PO4, NO3, NO2 surface concentrations along the US GEOTRACES North Atlantic Transect from the R/V Knorr KN199-04, KN199-05 cruises in the subtropical N. Atlantic during 2010 (U.S. GEOTRACES NAT project)

Dataset: GT10 - Nanomolar Nutrients - SurfacePO4, NO3, NO2 surface concentrations along the US GEOTRACES North Atlantic Transect from the R/V Knorr KN199-04, KN199-05 cruises in the subtropical N. Atlantic during 2010. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/3470NSF Division of Ocean Sciences (NSF OCE) OCE-0926423, NSF Division of Ocean Sciences (NSF OCE) OCE-092609

Surface transects for arsenic speciation, antimony speciation, and alkaline phosphatase activity from R/V Knorr cruise KN204-01 in the Subtropical North Atlantic Ocean in 2011 (U.S. GEOTRACES NAT project)

Dataset: GT11 - As AP Surface TransectsSurface transects for arsenic speciation, antimony speciation, and alkaline phosphatase activity. Data for the concentrations of the dissolved (<0.4 µm) arsenic species: total inorganic As (III+V), arsenite (AsIII), As(V), monomethyl As, dimethyl As, and the activity of the enzyme alkaline phosphatase (unfiltered). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/3830NSF Division of Ocean Sciences (NSF OCE) OCE-0926423, NSF Division of Ocean Sciences (NSF OCE) OCE-092609

Surface arsenic, antimony speciation, and alkaline phosphatase activity along with US GEOTRACES North Atlantic Transect from the R/V Knorr KN199-04, KN199-05 cruises in the subtropical N. Atlantic during 2010 (U.S. GEOTRACES NAT project)

Dataset: GT10 - As AP Surface TransectsData for the concentrations of the dissolved (<0.4 µm) arsenic species: total inorganic As (III+V), arsenite (AsIII), arsenate (AsV), monomethyl As, and dimethyl As; and the activity of the enzyme alkaline phosphatase (unfiltered) on the surface transect. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/3520NSF Division of Ocean Sciences (NSF OCE) OCE-0926423, NSF Division of Ocean Sciences (NSF OCE) OCE-092609

Do Parking Requirements Significantly Increase The Area Dedicated To Parking? A Test Of The Effect Of Parking Requirements Values In Los Angeles County

Minimum parking requirements are the norm for urban and suburban development in the United States (Davidson and Dolnick (2002)). The justification for parking space requirements is that overflow parking will occupy nearby street or off-street parking. Shoup (1999) and Willson (1995) provides cases where there is reason to believe that parking space requirements have forced parcel developers to place more parking than they would in the absence of parking requirements. If the effect of parking minimums is to significantly increase the land area devoted to parking, then the increase in impervious surfaces would likely cause water quality degradation, increased flooding, and decreased groundwater recharge. However, to our knowledge the existing literature does not test the effect of parking minimums on the amount of lot space devoted to parking beyond a few case studies. This paper tests the hypothesis that parking space requirements cause an oversupply of parking by examining the implicit marginal value of land allocated to parking spaces. This is an indirect test of the effects of parking requirements that is similar to Glaeser and Gyourko (2003). A simple theoretical model shows that the marginal value of additional parking to the sale price should be equal to the cost of land plus the cost of parking construction. We estimate the marginal values of parking and lot area with spatial methods using a large data set from the Los Angeles area non-residential property sales and find that for most of the property types the marginal value of parking is significantly below that of the parcel area. This evidence supports the contention that minimum parking requirements significantly increase the amount of parcel area devoted to parking.Minimum Parking Requirements; Land Use; Externalities

The uneasy case for lower Parking Standards

Minimum parking requirements are the norm for urban and suburban development in the United States (Davidson and Dolnick (2002)). The justification for parking space requirements is that overflow parking will occupy nearby street or off-street parking. Shoup (1999) and Willson (1995) provides cases where there is reason to believe that parking space requirements have forced parcel developers to place more parking than they would in the absence of parking requirements. If the effect of parking minimums is to significantly increase the land area devoted to parking, then the increase in impervious surfaces would likely cause water quality degradation, increased flooding, and decreased groundwater recharge. However, to our knowledge the existing literature does not test the effect of parking minimums on the amount of lot space devoted to parking beyond a few case studies. This paper tests the hypothesis that parking space requirements cause an oversupply of parking by examining the implicit marginal value of land allocated to parking spaces. This is an indirect test of the effects of parking requirements that is similar to Glaeser and Gyourko (2003). A simple theoretical model shows that the marginal value of additional parking to the sale price should be equal to the cost of land plus the cost of parking construction. We estimate the marginal values of parking and lot area with spatial methods using a large data set from the Los Angeles area non-residential property sales and find that for most of the property types the marginal value of parking is significantly below that of the parcel area. This evidence supports the contention that minimum parking requirements significantly increase the amount of parcel area devoted to parking. JEL codes:R52, H23Parking, Land Use, Sprawl

Underwater Video Survey: Planning and Data Processing

The importance of underwater video surveys as an exploration tool has been steadily increasing over recent years [1]. Better photographic equipment, more effective sources of illumination, and improved processing techniques - all make video surveying a reliable tool for seafloor habitat mapping, sediment boundary delineation and groundtruthing, mapping and documentation of forensic and archaeological sites. There is a change in attitude towards video surveying that affects the way the data is collected, and hence its quality. Earlier video data processing algorithms had to cope with whatever was recorded (often simultaneously with acquisition of other data, considered to be more important). Now we have a chance to plan ahead and organize a survey in a way most suitable for the processing. The goal of this paper is to review available processing techniques and to discuss preferable survey patterns, associated errors and processing stability

Improvement of Image Alignment Using Camera Attitude Information

We discuss a proposed technique for incorporation of information from a variety of sensors in a video imagery processing pipeline. The auxiliary information allows one to simplify computations, effectively reducing the number of independent parameters in the transformation model. The mosaics produced by this technique are adequate for many applications, in particular habitat mapping. The algorithm, demonstrated through simulations and hardware configuration, is described in detai

Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast

Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.

Seafloor Segmentation Based on Bathymetric Measurements from Multibeam Echosounders Data

Bathymetric data depicts the geomorphology of the seabottom and allows characterization of spatial distributions of apparent benthic habitats. The variability of seafloor topography can be defined as a texture. This prompts for the application of well developed image processing techniques for automatic delineation of regions with clucially different physiographic characteristics. In the present paper histograms of biologically motivated invariant image attributes are used for characterization of local geomorphological feahires. This technique can be naturally applied in a range of spatial scales. Local feature vectors are then submitted to a procedure which divides the set into a number of clusters each representing a distinct type of the seafloor. Prior knowledge about benthic habitat locations allows the use of supervised classification, by training a Suppolt Vector Machine on a chosen data set, and then applying the developed model to a full set. The classification method is shown to perform well on the multibeam echosounder (MBES) data from Piscataqua River, New Hampshire, USA