Engineering topics
Lavalle, Marco
Publications and source records attributed to Lavalle, Marco.
Experiments with small UAS to support SAR tomographic mission formulation
No abstract provided
Review of Change-Detection Algorithms Applied to Polarimetric SAR Time-Series: Dual-Pol L and C-Band Time-Series
No abstract provided
Distributed Aperture Radar Tomographic Sensors (DARTS) to Map Surface Topography and Vegetation Structure
No abstract provided
Distributed Aperture Radar Tomographic Sensors (darts) to Map Surface Topography and Vegetation Structure
Distributed Aperture Radar Tomographic Sensors (DARTS)is a mission concept being studied at the NASA Jet PropulsionLaboratory in collaboration with the California Institute ofTechnology to enable global and repeated imaging of surfacetopography and three-dimensional vegetation structure usingsingle-pass tomographic SAR technique. The observing systemconsists of a distributed formation of multiple small syntheticaperture radar platforms deployed in space with variabledistances to achieve look angle diversity and sensitivityto the vertical distribution of vegetation components. Ourgoal is to identify the optimal system configuration startingfrom documented community needs and mature the criticaltechnologies that lead to a viable implementation of DARTS.Here, we provide an overview of DARTS and describe ourapproach for designing and demonstrating single-pass SARtomographic systems as part of an on-going funded NASA Instrument Incubator Program effort.
Comparison of SAR and CYNSS surface water extent metrics over the Yucatan Lake wetland site
Wetlands have a major role in the carbon cycle, outgassing large quantities of carbon dioxide and methane through processes that are directly and strongly influenced by the duration and timing of inundation. Therefore, understanding the seasonal pattern of inundation can be a component for regional to global scale carbon models. Measurement of inundation extent also establishes a benchmark for the current status of wetland areas, useful in assessing the future impacts of climate change. The incorporation of frequent measurements of inundation extent into large-scale hydrological models would permit the evaluation of more detailed seasonal and longer-term floodplain dynamics and their associated management implications.The Cyclone GNSS (CYGNSS) constellation of satellites launched in 2016, and carries receivers capable of receiving data from L-band GNSS reflections. Delay Doppler maps (DDM) are generated on board and telemetered to the ground, along with a small number of raw data takes that can be used for special processing on the ground for evaluation purposes. It has been previously shown that these data can be sensitive to inundation.The NASA ISRO Synthetic Aperture Radar, currently planned for launch in January 2023, has both an L-band and S-band SAR for earth imaging. The L-band SAR, which will image the Earth's land mass twice every 12 days, has a requirement for measuring wetland inundation extent at the 1 ha scale. One of the sites that will be used to validate this requirement is Yucatan Lake, Louisiana. This oxbow lake and surrounding area located adjacent to the Mississippi river experiences periodic and extensive flooding in the surrounding forest areas.In 2019, NASA's UAVSAR fully polarimetric airborne L-band SAR conducted a flight campaign to image a dozen sites in the SE USA at approximately 12-day intervals and both in the morning and evening, to simulate the type of data NISAR will obtain. One site imaged during this campaign was the Yucatan Lake area, spanning water stages from low to high flood conditions.It has been demonstrated previously that GNSS reflectometry such as that measured by CYGNSS may be used to characterize surface inundation. It has also been known for decades that L-band SAR may be used to characterize not only the presence of open water, but also the presence of subcanopy inundation in forested areas. In this paper we will present results comparing data from these two types of instruments.
State of the Art in GNSS-R Capabilities Over Inland Waters
GNSS Reflectometry (GNSS-R) measurements are very sensitive to the presence of inland waters such as wetlands, floods, rivers and lakes. This paper reviews the basic characteristics of a GNSS-R ‘water detection’ product, including resolution and temporal sampling of wetlands, and discusses the main known sources of errors.
Distributed Aperture Radar Tomographic Sensors to map Changing Surface Topography and Vegetation Structure
No abstract provided
Joint Radar Time-Series Retrieval Framework for Ecosystem Science and Land Applications
No abstract provided
An Efficient Area-Based Algorithm for SAR Radiometric Terrain Correction and Map Projection
This article presents a projection algorithm based on the representation of radar samples as area elements, rather than point elements as traditionally done in previous works. Each area element in the geographic grid (geogrid) is associated with a set of samples in the radar grid that intersect completely or partially the area element according to the topography and the radar geometry. Accurate geocoding with adaptive multi-looking is achieved by successively assigning the weighted average of the radar samples to the corresponding geogrid elements. Analogously, the slant-range projection of geocoded data is improved by projecting the geogrid pixels onto the radar grid according to their projected area. When our slant-range projection approach is used within previously-published radiometric terrain correction (RTC) algorithms, the processing time is significantly reduced, performing 3.6 to 5.2 times faster over multi-looked data and up to 8.9 over single-look data. We demonstrate the strength of the area projection algorithm for RTC and geocoding using UAVSAR and Sentinel-1 data, and evaluate the results in the context of the upcoming NISAR mission.
Assessment Of Polsar And Insar Time-Series From The 2019 Nasa Am-Pm Campaign For Above-Ground Biomass Estimation
The forthcoming launch of the NASA-ISRO Synthetic ApertureRadar (NISAR) mission will open the path to a new typeof L-band measurements constituted by dense time-series ofpolarimetric backscatter and interferometric coherence withunprecedented spatial and temporal sampling. Here, we startthe development of a theoretical framework that links L-bandbackscatter time-series with interferometric coherence measurements.The water-cloud-model (WCM) and an extendedversion of the random-motion-over-ground (RMoG) modelare adopted to express radar measurements in terms of forestabove-ground biomass and tree height. Time-series datacollected during the 2019 UAVSAR AM-PM campaign inSoutheastern United States are used to evaluate the correlationof various PolSAR- and InSAR-derived parameters withfield-measured above-ground biomass.
Coherent Approaches to Disturbance Mapping Using SAR Covariance Matrices Time-Series
No abstract provided
Collaborative Data Curation to Support the Multi-Mission Algorithm and Analysis Platform (MAAP)
Upcoming space-borne missions will offer unprecedented data about Earth but will also feature exponentially high data volumes. These high data volumes will change the way the scientific community works with data and will also create a unique need for improved data sharing and collaboration. NASA and ESA are working together to address these issues by collaboratively developing the Multi-Mission Algorithm and Analysis Platform (MAAP) to improve the understanding of global aboveground terrestrial carbon dynamics. The MAAP will support ESA’s BIOMASS mission, NASA’s GEDI mission and NASA/ISRO’s NISAR mission. The MAAP will be developed in two phases: a pilot phase and a full production phase. The pilot phase will demonstrate collaboration and basic capabilities. The pilot phase will focus on biomass relevant airborne and field campaign data. Two NASA teams are supporting the development of the MAAP. The MAAP engineering team is responsible for the development, maintenance and operations of the MAAP system while the MAAP data team ensures the ongoing quality of the data, metadata and other information provided in the MAAP. The MAAP data team also supports the ingest and archive of identified data to the MAAP platform. This poster describes the use case development process for the pilot MAAP and the data curated in support of those use cases. Additionally, this presentation will outline the pilot MAAP data ingest process and metadata curation effort along with efforts to ensure interoperability between ESA and NASA data and metadata.