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Fatoyinbo, Temilola

Publications and source records attributed to Fatoyinbo, Temilola.

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗

Adaptive Antenna Pattern Notching of Interference in Synthetic Aperture Radar Data Using Digital Beamforming

Radio Frequency Interference (RFI) is a growing problem in Synthetic Aperture Radar (SAR)systems as scientific motivations push the radars to lower frequencies and as more wireless services share the frequency spectrum. New, advanced SAR instruments, such as NASA's EcoSAR, DBSAR and DLR's Tandem-L mission, employ a multichannel architecture capable of Digital Beamforming (DBF). Radars with DBF are capable of notching the antenna pattern in specific directions, which can be utilized to suppress RFI on board or in post-processing. A well-researched beamformer for this purpose is the Minimum Variance Distortionless Response (MVDR) Beamformer. However, the number of interferers that can be removed through notching is limited by the number of receive channels. It is therefore essential to adaptively change the antenna pattern notching throughout the image in time and frequency for the best results with a given number of receive channels. In this paper, we present several methods to achieve this notching by making use of the spatial SAR signal distribution in range time, range frequency, azimuth time and azimuth Doppler that is inherent to the SAR imaging geometry. Because this distribution is time-variable and yet predictable, it can be used to improve the angle of arrival estimation of the RFI and the adaptive notching. The presented methods can be applied to a Digital Beamforming (DBF) SAR signal with multiple channels in elevation and/or in azimuth. Simulations show that the proposed methods increase the ability to notch out-of-swath interference from multiple directions and lessen the impact on in-swath interference. The improvement of the interferometric coherence for a single-pass interferogram acquired by NASA's EcoSAR system (capable of DBF in elevation) is demonstrated. The removal of periodic RFI artifacts is achieved.

RFI↗

Measuring Mangrove Carbon Loss and Gain in Deltas

Demand for mangrove forest resources has led to a steady decline in mangrove area over the past century. Land conversions in the form of agriculture, aquaculture and urbanization account for much of the deforestation of mangrove wetlands. However, natural processes at the transition zone between land and ocean can also rapidly change mangrove spread. In this study, we applied a robust field-based carbon inventory and new structural and temporal remote sensing techniques to quantify the magnitude and change of mangrove carbon stocks in major deltas across Africa and Asia. From 2000–2016, approximately 1.6% (12 270 ha) of the total mangrove area within these deltas disappeared, primarily through erosion and conversion to agriculture. However, the rapid expansion of mangroves in some regions during this same period resulted in new forests that were taller and more carbon-dense than the deforested areas. Because of the rapid vertical growth rates and horizontal expansion, new mangrove forests were able to offset the total carbon losses of 5 332 843 Mg C by 44%. Each hectare of new mangrove forest accounted for ∼84% to ∼160% of the aboveground carbon for each hectare of mangrove forest lost, regardless of the net change in mangrove area. Our study highlights the significance of the natural dynamics of erosion and sedimentation on carbon loss and sequestration potential for mangroves over time. Areas of naturally regenerating mangroves will have a much larger carbon sequestration potential if the rate of mangrove deforestation of taller forests is curbed.

canopy height↗

Mapping Mangrove Extent and Change: A Globally Applicable Approach

This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image change method was used to detect annual and decadal changes in extent using ALOS PALSAR/JERS-1 imagery. The map-to-image method presented makes fewer assumptions of the data than existing methods, is less sensitive to variation between scenes due to environmental factors (e.g., tide or soil moisture) and is able to automatically identify a change threshold. Change maps were derived from the 2010 baseline to 1996 using JERS-1 SAR and to 2007, 2008 and 2009 using ALOS PALSAR. This study demonstrated results for 16 known hotspots of mangrove change distributed globally, with a total mangrove area of 2,529,760 ha. The method was demonstrated to have accuracies consistently in excess of 90% (overall accuracy: 92.2–93.3%, kappa: 0.86) for mapping baseline extent. The accuracies of the change maps were more variable and were dependent upon the time period between images and number of change features. Total change from 1996 to 2010 was 204,850 ha (127,990 ha gain, 76,860 ha loss), with the highest gains observed in French Guiana (15,570 ha) and the highest losses observed in East Kalimantan, Indonesia (23,003 ha). Changes in mangrove extent were the consequence of both natural and anthropogenic drivers, yielding net increases or decreases in extent dependent upon the study site. These updated maps are of importance to the mangrove research community, particularly as the continual updating of the baseline with currently available and anticipated spaceborne sensors. It is recommended that mangrove baselines are updated on at least a 5-year interval to suit the requirements of policy makers.

Thomas, Nathan↗

Forest Structure Retrieval from Ecosar P-Band Single-Pass Interferometry

EcoSAR is a single-pass (dual antenna) digital beamforming, P-band radar system that is designed for remote sensing of dense forest structure. Forest structure retrievals require the measurement related to the vertical dimension, for which several techniques have been developed over the years. These techniques use polarimetric and interferometric aspects of the SAR data, which can be collected using EcoSAR. In this paper we describe EcoSAR system in light of its interferometric capabilities and investigate forest structure retrieval techniques.

Osmanoglu, Batuhan↗

Digital Beamforming Based RFI Mitigation for Synthetic Aperture Radar

An increasing challenge for P-band Synthetic Aperture Radar (SAR) is Radio Frequency Interference (RFI). RFI results in image distortions and degrades the derived science products. This makes it critical to apply RFI removal techniques to restore the image quality. New advanced techniques can be achieved with Digital Beamforming (DBF) radars such as EcoSAR. In this paper, we present a Range-Dependent Time Minimum Variance Distortionless Response (RDTMVDR) Beamformer and apply it to EcoSAR flight data during post-processing. The antenna pattern (AP) is adaptively changed for each range line which increases the RFI suppression compared to a fixed AP for each pulse. The interferometric image quality is assessed before and after RFI suppression.

Bollian, Tobias↗

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Forest Productivity↗

Estimating Mangrove Aboveground Biomass from Airborne LiDAR Data: a Case Study from the Zambezi River Delta

Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models.We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R(exp 2) between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha(exp −1) up to 252 Mg ha(exp −1).We suggest the best model to predict AGB was based on the East Africa specific allometry and a power-based regression that used Lidar H100 as the height input with an R(exp 2) of 0.85 and an RMSE of 122 Mg ha(exp −1) or 33%. The total AGB of the Lidar inventoried mangrove area (6654 ha) was 1 350 902 Mg with a mean AGB of 203 Mg ha(exp −1) +/-166 Mg ha(exp −1). Because the allometry suggested here was developed using standardized height metrics, it is recommended that the models can generate AGB estimates using other remote sensing instruments that are more readily accessible over other mangrove ecosystems on a large scale, and as part of future carbon monitoring efforts in mangroves.

Fatoyinbo, Temilola↗

Forest Structure Retrieval From EcoSAR P-Band Single-Pass Interferometry

EcoSAR is a single-pass (dual antenna) digital beamforming, P-band radar system that is designed for remote sensing of dense forest structure. Forest structure retrievals require the measurement related to the vertical dimension, for which several techniques have been developed over the years. These techniques use polarimetric and interferometric aspects of the SAR data, which can be collected using EcoSAR. In this paper we describe EcoSAR system in light of its interferometric capabilities and investigate forest structure retrieval techniques.

SAR↗

Digital Beamforming Synthetic Aperture Radar Developments at NASA Goddard Space Flight Center

Advanced Digital Beamforming (DBF) Synthetic Aperture Radar (SAR) technology is an area of research and development pursued at the NASA Goddard Space Flight Center (GSFC). Advanced SAR architectures enhances radar performance and opens a new set of capabilities in radar remote sensing. DBSAR-2 and EcoSAR are two state-of-the-art radar systems recently developed and tested. These new instruments employ multiple input-multiple output (MIMO) architectures characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instruments have been developed to support several disciplines in Earth and Planetary sciences. This paper describes the radars advanced features and report on the latest SAR processing and calibration efforts.

Wide band↗

Development of RFI Mitigation Techniques with Digital Beamforming

Remote sensing radars with longer wavelengths penetrate deeper into the observed scene and are more suitable for the scientific observation of ice sheets or vegetation. Therefore, SAR systems are moving to lower frequencies like L- or P-band. However, as the frequency spectrum is a limited resource, this means that the occupied frequency band has to be shared with existing users. These users can have serious impact on the imaging quality. Radio frequency interference (RFI) that arrives at the antenna together with the SAR backscatter is causing a drop of the signal-to-noise ratio. Despite the high processing gain of the SAR signal, artifacts can appear in the image if the RFI is strong enough. This can lead to a corruption of the acquired data and make it unsuitable for scientific purposes. Hence, the investigation of methods for RFI mitigation is critical to the performance of radar missions and to ensure they meet their main task.

Digital Beamforming↗

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 stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Lee, Seung-Kuk↗

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

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 stereophotogrammetric 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.

HRSI↗

Digital Beamforming Synthetic Aperture Radar (DBSAR): Performance Analysis During the Eco-3D 2011 and Summer 2012 Flight Campaigns

The Digital Beamforming Synthetic Aperture radar (DBSAR) is a state-of-the-art airborne radar developed at NASA/Goddard for the implementation, and testing of digital beamforming techniques applicable to Earth and planetary sciences. The DBSAR measurements have been employed to study: The estimation of vegetation biomass and structure - critical parameters in the study of the carbon cycle; The measurement of geological features - to explore its applicability to planetary science by measuring planetary analogue targets. The instrument flew two test campaigns over the East coast of the United States in 2011, and 2012. During the campaigns the instrument operated in full polarimetric mode collecting data from vegetation and topography features.

SAR↗

Development of NASA's Next Generation L-Band Digital Beamforming Synthetic Aperture Radar (DBSAR-2)

NASA's Next generation Digital Beamforming SAR (DBSAR-2) is a state-of-the-art airborne L-band radar developed at the NASA Goddard Space Flight Center (GSFC). The instrument builds upon the advanced architectures in NASA's DBSAR-1 and EcoSAR instruments. The new instrument employs a 16-channel radar architecture characterized by multi-mode operation, software defined waveform generation, digital beamforming, and configurable radar parameters. The instrument has been design to support several disciplines in Earth and Planetary sciences. The instrument was recently completed, and tested and calibrated in a anechoic chamber.

SAR↗

The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

EcoSAR is a new synthetic aperture radar (SAR) instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. The instrument uses a phased-array beamforming architecture and supports full polarimetric measurements and single pass interferometry. This Instrument development is part of NASA's Earth Science Technology Office Instrument Incubator Program (ESTO IIP).

SAR↗

The 2011 Eco3D Flight Campaign: Vegetation Structure and Biomass Estimation from Simultaneous SAR, Lidar and Radiometer Measurements

The Eco3D campaign was conducted in the Summer of 2011. As part of the campaign three unique and innovative NASA Goddard Space Flight Center airborne sensors were flown simultaneously: The Digital Beamforming Synthetic Aperture Radar (DBSAR), the Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) and the Cloud Absorption Radiometer (CAR). The campaign covered sites from Quebec to Southern Florida and thereby acquired data over forests ranging from Boreal to tropical wetlands. This paper describes the instruments and sites covered and presents the first images resulting from the campaign.

Fatoyinbo, Temilola↗