David Lagomasino

EO-1 Hyperion Reflectance Time Series at Calibration and Validation Sites: Stability and Sensitivity to Seasonal Dynamics

This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends and their stability consistently is within 2.5-5 percent throughout most of the spectral range spanning the 12+ year data record. Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. A number of narrowband and derivative vegetation indices (VI) closely described the seasonal profiles in vegetation function and ecosystem carbon exchange (e.g., net and gross ecosystem productivity) in three very different ecosystems, including a hardwood forest and tallgrass prairie in North America, and a Miombo woodland in Africa. Our results demonstrate the potential for scaling the carbon flux tower measurements to local and regional landscape levels. The VIs with stronger relationships to the CO2 parameters were derived using continuous reflectance spectra and included wavelengths associated with chlorophyll content and/or chlorophyll fluorescence. Since these indices cannot be calculated from broadband multispectral instrument data, the opportunity to exploit these spectrometer-based VIs in the future will depend on the launch of satellites such as EnMAP and HyspIRI. This study highlights the practical utility of space-borne spectrometers for characterization of the spectral stability and uniformity of the calibration sites in support of sensor cross-comparisons, and demonstrates the potential of narrowband VIs to track and spatially extend ecosystem functional status as well as carbon processes measured at flux towers.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Abstract Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereo‐photogrammetric techniques on high‐resolution spaceborne imagery (HRSI) for southern Mozambique. A mean‐weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18–1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three‐dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

Large-scale mangrove canopy height map generation from TanDEM-X data by means of Pol-InSAR techniques

Mangroves are among the most-carbon rich forest in subtropics and tropics, containing on average 1,023 Mg carbon per hectare [1]. In order to better estimate mangrove biomass, carbon dynamics and land coverage changes, mangrove canopy height is a key parameter. However, there is a surprisingly absence of information needed for global-scale mangrove height mapping because of the lack of high spatial resolution data, available spaceborne data sets, and modeling techniques. In recent studies, the first single-pass TanDEM-X data showed a great possibility of mangrove canopy height estimate with accuracies comparable to airborne lidar canopy height model with single- and dual-Pol-InSAR techniques. Based on the method mentioned in [2], we here generated large-scale mangrove canopy height map with a 12-m spatial resolution over Sundarbans, the world largest mangrove forest, from existing global TDX acquisitions. The inversion result for mangrove canopy height was validated against field measurement data; a correlation coefficient of 0.852 and a RMSE of 0.774 m.

New perspectives on an iconic landscape from comparative international long-term ecological research

Iconic ecosystems like the Florida Coastal Everglades can serve as sentinels of environmental change from local to global scales. This characteristic can help inform general theory about how and why ecosystems transform, particularly if distinctive ecosystem properties are studied over long time scales and compared to those of similar ecosystems elsewhere. Here we review the ways in which long-term, comparative, international research has provided perspectives on iconic features of the Everglades that have, in turn, informed general ecosystem paradigms. Studies in other comparable wetlands from the Caribbean to Australia have shed light on distinctive and puzzling aspects such as the “upside-down estuary” and “productivity paradox” for which the Everglades is known. These studies suggest that coastal wetlands on carbonate (karstic) platforms have: (1) hydrological and biogeochemical properties that reflect “hidden” groundwater sources of water and nutrients, (2) very productive, mat-forming algal communities that present a low-quality food to aquatic consumers that encourages (3) highly diversified feeding strategies within and among populations, and (4) extensive and productive seagrass meadows and mangrove forests that promote strong cultural dependencies associated with the ecosystem services they provide. The contribution of international research to each of these general ecological topics is discussed with a particular goal of encouraging informed decision-making in threatened wetlands across the globe.

Radio frequency interference detection and mitigation techniques: EcoSAR 2014 flight campaign

Radio frequency interference (RFI) has strong influence on radar systems, especially for wideband airborne radars operating in the P-band (UHF). EcoSAR is a 435 MHz Synthetic Aperture Radar (SAR) system that employs a wideband digital beamforming architecture for the measurement of science parameters. RFI in EcoSAR measurements, degrades the quality of the SAR data and has to be removed from raw echoes. In this paper, we describe the current methodology used to mitigate RFI with EcoSAR, and provide an example on its performance. We also discuss the advantages and disadvantages of the proposed methods and discuss potential improvements.

3D forest structure parameter retrieval: Polarimetric SAR interferometry and waveform lidar airborne data

Forest vertical structure parameters are one of critical components for understanding of the global forest carbon storage and cycle, as well as climate changes. Polarimetric SAR Interferometry (Pol-InSAR) techniques and waveform lidar have been widely and successfully used for extracting 3D forest structure profiles by means of both SAR and lidar airborne systems, but individually. Therefore, fusing both data sets and developing new algorithms and models to understand forest structure are critical. We have used waveform lidar data acquired by NASAs LVIS (Land, Vegetation, and ICE sensor and SAR data acquired by various airborne and spaceborne SAR systems over mangrove forests in Pongara national park, Gabon.

Ground-level digital terrain model (DTM) construction from TanDEM-X InSAR data and WorldView stereo-photogrammetric images

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stere-ophotogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.