Geology topics

Chuanmin Hu

Publications and source records attributed to Chuanmin Hu.

7 recordsLinked to original sources

USGS2022

The influence of satellite-derived environmental and oceanographic parameters on marine turtle time at surface in the Gulf of Mexico

The aftermath of the 2010 Deepwater Horizon oil spill highlighted the lack of baseline spatial, behavioral, and abundance data for many species, including imperiled marine turtles, across the Gulf of Mexico. The ecology of marine turtles is closely tied to their vertical movements within the water column and is therefore critical knowledge for resource management in a changing ocean. A more comprehensive understanding of diving behavior, specifically surface intervals, can improve the accuracy of density and abundance estimates by mitigating availability bias. Here, we focus on the proportion of time marine turtles spend at the top 2 m of the water column to coincide with depths where turtles are assumed visible to observers during aerial surveys. To better understand what environmental and oceanographic conditions influence time at surface, we analyzed dive and spatial data from 136 satellite tags attached to three species of threatened or endangered marine turtles across 10 years. We fit generalized additive models with 11 remotely sensed covariates, including sea surface temperature (SST), bathymetry, and salinity, to examine dive patterns. Additionally, the developed model is the first to explicitly examine the potential connection between turtle dive patterns and ocean frontal zones in the Gulf of Mexico. Our results show species-specific associations of environmental covariates related to increased time at surface, particularly for depth, salinity, and frontal features. We define seasonal and spatial variation in time-at-surface patterns in an effort to contribute to marine turtle density and abundance estimates. These estimates could then be utilized to generate correction factors for turtle detection availability during aerial surveys.

Gulf of Mexico↗

USGS2020

Classification of oil spill by thicknesses using multiple remote sensors

Satellite Synthetic Aperture Radar (SAR) is an operational tool for monitoring and assessment of oil spills. Satellite SAR has primarily been used to detect the presence/absence of oil, yet its ability to discriminate oil emulsions within a detected oil slick has not been fully exploited. Additionally, one of the challenges in the past has been the ability to deliver strategic information derived from satellite remote sensing in a timely fashion to responders in the field. This study presents methods for the rapid classification of oil types and estimated thicknesses, from which information about thick oil and oil emulsions (i.e., “actionable” oil) can be delivered in an operational timeframe to responders in the field. Experiments carried out at the OHMSETT test facility in New Jersey demonstrate that under specific viewing conditions, a single polarization satellite SAR image can record a signal variance between thick stable emulsions and non-emulsified oil. During a series of field campaigns in the Gulf of Mexico with in situ measurements of oil thickness, multiple satellite data were obtained including fully polarimetric C-band SAR imagery from RADARSAT-2 and multispectral imagery from ASTER and WorldView-2. One campaign included the airborne polarimetric UAVSAR L-band sensor. An oil/emulsion thickness classification product was generated based on RADARSAT-2 polarimetric imagery using entropy and the damping ratio derivations. Herein, we present the classification methods to generate oil thickness products from SAR, validated by sea-truth observations, the multispectral imagery, and the UAVSAR data. We tested the ability to deliver these products with minimum latency to responding vessels via NOAA. During field operations in the Gulf of Mexico, a satellite SAR-based product of oil delineation by relative thickness was delivered to a responding vessel 42 min after the RADARSAT-2 data acquisition. This proof-of-concept test using satellite SAR and multispectral imagery to detect emulsions and deliver a derived information product to a vessel in near-real-time points directly to methods for satellite-based assets to be used in the near future for oil spill tactical response operations.

Louisiana↗

USGS2016

Remote estimation of surface pCO2 on the West Florida Shelf

Surface p CO 2 data from the West Florida Shelf (WFS) have been collected during 25 cruise surveys between 2003 and 2012. The data were scaled up using remote sensing measurements of surface water properties in order to provide a more nearly synoptic map of p CO 2 spatial distributions and describe their temporal variations. This investigation involved extensive tests of various model forms through parsimony and Principal Component Analysis, which led to the development of a multi-variable empirical surface p CO 2 model based on concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) estimates of surface chlorophyll a concentrations (CHL, mg m −3 ), diffuse light attenuation at 490 nm (Kd_Lee, m −1 ), and sea surface temperature (SST, °C). Validation using an independent dataset showed a p CO 2 Root Mean Square Error (RMSE) of <12 µatm and a 0.88 coefficient of determination (R 2 ) for measured and model-predicted p CO 2 ranging from 300 to 550 µatm. The model was more sensitive to SST than to CHL and Kd_Lee, with a 1 °C change in SST leading to a ~16 µatm change in the predicted p CO 2 . Application of the model to the entire WFS MODIS time series between 2002 and 2014 showed clear seasonality, with maxima (~450 µatm) in summer and minima (~350 µatm) in winter. The seasonality was positively correlated to SST (high in summer and low in winter) and negatively correlated to CHL and Kd_Lee (high in winter and low in summer). Inter-annual variations of p CO 2 were consistent with inter-annual variations of SST, CHL, and Kd_Lee. These results suggest that surface water p CO 2 of the WFS can be estimated, with known uncertainties, from remote sensing. However, while the general approach of empirical regression may work for waters from other areas of the Gulf of Mexico, model coefficients need to be empirically determined in a similar fashion.

Continental Shelf Research↗

USGS2016

Oil slick morphology derived from AVIRIS measurements of the Deepwater Horizon oil spill: Implications for spatial resolution requirements of remote sensors

Using fine spatial resolution (~ 7.6 m) hyperspectral AVIRIS data collected over the Deepwater Horizon oil spill in the Gulf of Mexico, we statistically estimated slick lengths, widths and length/width ratios to characterize oil slick morphology for different thickness classes. For all AVIRIS-detected oil slicks (N = 52,100 continuous features) binned into four thickness classes (≤ 50 μm but thicker than sheen, 50–200 μm, 200–1000 μm, and > 1000 μm), the median lengths, widths, and length/width ratios of these classes ranged between 22 and 38 m, 7–11 m, and 2.5–3.3, respectively. The AVIRIS data were further aggregated to 30-m (Landsat resolution) and 300-m (MERIS resolution) spatial bins to determine the fractional oil coverage in each bin. Overall, if 50% fractional pixel coverage were to be required to detect oil with thickness greater than sheen for most oil containing pixels, a 30-m resolution sensor would be needed.

Marine Pollution Bulletin↗

USGS2014

Whiting events in SW Florida coastal waters: a case study using MODIS medium-resolution data

Whitings, floating patches of calcium carbonate mud, have been found in both shallow carbonate banks and freshwater environments around the world. Although these events have been studied for many decades, much of their characteristics remain unknown. Recent sightings of whitings near Ten Thousand Islands, Florida suggest a phenomenon that has not previously been documented in this area. Using medium-resolution (250-m) data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) from December 2010 to November 2013, we documented whiting events and their spatial and temporal patterns in this region. Classification rules were first established, and then applied to all 474 cloud-free and sun glint-free MODIS images. Whiting occurrences were found between 25°46′N and 25°20′N and less than 40 km from the southwest Florida coastline. Over the 3-year period, whiting occurrence peaked in spring and autumn and reached a minimum during the winter and summer months. Further field and laboratory research are needed to explain driving force(s) behind these events.

Florida↗

USGS2005

Multi-scale remote sensing of coral reefs

In this chapter we present how both direct and indirect remote sensing can be integrated to address two major coral reef applications - coral bleaching and assessment of biodiversity. This approach reflects the current non-linear integration of remote sensing for environmental assessment of coral reefs, resulting from a rapid increase in available sensors, processing methods and interdisciplinary collaborations (Andréfouët and Riegl, 2004). Moreover, this approach has greatly benefited from recent collaborations of once independent investigations (e.g., benthic ecology, remote sensing, and numerical modeling).

Florida↗

USGS2004

Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL

Using Tampa Bay, FL as an example, we explored the potential for using MODIS medium-resolution bands (250- and 500-m data at 469-, 555-, and 645-nm) for estuarine monitoring. Field surveys during 21–22 October 2003 showed that Tampa Bay has Case-II waters, in that for the salinity range of 24–32 psu, (a) chlorophyll concentration (11 to 23 mg m −3 ), (b) colored dissolved organic matter (CDOM) absorption coefficient at 400 nm (0.9 to 2.5 m −1 ), and (c) total suspended sediment concentration (TSS: 2 to 11 mg L −1 ) often do not co-vary. CDOM is the only constituent that showed a linear, inverse relationship with surface salinity, although the slope of the relationship changed with location within the bay. The MODIS medium-resolution bands, although designed for land use, are 4–5 times more sensitive than Landsat-7/ETM+ data and are comparable to or higher than those of CZCS. Several approaches were used to derive synoptic maps of water constituents from concurrent MODIS medium-resolution data. We found that application of various atmospheric-correction algorithms yielded no significant differences, due primarily to uncertainties in the sensor radiometric calibration and other sensor artifacts. However, where each scene could be groundtruthed, simple regressions between in situ observations of constituents and at-sensor radiances provided reasonable synoptic maps. We address the need for improvements of sensor calibration/characterization, atmospheric correction, and bio-optical algorithms to make operational and quantitative use of these medium-resolution bands.

Florida↗