Urban Areas. In territorial terms, only 1.3% of Ireland is defined as Predominantly Urban (PU) in the Eurostat definition compared to an EU average of 10%. Cohesion policy stresses the role of urban investment, in support of territorial cohesion objectives, through integrated urban actions. Urban areas are recognised as engines for economic growth and as hubs for knowledge, creativity and innovation. On the other hand, particular challenges such as congestion, degradation and concentrations of disadvantage are prevalent in urban areas. Under the Investment for Growth and Jobs goal, a minimum of 5% of ERDF resources must be allocated to integrated actions for sustainable urban development (SUD). In Ireland the principal strategic framework for urban policy is the National Spatial Strategy (NSS) 2002-2020, which provides a 20 year planning framework and a hierarchy of designated growth centres. The key objectives of the NSS are set out hereunder. These align very well with the overall goals for the European Structural and Investment Funds: Sustain economic and employment growth; Improve competitiveness; Xxxxxx balanced regional development; Improve quality of life for all; and Maintain and enhance quality and diversity of natural environment and cultural heritage.
Urban Areas. (summary) Analysis of urban areas of Jugla (the current condition and the possible future improvements) in total found 7 problems (with 19 sub problems), 14 development activities, which should be carried out by implementing 2 organizational and 2 financial activities, and 9 recommendations for the development activities were given. The activities listed below contribute in reaching the following aims of the “Riga long-term development strategy till the year 2025”: Priority Aim PA4 ‚Life in a city with qualitative neighborhoods‟; Strategical Aim SA10 „Green city with good environmental quality‟. Problems
Urban Areas. “Urban areas” of interest are the geographic area for the urbanized area6 or urban cluster7 as delineated by the Bureau of the Census from the 2000 Census for the places listed below. Coverage for an area larger than that delineated by the Bureau of the Census may be proposed by the applicant. Albany, NY Albuquerque, NM Allentown – Bethlehem, PA Amarillo, TX Anchorage, AK Atlanta, GA Augusta, GA Augusta, ME Austin, TX Bakersfield. CA Baltimore – Annapolis, MD Barre – Montpelier, VT Baton Rouge, LA Birmingham, AL Bismarck, ND Boise, ID Boston, MA Bridgeport – Stamford, CT Buffalo, NY Cape Coral, FL Carson City, NV El Paso, TX Flint, MI Frankfort, KY Fresno, CA Ft. Xxxxx, IN Grand Rapids, MI Greensboro – Winston Salem, NC Harrisburg, PA Hartford, CT Helena, MT Honolulu, HI Houston, TX Huntsville, AL Indianapolis, IN Jackson, MS Jacksonville, FL Jefferson City, MO Juneau, AK Kansas City, MO-KS Knoxville, TN Lancaster, PA New Haven, CT New Orleans – Metairie, LA New York – Newark, NY Norfolk – Chesapeake – Newport News – Virginia Beach, VA Oklahoma City, OK Olympia, WA Omaha, NE Orlando, FL Oxnard, CA Palm Bay – Melbourne, FL Pensacola, FL Philadelphia, PA Phoenix – Glendale – Mesa, AZ Pierre, SD Pittsburgh, PA Portland, OR Poughkeepsie – Newburgh, NY Providence, RI Raleigh – Durham, NC Reno, NV Charleston – North Charleston, Lansing, MI Richmond, VA SC Charleston, WV Charlotte, NC Chattanooga, TN Cheyenne, WY Chicago, IL Cincinnati, OH Cleveland – Akron, OH Colorado Springs, CO Columbia, SC Columbus, GA Columbus, OH Concord, NH Las Vegas, NV Lexington, KY Lincoln, NE Little Rock, AR Los Angeles – Glendale – Long Beach – Huntington Beach – Santa Xxx – Anaheim, CA Louisville, KY Lubbock, TX Madison, WI McAllen, TX Memphis, TN Miami – Ft. Lauderdale, FL Riverside – San Bernardino, CA Rochester, NY Sacramento, CA Salem, OR Salt Lake City – Ogden, UT San Antonio, TX San Diego, CA San Francisco – Oakland – San Xxxx – Fremont, CA San Xxxx, PR Santa Fe, NM Sarasota – Bradenton, FL Savannah, GA 6 The Bureau of the Census defines an urbanized area as consisting of a central place(s) and adjacent territory with a general population density of at least 1,000 people per square mile of land area that together have a minimum residential population of at least 50,000 people.
Urban Areas. 1:2000, 1:2500, 1: 4800, 1:5000, or 1:10000 metric / Rural Areas – 1: 12,500 metric (1: 50,000 and written details where map scale is not available.
Urban Areas. Changes in land use patterns in urban areas potentially include the creation of extensive impermeable areas, which have potential implications for the concentration of run-off. Thus the following data sets have been examined: - IPGS data: airport / aerodrome, industrial or commercial areas, urban fabric - CLC data: discontinuous urban fabric, sport and leisure facilities - CRIGE data: continuous, discontinuous and diffuse urban fabric, industrial and commercial units, airports All of the data sets show an increase in urban areas. The IPGS data demonstrates an increase in the urban areas of two thirds during the period 1974 to 2004. This seems not to correlate well with the limited increase in the population (see Section 5.1.1), but might be due in large part to the increase in tourism activities (Figure 16). The CLC data indicates that urban areas have more than doubled between 1990 and 2006, from 272 ha to 596ha (Figure 17), while the CRIGE data suggests a stable situation at 1039 ha for the period 1999 to 2006 (Figure 18). Legend Unchanged urban area Desurbanized area Urbanized area
Urban Areas. Figure 1: 30 Urban areas considered in Esperantia, each with a circle whose radius is proportional to population size1. Esperantia encompasses 30 urban areas: two main urban areas with 4 and 2 million inhabitants each, and 28 minor urban areas between 2 and 984 thousand inhabitants. Figure 1 shows with purple crosses the points associated to the urban areas, while magenta circles centred in the pur- ple crosses have a radius which is proportional to the population size of each urban area. The next table summarises the relative vertical and horizontal position of the urban areas in km with respect to the upper left corner and the population of the urban areas. 1 The underlying image is fiction and it has no meaning. It has been added just to give a more understandable view with respect to white background. Table 1: Urban areas ID Ordinate (km) Abscissa (km) Population UA1 30,00 70,00 4000000 UA2 70,00 30,00 2000000 UA3 50,38 64,68 930040 UA4 30,77 13,87 399019 UA5 47,55 36,24 47401 UA6 78,81 78,03 342373 UA7 66,85 13,35 735966 UA8 2,15 55,98 794682 UA9 30,08 93,94 544905 UA10 98,09 28,66 686223 UA11 80,08 89,61 893632 UA12 59,75 88,40 54791 UA13 94,37 54,91 303661 UA14 72,83 57,67 2191 UA15 2,58 44,65 195476 UA16 64,63 52,12 720165 UA17 37,23 93,71 721753 UA18 82,95 84,90 877799 UA19 37,25 59,31 582432 UA20 87,25 93,35 70684 UA21 66,84 20,67 922744 UA22 65,38 7,20 800372 UA23 40,67 66,69 285946 UA24 93,37 81,09 543663 UA25 48,45 75,67 984776 UA26 41,70 97,17 715678 UA27 98,79 86,41 838969 UA28 38,88 45,47 433260 UA29 24,66 78,44 470624 UA30 55,82 59,88 560713
Urban Areas. 2.2.4.1.1 Dependencies on other urban areas We show next the degradation profile obtained when the links representing the local roads and highways connecting the urban areas are completely unusable, e.g., due to a natural event or to intense traffic. Table 20: Degradation profiles for the urban areas with respect to unavailability of local roads and highways. ID Time thalf for 50% operativeness (hours) Slope k Final operative level σ A,B,min UA1 19,11 0,80 0,74 UA2 16,08 0,55 0,71 UA3 16,16 0,65 0,83 UA4 17,61 0,45 0,78 UA5 17,86 0,40 0,82 UA6 17,90 0,73 0,71 UA7 17,90 0,28 0,74 UA8 18,95 0,50 0,72 UA9 17,68 0,67 0,75 UA10 17,62 0,36 0,74 UA11 18,17 0,55 0,65 UA12 18,11 0,98 0,76 UA13 17,40 0,29 0,77 UA14 18,16 0,18 0,66 UA15 17,72 0,76 0,79 UA16 18,08 0,39 0,79 UA17 17,80 0,56 0,80 UA18 18,90 0,34 0,76 UA19 17,89 0,01 0,77 UA20 17,88 0,29 0,83 UA21 17,11 0,35 0,76 UA22 18,38 0,34 0,76 UA23 17,97 0,03 0,81 UA24 18,01 0,67 0,75 UA25 18,50 0,68 0,74 UA26 17,77 0,57 0,84 UA27 18,38 0,45 0,75 UA28 17,67 0,29 0,70 UA29 17,05 0,49 0,73 UA30 17,94 0,55 0,75 The next figure shows some of the degradation profiles (e.g., for UA1—UA6), assuming the complete inoperability (e.g., OLB(t)=0) of the element on which the urban areas are dependent. Dependency for of UA1 Dependency for of UA2 1 Dependency for of UA3 1 0.8 operativeness 0.6 0.6 0.6 0.4 0.4 operativeness operativeness 0.2 0 0 5 10 15 20 0 0 5 10 15 20 0 15 20 time (hours) time (hours) time (hours) Dependency for of UA4 Dependency for of UA5 1 Dependency for of UA6 1 0.8 operativeness 0.6 0.6 0.6 0.4 0.4 operativeness operativeness 0.2 0 0 5 10 15 20 time (hours) 0 time (hours) 0 time (hours) Figure 21: Degradation profiles for UA1—UA6 with respect to the dependencies on other urban areas.
Urban Areas. One of the assumptions made in 4.2.1 and 4.2.2 is the non-urban nature of the overflown area. If the same operations are envisaged in an urban environment, the requirements become substantially more stringent (standard scenarios S01 and S02, see section 3.4.2.3). First of all, the maximum allowed take-off mass drops to 4 kg, then the maximum distance from the pilot drops to 100 m. Keeping in consideration also the buffer area (30m for S01, 50m for S02) that often results in major limitations for urban environments, the recommendation for MOMIT is to plan the demonstrators out of urban areas.
Urban Areas. (development actions) In this chapter the activities to help solving the problems listed in chapter “Urban areas (conclusions of SWOT analyses)” are given. These activities also would contribute in reaching two aims of the “Riga long-term development strategy till the year 2025”: Priority Aim PA4 ‚Life in a city with qualitative neighbourhoods‟ and its tasks; Strategical Aim SA10 „Green city with good environmental quality‟ and its tasks. Activity A1.1 Provision of overnight parking places for multi- apartment building inhabitants [Responsible institutions - District administration of Riga City Council; Municipal company “Rīgas satiksme (Riga traffic)”; Traffic Department of Riga City Council]
