Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Relationship between Land Use and Water Quality and its Assessment Using Hyperspectral Remote Sensing in Mid- Atlantic Estuaries

Mid-Atlantic coastal waters are under increasing pressures from anthropogenic disturbances at various temporal and spatial scales exacerbated by the climate change. According to the National Oceanic Atmospheric Association (NOAA), 10 of the 22 estuaries in the Mid-Atlantic, including the Chesapeake Bay, exhibit high levels of eutrophic conditions while seven, including Delaware Bay, exhibit low conditions. Chesapeake Bay is the largest estuarine system in the United States and undergoes frequent eutrophication and low dissolved oxygen events. Although substantially lower in nutrients compared to other Mid-Atlantic Estuaries, the biological, chemical, and ecological status of the Delaware Bay has changed in the past few decades due to high coastal tourism, increased local resident populations, and agricultural activities which have increased nutrient inputs into this shallow coastal bay. As stated by the Academy of Natural Sciences, although the nutrient load has reduced since the Clean Water Act, years of nutrient accumulation, contaminations, and sedimentation have impacted estuarine systems substantially, long-term monitoring is lacking, and ecological responses are not well quantified. Eutrophication within the Bays has degraded water quality conditions advanced by sedimentation. Understanding the quality of the water in any aquatic ecosystem is a critical first step in order to identify characteristics of that ecosystem and draw conclusions about how well adapted the system is in terms of anthropogenic activity and climate change. Determining water quality in intertidal creeks along the Chesapeake and Delaware coastlines is important because land cover is constantly changing. Many of these tidal creeks are lined with forested riparian buffers that may be intercepting nutrients from running off into the waterways. Identifying water conditions, coupled with the marsh land cover, provides a strong foundation to see if the buffer systems are providing the ecosystem services they are designed to provide. Our primary goal in this chapter is to provide research findings on the application of the hyperspectral remote sensing to monitor specific land-use activities and water quality. Along with hyperspectral remote sensing, our monitoring was coupled with the integration of remotely sensed data, global positioning system (GPS), and geographic information system (GIS) technologies that provide a valuable tool for monitoring and assessing waterways in the Mid-Atlantic Estuaries

Coastal Habitat Integrated Mapping and Monitoring Program report for the State of Florida

Mangrove swamps and salt marshes provide valuable ecological services to coastal ecosystems in Florida. Coastal wetlands are an important nursery for many ecologically and commercially important fish and invertebrates. The vegetation stabilizes shorelines, protecting the coast from wave energy, storm surge, and erosion. Coastal wetlands are also able to filter surface water runoff, removing excess nutrients and many pollutants. Peat deposits sequester large amounts of carbon, making coastal wetlands a key sink in global carbon cycles. Mangroves and salt marshes, however, are vulnerable to both direct and indirect threats from human development. Current threats include continued habitat loss, hydrologic alteration of surface and groundwater, sea-level rise, and invasive vegetation. ... Coastal wetland monitoring programs are often short-lived and vary widely in methodology. Monitoring most commonly occurs on protected public lands or at wetland mitigation or restoration sites. These monitoring projects are rarely long-term due to a lack of funding; restoration sites are generally monitored for only a few years. Although long-term funding is difficult to secure, monitoring over long time scales is increasingly important due to regional uncertainties as to how coastal wetland vegetation and substrate accretion will respond to sea-level rise, altered freshwater hydrology, and other disturbances. While periodic land cover mapping programs can capture large-scale changes in habitat extent, smaller-scale species shifts among mangrove and salt marsh vegetation are best captured by on-the-ground monitoring. The chapters in this report summarize recent mapping and monitoring programs in each region of Florida. Content of each chapter includes a general introduction to the region, location-specific threats to salt marshes and mangroves, a summary of selected mapping and monitoring programs, and recommendations for protection, management, and monitoring. Land cover maps in this report generally use data from the most recent water management district land use/land cover (LULC) maps

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

The Ecology and Sociology of the Mission-Aransas Estuary : An Estuarine and Watershed Profile

watershed profileThe Mission-Aransas National Estuarine Research Reserve (NERR) is one of 28 national estuarine reserves created to promote the responsible use and management of the nation's estuaries through a program combining scientific research, education, and stewardship. The purpose of this document is to provide researchers and resource managers with an adequate basis of knowledge to further development of scientific studies and applied management investigations. This document describes the different physical ecosystem components, ecological processes, habitats, and watersheds of the Reserve. The Mission-Aransas NERR is a complex of wetland, terrestrial, and marine environments. The land is primarily coastal prairie with unique oak motte habitats. The wetlands include riparian habitat, and freshwater and salt water marshes. Within the water areas, the bays are large, open, and include extensive wind tidal flats, seagrass meadows, mangroves, and oyster reefs. This site profile describes each habitat by their location, type, distribution, abundance, current status and trends, issues of concerns, and future research plans. Research within the Mission-Aransas NERR seeks to improve the understanding of the Texas coastal zone ecosystems structure and function. Current research includes: nutrient loading and transformation, estimates of community metabolism, water quality monitoring, freshwater inflow, climate change and fishery habitat. Harmful algal blooms, zooplankton, coliform bacteria, submerged aquatic vegetation, and marsh grass are monitored through the System- Wide Monitoring Program (SWMP). This document also describes the climate, hydrography and oceanography, geology, water quality, and endangered species within the Mission-AransasUniversity of Texas Marine Science InstituteMarine Scienc

Oyster Integrated Mapping and Monitoring Program report for the State of Florida

Oysters provide a variety of critical ecosystem services to coastal communities in Florida. They improve water quality and clarity as they filter feed, lessen shoreline erosion, and provide a habitat or food source for a wide variety of birds, fish, and invertebrates. Oysters are commercially valuable as a harvested food source, and historically their shell has been mined extensively for construction material. The eastern oyster (Crassostrea virginica) is the only reef-building oyster in Florida and forms both subtidal and intertidal reefs. Numerous other species of non-reef-building oysters are less frequent. This report focuses primarily on the eastern oyster, because it is the most abundant oyster in Florida and because it is important as both a keystone species and an ecosystem engineer

Assessment of indigenous forest degradation and deforestation along the wild coast, near Port St John’s, Eastern Cape Province, South Africa

Indigenous forests along the Wild Coast of the Eastern Cape Province have experienced both degradation and deforestation over the past decades. In early 2000, steps were taken to rehabilitate some of the degraded areas. Nevertheless, there is no monitoring mechanism in place, so little is known about the extent of degradation and impact of the rehabilitation efforts. The present study assesses the extent to which deforestation and degradation of the indigenous forests have occurred, and evaluates rehabilitation efforts in the study area around Port Saint John’s. Forest degradation was defined as the decrease in forest cover density while deforestation was defined as an increase in the trend of light forests and/ or a decrease in dense forests. The details for this study were obtained from multi – temporal remotely sensed data for a period between 1982 and 2013 (31 years). Multi-temporal Landsat satellite imagery for 1982, 1986, 1989, 2002, 2009 and 2013 was acquired and analysed. On the basis of prior knowledge of the area, the supervised classification approach was used. The Maximum likelihood supervised classification technique was used to extract information from satellite data. The classified images were filtered using a majority filtering procedure to reduce noise. Google Earth (Astrium) ancillary images were used to refine the classification based on expert rules. The derived changes in the degraded and rehabilitated areas were further validated through field visits. The overall image classification accuracy generated from Landsat image data ranged from 80% to 90%. It was noted that the area of dense forest almost doubled between 1986 and 1989, coinciding with a 59% decrease in the light forest. Subsequently, dense forests increased by 14,820 ha while light forests decreased by 16,690 ha between 1989 and 2002. The subsequent reduction in light forest coverage is explained by the establishment of the Participatory Forest Management (PFMA) approach by Department of Water Affairs and Forestry (DWAF) which reversed the degradation trend. However, specific degradation hotspots were identified, particularly where new settlements have been established. The emergence of the non-vegetated area increased gradually from 7% in 1986 to 23.4% in 2013. Notably, dense forest was observed to have experienced higher rates of forest degradation and deforestation than the light forest. The highest number patches were 4 recorded between 2002 and 1998, followed by between 2010 and 2013 and lastly 1986. Based on spatial connectedness of patches, the year 1986 had the highest landscape connectedness of forest vegetation (CONAT = 35.3) followed by 2002 and 1996 while the year 2010 and 2013 had the lowest landscape contiguity. Over the study period, the distribution of patches clearly shows that forest degradation and deforestation rates were lower in the years 1986, 1998 and tremendously increased in the later period of between 2010 and 2013. However, as a result of rehabilitation efforts, dense forest was seen to steadily gain more land than light forest. Finer details of degradation trends could not be easily picked from the images used in the study, given their spatial resolution limitations. That notwithstanding, the trends identified are good for overview decisions. The study has also established that de-agraianisation, forest restoration and rehabilitation greatly contributed to increased forest cover. Therefore, with more use of GIS by forest managers, and imagery of the high resolution being readily available, forests will in future be easily monitored using remote sensing

Coastal zone landscape classification using remote sensing and model development

Coastal zone landscape characterization and empirical model development were evaluated using multi-spectral airborne imagery. Collectively, four projects are described that address monitoring and classification issues common to the resource management community. Chapter 1 discusses opportunities for remote sensing. Chapter 2 examines spectral and spatial image resolution requirements, as well as training sample selection methods required for accurate landscape classification. Classification accuracy derived from 25nm imagery with 4m pixel sizes outperformed 70nm imagery with 1m pixel sizes. Eight natural and five cultural landscape features were tested for classification accuracy. Chapter 3 investigated the ability to characterize 1m multispectral imagery into rank-ordered categorical biomass index classes of Phragmites australis. Statistical clustering and sample membership was based upon normalized field-measurements. The red imagery channel showed highly significant correlation with field measurements (p = 0.00) and explained much of its variability (r2 = 0.79). Addition of near-infra red, green, and blue image channels in a forward stepwise regression improved the coefficient of determination (r2 = 0.98). In Chapter 4, a landscape cover map was revised by incorporating expert knowledge into a simple spatial model. Examples are provided for a barrier island environment to illustrate this post-classification methodology. A prototype selection of expert rules was sufficient to change more than 20 per cent of the originally classified landscape pixels. Chapter 5 discusses the development of an empirical model that uses vegetation community classes to estimate: (a) soil type, (b) soil compaction rate, and (c) elevation. Vegetation class proved itself a reliable surrogate for estimating these variables based upon field-based statistical measures of association and significance tests. Vegetation was highly associated with four soil types (Cramer\u27s V = 0.98) and soil compaction rates values at depths of 30 and 46cm (Cramer\u27s V \u3e 0.85), and was able to accurately estimate three decimeter-level elevation zones (r2 = 0.86, p = 0.00). A preliminary model to estimate transverse dune crest heights and locations under forest canopy was presented. Lastly, Chapter 6 offers a summary and concluding statements advocating continued use of remote sensing as an application tool for resource management needs

Pasturelands as natural climate solutions: a socioecological study of tree carbon and beef production trade-offs

Forest restoration is the most effective natural climate solution, with the potential to sequester 37% of the carbon dioxide (CO2) needed to reach the Paris climate mitigation goal. Cattle pastures offer an underutilized opportunity to increase global forest restoration efforts, improve biodiversity, and maximize carbon storage through the adoption of management strategies that prioritize the incorporation of trees into pasturelands. However, remote estimations of tree carbon storage in pastoral systems have never been field-verified and their accuracy is unclear. Furthermore, the effect of increased trees on cattle production is understudied across biomes. Lastly, the restoration potential of these landscapes as a byproduct of tree carbon also remains to be studied. Therefore, the aims of this study were (i) compare past remote tree carbon estimations in pastureland systems to current field estimates to assess their accuracy, (ii) evaluate the effect of increasing tree carbon (MgC ha-1) on the pastoral stocking density (AU ha-1), (iii) quantify the woody species diversity (H’) within pastures, and (iv) compare findings between farms in temperate (n = 26) and tropical (n = 16) ecosystems. To accomplish these goals, two remote datasets of global tree carbon from Harris et al., 2021 and Chapman et al., 2020 were first acquired, while the current pastoral carbon storage in temperate forest ecosystems of Virginia, USA and dry tropical forest ecosystems of Los Santos, Panama was estimated with in-situ plots. Woody plant species were also quantified to determine diversity as a metric of ecological restoration potential within these systems. We also conducted IRB-approved interviews with landowners to better understand their motivations for tree incorporation in their systems. We found that Chapman et al., 2020 significantly overestimated the carbon storage of pasturelands in Los Santos, Panama, while underestimating carbon in Virginia (p \u3c 0.001). There was no difference in MgC ha-1 between tropical farms and temperate farms, but H’ (p \u3c 0.001) and stocking density (AU ha-1) were significantly higher in Los Santos, Panama (p = 0.003). Additionally, farms enrolled in conservation programs had lower stocking densities than those that practiced traditional management (p = 0.026), but no significant differences in H’ or MgC ha-1. There was also no effect of MgC ha-1 on stocking density, which suggests that pastures with more trees did not result in a decrease in beef production. Woody species diversity (H’) was positively associated with increasing MgC ha-1 (p \u3c 0.001), in Los Santos, but not in Virginia. Landowners had overall positive perceptions of trees in their systems, but some struggled to incorporate them due to financial and labor-related hurdles. These findings demonstrate the potential for pastures to increase above ground tree carbon and potentially woody species diversity without decreasing beef production. Moreover, such efforts support landscape restoration and offer potentially novel revenue streams for farmers through carbon credit programs. Lastly, we demonstrate the importance of taking a socio-ecological approach to restoration of human-dominated systems

Effective strategies to manage dredge related threats to tropical seagrass systems based on seagrass ecological requirements

Major dredging projects have the potential to impact on tropical seagrass communities through direct removal and burial and indirectly through turbid dredge plumes reducing the amount of light available to seagrasses. This is a major concern in Australia and elsewhere in the Indo Pacific region where substantial expansion of tropical ports associated with the resources boom is occurring. In the majority of cases managing the impacts from turbid plumes has focussed on a turbidity threshold that has not been related to the true light requirements of the various seagrass species potentially impacted. Here we report on the value of an approach based on determining the minimum light requirements of species, their resilience to impacts and ability to recover and designing a dredge mitigation approach that is focussed on maintaining critical windows of light to support seagrass growth and longer term survival. Results show the value of experimentally determining locally relevant ecological requirements and the importance of understanding the relationships between light requirements, tidal exposure, shifts in spectral quality of light, seasonality and capacity for species to recover from light stress in determining ecologically relevant triggers. This information combined with a robust toolkit for assessing sub-lethal light stress provides an effective dredge mitigation strategy to protect seagrasses