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Amina Rangoonwala

Publications and source records attributed to Amina Rangoonwala.

At least 19 recordsLinked to original sources
USGS2021

Using ALOS-2 synthetic aperture radar (SAR) and interferometric SAR to detect landslides on the mountainous island of Pohnpei, Federated States of Micronesia

This study was undertaken by the U.S. Geological Survey to assess the detectability of landslides in the densely forested and mountainous island of Pohnpei in the Federated States of Micronesia. The study used existing field-observed land-cover changes and landslides visible on Google Earth (GE) images. A limited number of ALOS-2 PALSAR-2 L-band synthetic aperture radar (SAR) images were collected on two adjacent orbit paths before and after an intense rainfall event that affected Pohnpei in mid-March 2018. Similar sets of images were collected in 2019 and 2020. Low coherence throughout the island interior eliminated use of phase-change products, and change analysis identified no landslide features as having formed in 2019 or 2020. The assessment of red-green-blue image composites and application of the log-ratio method to the 2018 ground-range SAR images identified 5 of the 11 landslides observed on the GE images. Visual comparisons of the co-event and post-event coherence image products detected 9 of the 11 landslides observed on the GE images. Combined, the ground-based SAR and interferometric SAR coherence change detections overcame high temporal and spatial decorrelations, identified all but one landslide visible in the GE comparison, and included substantial redundancy. The robustness of the landslide detection indicates that an increased collection frequency of L-band images could support systematic monitoring of land-cover change on Pohnpei at the scale reported in this study.

Island of Pohnpei↗
USGS2021

Grassland live fractional cover map creation and Geographic Information System (GIS) analysis for rangeland management supporting Kenya Northern Rangelands Trust Conservancies

The handbooks and synchronized MP4 recordings provide hands-on instruction for creating and analyzing vegetation live fractional cover (LFC) maps. The methods and protocols used in the instruction materials follow those developed and recorded in Rangoonwala and Ramsey (2019). The LFC mapping and geographic information system (GIS) analyses highlight the consortium of rangeland conservancies covering the semiarid central region of Kenya (approximately 44,000 square kilometers). The instruction materials are separated into two parts: processing and map-product creation based on remote-sensing images and GIS analyses of the created maps for rangeland management. The image processing is conducted using the advanced and professional software package SeNtinels Application Platform (SNAP) that is supported and maintained by the European Space Agency. SNAP is a free image analyses software package available for download. It is largely icon driven but offers simple to advanced program inserts and batch processing. The GIS analyses are conducted using the software package Quantum Geographic Information System (QGIS), another free and downloadable software. QGIS is compatible with numerous software, including the Esri suite of ArcGIS software and database structure. The image data includes both high-spatial-resolution Sentinel-2 optical data and Sentinel-1 synthetic aperture radar (SAR). Both datasets are freely available via a public portal that is maintained by the European Space Agency. The image-processing instruction handbook covers all aspects of acquiring and processing satellite-image data and importing vector-data sources into SNAP. The GIS analysis handbook covers final creation of map products from the maps created in SNAP and creation of GIS procedures in QGIS that are needed to manage the rangeland resources for wildlife and pastoral grazing. Although focused on the Kenyan conservancies and their semiarid environment, the processing methods and procedures are applicable for similar environments and management, and to a large part, even for integrated mapping and GIS functionality of any managed landscape resource. The instruction handbooks are synchronized to MP4 training videos created with U.S. Geological Survey-licensed Camtasia 9 software. The workbook and MP4 video combinations are suitable for a single user or a workshop setting.

Open-File Report↗
USGS2021

Synthetic aperture radar and optical mapping used to monitor change and replacement of Phragmites australis marsh in the Lower Mississippi River Delta, Louisiana

Synthetic aperture radar (SAR) mapping of density as an enhancement of Phragmites australis optical live fractional cover (LFC) mapping was carried out in the lower Mississippi Delta during 2016 to 2019. Also, as part of the study, the replacement of P. australis with elephant-ear was analyzed. To that end, yearly maps from 2016 to 2019 of L-band SAR horizontal send, vertical receive (HV) data representing marsh density were produced for the lower Mississippi River Delta. The mapping indicated high local variability within broad yearly density change in P. australis marsh. LFC mapping indicated a similar pattern of broad yearly change. That overall density and LFC linear correspondence was confirmed with regressions of P. australis marsh HV-density data and optical-LFC data. Local differences reflected as high scatter in the plots. Based on those results, a combined LFC and HV-density assessment tracker of P. australis condition was developed. Major findings from the use of the trajectory tool were the high decrease in HV density from 2016 to 2017, the identification of severely degraded P. australis marsh and European P. australis marsh in some areas, and indications of linkage between the density decline from 2016 to 2017 and the elephant-ear replacement from 2018 to 2019. The trajectory tool application also indicated an inverse relationship between elephant-ear occurrence and HV-density changes from 2018 to 2019. A similar but weaker relationship was found between elephant-ear and LFC. These relationships may provide a means for early detection of replacement of P. australis marsh by elephant-ear and other unwanted plant species.

Louisiana↗
USGS2020

Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana

In response to a co-occurring non-native scale infestation and Phragmites australis dieback in southeast Louisiana, normalized difference vegetation index (NDVI) satellite mapping was implemented to track P. australis condition in the lower Mississippi River Delta. While the NDVI mapping successfully documented relative condition changes, identification of cause required a quantitative-biophysical metric directly related to P. australis marsh live vegetation proportion. During this study, a satellite mapping tool that quantified P. australis live fraction cover (LFC) magnitude was designed and implemented. The key to development of the quantitative LFC mapping was the field to satellite calibration design. The calibration of P. australis marsh LFC to optical satellite image data combined field and near-in-time satellite data collections in the fall of 2018 and summer of 2019. Basing the field-NDVI to field-LFC calibrations and the satellite-NDVI to field-NDVI calibrations on combined pre-senescence and peak-growth period data offers nearly year-round LFC mapping. The utility of the developed P. australis marsh LFC mapping tool was demonstrated by the creation of a yearly suite of Mississippi River Delta LFC status and change maps extending from 2009 to 2019. P. australis marsh LFC mapping relies on Sentinel-2 for current to future mapping and relies on Landsat for historical mapping.

Louisiana↗
USGS2019

Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya

As part of the U.S. Department of the Interior’s (DOI) commitment to provide technical assistance to the Kenyan Northern Rangelands Trust (NRT), the U.S. Geological Survey, in collaboration with the DOI International Technical Assistance Program and the U.S. Agency for International Development’s regional mission in East Africa, created a high spatial and time-sensitive live vegetation monitoring system for NRT. The system built with advanced field and sensor technologies produced directly calibrated and highly accurate satellite mapping that is extendable both forward and backward in time. The maps are produced in a simple 0–100-percent representation of live vegetation status and change over time. The backbone of the mapping is the Sentinel satellite remote sensing systems with 5-day collection frequencies and ground spatial resolutions of 10 meters. The European Space Agency (ESA) offers free Sentinel satellite image data through conveniently accessed websites and free user-friendly image processing software downloadable directly onto a personal workstation. ESA provides free online software support. The mapping capability was extended from the forward mapping of Sentinel back in time with the Landsat satellite remote sensing system that has an available and free data archive back to 1983. Although Landsat has coarser spatial resolution, the Landsat to Sentinel live vegetation mapping comparison supports the use of Landsat to provide NRT the historical recreation of prominent live vegetation changes.

Open-File Report↗
USGS2018

Hyperspectral remote sensing of wetland vegetation

Chapter 11 by Ramsey and Rangoonwala provides an overview of how hyperspectral imaging (HSI) advances the mapping of coastal wetlands that comprise a unique variety of plant species, forms, and associations. Each description begins by seeking to uncover the relationship between canopy hyperspectral reflectance and one or more of the aggregated biophysical properties of the wetland canopy: leaf spectral properties, canopy structure, or background reflectance. Examples incorporate the application of radiative transfer equations, direct measurements, and above the top of canopy reflectance and photography. First demonstrated is how HSI can elucidate relations observed with broadband mapping of mangroves as well as enhance change detection. Similar uses of HSI are suggested for the mapping of cypress and bottomland hardwood forests. Next, the mapping of invasive plants is used to demonstrate how HSI can be used to transfer high-spatial-resolution broadband information to spatial resolutions amenable to regional mapping. The demonstration also includes the fusion of HSI and broadband mapping for added-value regional risk assessment of invasive establishment. Illustrations and discussion then show that the proper interpretation of HSI canopy reflectance can require measurement of both the marsh canopy structure and its compositional biomass. The final HSI application demonstrates the capability to detect and track abnormal marsh change at the leaf and canopy levels within variable backgrounds. It further shows how necessary HSI spectral information can be identified and captured in a limited number of narrowbands for advancing operational mapping.

Book chapter↗
USGS2017

Mapping the change of Phragmites australis live biomass in the lower Mississippi River Delta marshes

Multiyear remote sensing mapping of the normalized difference vegetation index (NDVI) was carried out as an indicator of live biomass composition of the Phragmites australis (hereafter Phragmites ) marsh in the lower Mississippi River Delta (hereafter delta) from 2014 to 2017. Maps of NDVI change showed that the Phragmites condition was fairly stable between May 2014 and July 2015. From July 2015 to April 2016 NDVI change indicated Phragmites suffered a widespread decline in the live biomass proportion. Between April and September 2016, most marsh remained unchanged from the earlier period or showed improvement; although there were pockets of continued decline scattered throughout the lower delta. From September 2016 to May 2017 a pronounced and widely exhibited decline in the condition of Phragmites marsh again occurred throughout the lower delta. This final NDVI change mapping supported field observations of Phragmites decline during the same period.

Louisiana↗
USGS2017

Operational shoreline mapping with high spatial resolution radar and geographic processing

A comprehensive mapping technology was developed utilizing standard image processing and available GIS procedures to automate shoreline identification and mapping from 2 m synthetic aperture radar ( SAR ) HH amplitude data. The development used four NASA Uninhabited Aerial Vehicle SAR ( UAVSAR ) data collections between summer 2009 and 2012 and a fall 2012 collection of wetlands dominantly fronted by vegetated shorelines along the Mississippi River Delta that are beset by severe storms, toxic releases, and relative sea-level rise. In comparison to shorelines interpreted from 0.3 m and 1 m orthophotography, the automated GIS 10 m alongshore sampling found SAR shoreline mapping accuracy to be ±2 m, well within the lower range of reported shoreline mapping accuracies. The high comparability was obtained even though water levels differed between the SAR and photography image pairs and included all shorelines regardless of complexity. The SAR mapping technology is highly repeatable and extendable to other SAR instruments with similar operational functionality.

Photogrammetric Engineering and Remote Sensing↗
USGS2016

Wetland shoreline recession in the Mississippi River Delta from petroleum oiling and cyclonic storms

We evaluate the relative impact of petroleum spill and storm surge on near-shore wetland loss by quantifying the lateral movement of coastal shores in upper Barataria Bay, Louisiana (USA), between June 2009 and October 2012, a study period that extends from the year prior to the Deepwater Horizon spill to 2.5 years following the spill. We document a distinctly different pattern of shoreline loss in the 2 years following the spill, both from that observed in the year prior to the spill, during which there was no major cyclonic storm, and from change related to Hurricane Isaac, which made landfall in August 2012. Shoreline erosion following oiling was far more spatially extensive and included loss in areas protected from wave-induced erosion. We conclude that petroleum exposure can substantially increase shoreline recession particularly in areas protected from storm-induced degradation and disproportionally alters small oil-exposed barrier islands relative to natural erosion.

Louisiana↗
USGS2016

Response and resilience of Spartina alterniflora to sudden dieback

We measured an array of biophysical and spectral variables to evaluate the response and recovery of Spartina alterniflora to a sudden dieback event in spring and summer 2004 within a low marsh in coastal Virginia, USA. S. alterniflora is a foundation species, whose loss decreases ecosystem services and potentiates ecosystem state change. Long-term records of the potential environmental drivers of dieback such as precipitation and tidal inundation did not evidence any particular anomalies, although Hurricane Isabel in fall 2003 may have been related to dieback. Transects were established across the interface between the dieback area and apparently healthy areas of marsh. Plant condition was classified based on ground cover within transects as dieback, intermediate and healthy. Numerous characteristics of S. alterniflora culms within each condition class were assessed including biomass, morphology and spectral attributes associated with photosynthetic pigments. Plants demonstrated evidence of stress in 2004 and 2005 beyond areas of obvious dieback and resilience at a multi-year scale. Resilience of the plants was evident in recovery of ground cover and biomass largely within 3 y, although a small remnant of dieback persisted for 8 y. Culms surviving within the dieback and areas of intermediate impact had modified morphological traits and spectral response that reflected stress. These morphometric and spectral differences among plant cover condition classes serve as guidelines for monitoring of dieback initiation, effects and subsequent recovery. Although a number of environmental and biotic parameters were assessed relative to causation, the reason for this particular dieback remains largely unknown, however.

Virginia↗
USGS2016

Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy

This study combined a radar-based time series of Hurricane Sandy surge and estimated persistence with optical sensor-based marsh condition change to assess potential causal linkages of surge persistence and marsh condition change along the New Jersey Atlantic Ocean coast. Results based on processed TerraSAR-X and COSMO-SkyMed synthetic aperture radar (SAR) images indicated that surge flooding persisted for 12 h past landfall in marshes from Great Bay to Great Egg Harbor Bay and up to 59 h after landfall in many back-barrier lagoon marshes. Marsh condition change (i.e. loss of green marsh vegetation) was assessed from optical satellite images (Satellite Pour l’Observation de la Terre and Moderate Resolution Imaging Spectroradiometer) collected before and after Hurricane Sandy. High change in condition often showed spatial correspondence, with high surge persistence in marsh surrounding the lagoon portion of Great Bay, while in contrast, low change and high persistence spatial correspondence dominated the interior marshes of the Great Bay and Great Egg Harbor Bay estuaries. Salinity measurements suggest that these areas were influenced by freshwater discharges after landfall possibly mitigating damage. Back-barrier marshes outside these regions exhibited mixed correspondences. In some cases, topographic features supporting longer surge persistence suggested that non-correspondence between radar and optical data-based results may be due to differential resilience; however, in many cases, reference information was lacking to determine a reason for non-correspondence.

New Jersey↗
USGS2016

Marsh canopy structure changes and the Deepwater Horizon oil spill

Marsh canopy structure was mapped yearly from 2009 to 2012 in the Barataria Bay, Louisiana coastal region that was impacted by the 2010 Deepwater Horizon (DWH) oil spill. Based on the previously demonstrated capability of NASA's UAVSAR polarimetric synthetic aperture radar (PolSAR) image data to map Spartina alterniflora marsh canopy structure, structure maps combining the leaf area index (LAI) and leaf angle distribution (LAD, orientation) were constructed for yearly intervals that were directly relatable to the 2010 LAI-LAD classification. The yearly LAI-LAD and LAI difference maps were used to investigate causes for the previously revealed dramatic change in marsh structure from prespill (2009) to postspill (2010, spill cessation), and the occurrence of structure features that exhibited abnormal spatial and temporal patterns. Water level and salinity records showed that freshwater releases used to keep the oil offshore did not cause the rapid growth from 2009 to 2010 in marsh surrounding the inner Bay. Photointerpretation of optical image data determined that interior marsh patches exhibiting rapid change were caused by burns and burn recovery, and that the pattern of 2010 to 2011 LAI decreases in backshore marsh and extending along some tidal channels into the interior marsh were not associated with burns. Instead, the majority of 2010 to 2011 shoreline features aligned with vectors displaying the severity of 2010 shoreline oiling from the DWH spill. Although the association is not conclusive of a causal oil impact, the coexistent pattern is a significant discovery. PolSAR marsh structure mapping provided a unique perspective of marsh biophysical status that enhanced detection of change and monitoring of trends important to management effectiveness.

Louisiana↗
USGS2015

Structural classification of marshes with Polarimetric SAR highlighting the temporal mapping of marshes exposed to oil

Empirical relationships between field-derived Leaf Area Index (LAI) and Leaf Angle Distribution (LAD) and polarimetric synthetic aperture radar (PolSAR) based biophysical indicators were created and applied to map S. alterniflora marsh canopy structure. PolSAR and field data were collected near concurrently in the summers of 2010, 2011, and 2012 in coastal marshes, and PolSAR data alone were acquired in 2009. Regression analyses showed that LAI correspondence with the PolSAR biophysical indicator variables equaled or exceeded those of vegetation water content (VWC) correspondences. In the final six regressor model, the ratio HV/VV explained 49% of the total 77% explained LAI variance, and the HH-VV coherence and phase information accounted for the remainder. HV/HH dominated the two regressor LAD relationship, and spatial heterogeneity and backscatter mechanism followed by coherence information dominated the final three regressor model that explained 74% of the LAD variance. Regression results applied to 2009 through 2012 PolSAR images showed substantial changes in marsh LAI and LAD. Although the direct cause was not substantiated, following a release of freshwater in response to the 2010 Deepwater Horizon oil spill, the fairly uniform interior marsh structure of 2009 was more vertical and dense shortly after the oil spill cessation. After 2010, marsh structure generally progressed back toward the 2009 uniformity; however, the trend was more disjointed in oil impact marshes.

Louisiana↗
USGS2015

Marsh canopy leaf area and orientation calculated for improved marsh structure mapping

An approach is presented for producing the spatiotemporal estimation of leaf area index (LAI) of a highly heterogeneous coastal marsh without reliance on user estimates of marsh leaf-stem orientation. The canopy LAI profile derivation used three years of field measured photosynthetically active radiation (PAR) vertical profiles at seven S. alterniflora marsh sites and iterative transform of those PAR attenuation profiles to best-fit light extinction coefficients (KM). KM sun zenith dependency was removed obtaining the leaf angle distribution (LAD) representing the average marsh orientation and the LAD used to calculate the LAI canopy profile. LAI and LAD reproduced measured PAR profiles with 99% accuracy and corresponded to field documented structures. LAI and LAD better reflect marsh structure and results substantiate the need to account for marsh orientation. The structure indexes are directly amenable to remote sensing spatiotemporal mapping and offer a more meaningful representation of wetland systems promoting biophysical function understanding.

Photogrammetric Engineering and Remote Sensing↗
USGS2014

Oil source-fingerprinting in support of polarimetric radar mapping of Macondo-252 oil in Gulf Coast marshes

Polarimetric synthetic aperture radar (PolSAR) data exhibited dramatic, spatially extensive changes from June 2009 to June 2010 in Barataria Bay, Louisiana. To determine whether these changes were associated with the Deepwater Horizon (DWH) oil spill, twenty-nine sediment samples were collected in 2011 from shoreline and nearshore–interior coastal marsh locations where oil was not observed visually or with optical sensors during the spill. Oil source-fingerprinting and polytopic vector analysis were used to link DWH oil to PolSAR changes. Our results prove that DWH oil extended beyond shorelines and confirm the association between presence of DWH oil and PolSAR change. These results show that the DWH oil spill probably affected much more of the southeastern Louisiana marshland than originally concluded from ground and aerial surveys and verify that PolSAR is a powerful tool for tracking oil intrusion into marshes with high probability even where contamination is not visible from above the canopy.

Louisiana↗
USGS2014

Marsh dieback, loss, and recovery mapped with satellite optical, airborne polarimetric radar, and field data

Landsat Thematic Mapper and Satellite Pour l'Observation de la Terre (SPOT) satellite based optical sensors, NASA Uninhabited Aerial Vehicle synthetic aperture radar (UAVSAR) polarimetric SAR (PolSAR), and field data captured the occurrence and the recovery of an undetected dieback that occurred between the summers of 2010, 2011, and 2012 in the Spartina alterniflora marshes of coastal Louisiana. Field measurements recorded the dramatic biomass decrease from 2010 to 2011 and a biomass recovery in 2012 dominated by a decrease of live biomass, and the loss of marsh as part of the dieback event. Based on an established relationship, the near-infrared/red vegetation index (VI) and site-specific measurements delineated a contiguous expanse of marsh dieback encompassing 6649.9 ha of 18,292.3 ha of S. alterniflora marshes within the study region. PolSAR data were transformed to variables used in biophysical mapping, and of this variable suite, the cross-polarization HV (horizontal send and vertical receive) backscatter was the best single indicator of marsh dieback and recovery. HV backscatter exhibited substantial and significant changes over the dieback and recovery period, tracked measured biomass changes, and significantly correlated with the live/dead biomass ratio. Within the context of regional trends, both HV and VI indicators started higher in pre-dieback marshes and exhibited substantially and statistically higher variability from year to year than that exhibited in the non-dieback marshes. That distinct difference allowed the capturing of the S. alterniflora marsh dieback and recovery; however, these changes were incorporated in a regional trend exhibiting similar but more subtle biomass composition changes.

Louisiana↗
USGS2013

Coastal flood inundation monitoring with Satellite C-band and L-band Synthetic Aperture Radar data

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm- and tidal-related flooding of spatially extensive coastal marshes within the north-central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L-Band SAR (PALSAR) (L-band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C-band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006-2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR- and ASAR-based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference-scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR-based inundation accuracies averaged 84% (n = 160), while ASAR-based mapping accuracies averaged 62% (n = 245).

Louisiana↗