Physical Sciences and Mathematics Commons^™

Quality Of Life In A “High-Rise Lawless Slum”: A Study Of The Kowloon Walled City, Prudencea Leung Kwok Lau, Lawrenceb Wai Chung Lai, Daniel Chi Wing Ho

Faculty of Design & Environment (THEi)

Informed by the ‘quality of life’ model with specific reference to Chinese culture, this article uses reliable and publicly available information seldom used in historical or heritage study to identify the designs of flats and builders of the “Kowloon Walled City” (hereafter the City) and reliable oral testimonies to refute some myths about the quality of life within it. This settlement has been notoriously misrepresented by some as a city of darkness that was razed from the face of the Earth before 1997 to fulfill a pre-war dream of the colonial government. This article confirms the view that this extremely …

Designing Sustainable Landscapes: Topographic Wetness And Flow Volume Settings Variables, Kevin Mcgarigal, Brad Compton, Ethan Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Topographic wetness and flow volume are two of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). These variables are two ways of assessing the flow of water; they share an underlying algorithm. Topographic wetness gives an estimate of the amount of moisture at any point in the landscape based on topography, which has a major effect on species habitat, soils, and the nutrient cycle. It ranges, in arbitrary units, from low values at hilltops and steep upper slopes to high values in low, …

Designing Sustainable Landscapes: Tides Settings Variable, Kevin Mcgarigal, Brad Compton, Ethan B. Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Tides is one of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). Tides estimates the probability that a point is intertidal or subtidal. It is derived from a logistic regression model using tide range and elevation to distinguish mapped salt marshes from uplands.

Designing Sustainable Landscapes: Development Settings Variable, Hard Development Settings Variable, Kevin Mcgarigal, Brad Compton, Ethan Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Development and hard development are two of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). Development represents all development, scaled from 0 to 10 by development intensity. Hard development is a subset of development, with a value of 1 for very high intensity development only. Both layers come from DSLland, the primary landcover map. These are dynamic settings variables, increasing with future urban growth.

Designing Sustainable Landscapes: Substrate Mobility Settings Variable, Kevin Mcgarigal, Brad Compton, Ethan B. Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Substrate mobility is one of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). Substrate mobility measures the realized mobility of the physical substrate, due to both substrate composition (e.g., sand) and exposure to forces (wind and water) that transport material. This is an important attribute of certain dynamic systems (e.g., coastal dune systems); given as a simple index of mobility (1 = stable, 10 = highly mobile). Substrate mobility is assigned by landcover class, derived from expert opinion. This settings variable is dynamic, …

Designing Sustainable Landscapes: Wind Exposure Settings Variable, Kevin Mcgarigal, Brad Compton, Ethan Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Wind exposure is one of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). Wind exposure gives the mean sustained wind speed (m/s) at 50 m height. High wind speeds can shape natural communities, especially on exposed high peaks.

Designing Sustainable Landscapes: Water Salinity Settings Variable, Kevin Mcgarigal, Brad Compton, Ethan Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

Water salinity is one of several ecological settings variables that collectively characterize the biophysical setting of each 30 m cell at a given point in time (McGarigal et al 2017). Salinity, which varies from 0‰ in freshwater to 30‰ in seawater, is a major driver of aquatic systems, as very few organisms can survive across this full range.

Designing Sustainable Landscapes: Index Of Ecological Integrity, Kevin Mcgarigal, Brad Compton, Ethan Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

The index of ecological integrity (IEI) is a measure of relative intactness (i.e., freedom from adverse human modifications and disturbance) and resiliency to environmental change (i.e., capacity to recover from or adapt to changing environmental conditions driven by human land use and climate change). It is a composite index derived from up to 21 different landscape metrics, each measuring a different aspect of intactness (e.g., road traffic intensity, percent impervious) and/or resiliency (e.g., ecological similarity, connectedness) and applied to each 30 m cell (see technical document on integrity, McGarigal et al 2017). The index is scaled 0-1 by ecological system …

Ecological Integrity Metrics: All Integrity Data Products, Kevin Mcgarigal, Brad Compton, Ethan B. Plunkett, Bill Deluca, Joanna Grand

Data and Datasets

The ecological integrity products represent a set of metrics corresponding to our ecosystem-based ecological assessment in 2010 (see Integrity document for details). The ecological integrity metrics include a variety of measures of intactness and resiliency. The individual metrics are also combined into a composite local index of ecological integrity (IEI).

Gis Data: Essex County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner

Data

No abstract provided.

Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith

Data

Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays.

Gis Data: New Kent County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

No abstract provided.

Gis Data: Caroline County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl H. Hershner

Data

No abstract provided.

Gis Data: Caroline County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: Caroline County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

No abstract provided.

Gis Data: Richmond County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

No abstract provided.

Gis Data: Richmond County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: Richmond County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

No abstract provided.

Gis Data: Essex County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner

Data

No abstract provided.

Gis Data: Essex County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: New Kent County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: Arlington County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner

Data

No abstract provided.

One Day Air Traffic In The Airspace Of The United States, Yuefeng Wu

Yuefeng Wu

Informing Students About Academic Integrity In Programming., Simple Simon, Judy Sheard, Michael Morgan, Andrew Petersen, Amber Settle, Jane Sinclair

Amber Settle

Pengujian Functionality Dan Performance Sistem Inforamasi Berbasis Web Menggunakan Framework Codeigniter Di Smk Negeri 1 Jogonalan Klaten, Patan Pindoyono

Elinvo (Electronics, Informatics, and Vocational Education)

Penelitian ini bertujuan untuk menganalisis kualitas sistem informasi alumni berbasis web menggunakan framework CodeIgniter sehingga mampu: (1) mengurangi kesalahan pengelolaan data alumni SMK N 1 Jogonalan. (2) menyingkat waktu pencarian data alumni SMK N 1 Jogonalan. Pengujian yang digunakan pada penelitian ini adalah aspek functionality suitability dan aspek performance efficiency. Aspek functionality menggunakan test case yang mengacu pada analisis kebutuhan perangkat lunak. Sedangkan aspek performance efficiency dilakukan dengan menghitung waktu rata-rata respon dari sistem sebanyak lima kali percobaan. Hasil penelitian yang telah dilakukan menunjukan bahwa: (1) Sistem informasi yang dikembangkan dapat mengurangi kesalahan pegelolaan data, hal ini dibuktikan pada pada …

Obat Aborsi Cytotec Asli Wa 085875427775, Nia Diana

nia diana

Matlab Processing Scripts To Accompany Spatially Resolved Measurements Of Crosslinking In Uv-Curable Coatings Using Single-Sided Nmr, Madeline Brass, Frances Jude Morin, Tyler Meldrum

Data

These Matlab scripts are used to import CPMG data collected using a Kea spectrometer (through the program Prospa), and to process each echo using the Fourier transformation. This provides spatially resolved NMR relaxation data that can be fitted or subjected to inverse Laplace transformation (not provided) to characterize relaxation at different positions within a sample.

Conductivity, Temperature And Depth (Ctd) Data For Deepend Stations, Cruise Dp04, August 2016, David English, Chuanmin Hu, April Cook, Tracey Sutton

DEEPEND Datasets

Conductivity, temperature and depth data from the ship's CTD, which was deployed at each of the DEEPEND stations. Depth of cast was variable, but extended from near-surface waters to below the euphotic zone. This data was used in the assessment of the water column's vertical structure, and for comparison with physical models. Data were collected on cruise DP04 in August, 2016.

Gis Data: 2016 Chesapeake Bay Sav Coverage, Virginia Institute Of Marine Science, Sav Data Administrator

Data

Abstract: The 2015 Chesapeake Bay SAV Coverage was mapped from digital multispectral imagery with a 25cm GSD to assess water quality in the Bay. Each area of SAV was interpreted from the rectified imagry and classified into one of four density classes by the percentage of cover. The SAV beds were entered into an SDE GIS fetaure class using the quality control procedures documented below. The dataset contains all SAV areas that were identified from the areas flown. Some areas that are presumed to contain no SAV were not flown. Some small beds, particularly along narrow tributaries may not have …

Emissions Of Organic Compounds From Produced Water Ponds, Seth Lyman

Browse all Datasets

We measured fluxes of methane, a suite of non-methane hydrocarbons (C2-C11), light alcohols, and carbon dioxide from oil and gas produced water storage and disposal ponds in Utah (Uinta Basin) and Wyoming (Upper Green River Basin) United States during 2013-2016. In this paper, we discuss the characteristics of produced water composition and air-water fluxes, with a focus on flux chamber measurements. In companion papers, we will (1) report on inverse modeling methods used to estimate emissions from produced water ponds, including comparisons with flux chamber measurements, and (2) discuss the development of mass transfer coefficients to estimate emissions and place …