Worldview-2 and Landsat 8 Satellite Data for Seaweed Mapping along Karachi Coast

Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastalwaters of Karachi. The continuous monitoring and mapping of this precious marine plant and their breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation wasachieved with WV-2 data that shows 15.5Ha (0.155 Km2)of seaweed cover along Karachi coast that is more representative of the field observed data. A much larger area wasestimated with Landsat 8 image (71.28Ha or 0.7128 Km2) that was mainly due to the mixing of seaweed pixels with water pixels. The WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat8 in mapping seaweed patche

Using RapidEye high spatial resolution imagery in mapping shallow coastal water benthic habitats

http://www.ester.ee/record=b448589

Physics-based satellite-derived bathymetry for nearshore coastal waters in North America

Accurate bathymetric information is fundamental to safe maritime navigation and infrastructure development in the coastal zone, but is expensive to acquire with traditional methods. Satellite-derived bathymetry (SDB) has the potential to produce bathymetric maps at dramatically reduced cost per unit area and physics-based radiative transfer model inversion methods have been developed for this purpose. This thesis demonstrates the potential of physics-based SDB in North American coastal waters. First the utility of Landsat-8 data for SDB in Canadian waters was demonstrated. Given the need for precise atmospheric correction (AC) for deriving robust ocean color products such as bathymetry, the performances of different AC algorithms were then evaluated to determine the most appropriate AC algorithm for deriving ocean colour products such as bathymetry. Subsequently, an approach to minimize AC error was demonstrated for SDB in a coastal environment in Florida Keys, USA. Finally, an ensemble approach based on multiple images, with acquisitions ranging from optimal to sub-optimal conditions, was demonstrated. Based on the findings of this thesis, it was concluded that: (1) Landsat-8 data hold great promise for physics-based SDB in coastal environments, (2) the problem posed by imprecise AC can be minimized by assessing and quantifying bias as a function of environmental factors, and then removing that bias in the atmospherically corrected images, from which bathymetry is estimated, and (3) an ensemble approach to SDB can produce results that are very similar to those obtained with the best individual image, but can be used to reduce time spent on pre-screening and filtering of scenes

New Simulation and Fusion Techniques for Assessing and Enhancing UAS Topographic and Bathymetric Point cloud Accuracy

Imagery acquired from unmanned aircraft systems (UAS) and processed with structure from motion (SfM) – multi-view stereo (MVS) algorithms provides transformative new capabilities for surveying and mapping. Together, these new tools are leading to a democratization of airborne surveying and mapping by enabling similar capabilities (including similar or better accuracies, albeit from substantially lower altitudes) at a fraction of the cost and size of conventional aircraft. While SfM-MVS processing is becoming widely used for mapping topography, and more recently bathymetry, empirical accuracy assessments—especially, those aimed at investigating the sensitivity of point cloud accuracy to varying acquisition and processing parameters—can be difficult, expensive, and logistically complicated. Additional challenges in bathymetric mapping from UAS imagery using SfM-MVS software relate to refraction-induced errors and lack of coverage in areas of homogeneous sandy substrate. This dissertation aims to address these challenges through development and testing of new algorithms for SfM-MVS accuracy assessment and bathymetry retrieval. A new tool for simulating UAS imagery, simUAS, is presented and used to assess SfM-MVS accuracy for topographic mapping (Chapter 2) and bathymetric mapping (Chapter 3). The importance of simUAS is that it can be used to precisely vary one parameter at a time, while perfectly fixing all others, which is possible, because the UAS data are synthetically generated. Hence, the issues of uncontrolled variables, such as changing illumination levels and moving objects in the scene, which occur in empirical experiments using real UAS, are eliminated. Furthermore, simulated experiments using this approach can be performed without the need for costly and time-intensive fieldwork. The results of these studies demonstrate how processing settings and initial camera position accuracy relate to the accuracy of the resultant point cloud. For bathymetric processing, it was found that camera position accuracy is particularly important for generating accurate results. Even when accurate camera positions are acquired for bathymetric data, SfM-MVS processing is still unable to resolve depths in regions which lack seafloor texture, such as sandy, homogeneous substrate. A new methodology is introduced and tested which uses the results from the SfM-MVS processing to train a radiometric model, which estimates water depth based on the wavelength-dependent attenuation of light in the water column (Chapter 4). The methodology is shown to increase the spatial coverage and improve the accuracy of the bathymetric data at a field site on Buck Island off of St. Croix in the U.S. Virgin Islands. Collectively, this work is anticipated to facilitate greater use of UAS for nearshore bathymetric mapping

Seasonality and nutrient-uptake capacity of Sargassum spp. in Western Australia

The eight-band high resolution multispectral WorldView-2 satellite imagery demonstrated potential for mapping and monitoring Sargassum spp. beds and other associated coastal marine habitats around Rottnest Island and Point Peron. Sargassum spp. in Western Australian coast showed seasonal changes in canopy cover and mean thallus length which are also significantly influenced by the nutrient concentrations. This study documented the life cycle of Sargassum spinuligerum and successfully cultivated the species for the first time in Western Australia