forest structure gradient. Remote Sensing of Environment. 154, 398-407. DOI: 10.1016/j.rse.2014.01.027

Tang, H., Brolly, M., Zhao, F., Strahler, A. H., Schaaf, C. L., Ganguly, S., Zhang, G., Dubayah, R. 2014. Deriving and validating Leaf Area Index (LAI) at multiple spatial scales through lidar remote sensing: A case study in Sierra National Forest, CA. Remote Sensing of Environment. 143, 131-141. DOI: 10.1016/j.rse.2013.12.007

Propastin, P., Ibrom, A., Knohl, A., Erasmi, S. 2012. Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest. Remote Sensing of Environment. 121, 252-260. DOI: 10.1016/j.rse.2012.02.005

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

• Integrating Lidar Canopy Height and Landsat-based Forest Disturbance History with Ecosystem Demography Model for Carbon Change Estimation, A Case in Charles County, Maryland   --   (Maosheng Zhao, Chengquan Huang, George Hurtt, Ralph Dubayah, Justin Fisk, Anu Swatantran, Wenli Huang, Hao Tang)   [abstract]

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

• NASA Terrestrial Ecology (TE) Project Profile