Hobart Printable Map, Tasmania, Australia, exact vector street map, V29.11, fully editable, Adobe Illustrator, G-View Level 17 (100 meters scale), full vector

Printable Map Hobart, Tasmania, Australia, exact vector street map, V29.11, fully editable, Adobe Illustrator, G-View Level 17 (100 meters scale), full vector, scalable, editable, text format of street names, 4 Mb ZIP.
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$ 26.00

Printable Map Hobart, Tasmania, Australia, exact vector street map, V29.11, fully editable, Adobe Illustrator, G-View Level 17 (100 meters scale), full vector, scalable, editable, text format of street names, 4 Mb ZIP.
All streets names, main objects. Map for publishing, design, printing, publications, arts, projects, presentations, for architects, designers and builders, business, logistics. The most exact and detailed map of the city.
Separated layers: streets and roads, color fills, objects, road labels, street arrows, names 1,2,3, scales. Royalty Free.

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Product Description

Printable Map Hobart, Tasmania, Australia, exact vector street map, V29.11, fully editable, Adobe Illustrator, G-View Level 17 (100 meters scale), full vector, scalable, editable, text format of street names, 4 Mb ZIP.
All streets names, main objects. Map for publishing, design, printing, publications, arts, projects, presentations, for architects, designers and builders, business, logistics. The most exact and detailed map of the city.
Separated layers: streets and roads, color fills, objects, road labels, street arrows, names 1,2,3, scales. Royalty Free.
DWG, DXF, CDR and other formats - by request, same price, please contact.

Free download vector map Australia, Adobe Illustrator, download now Free maps vector clipart >>>>>
Map for design, projects, presentation free to use as you like.
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Free download vector map Australia, Adobe Illustrator, download now Free maps vector clipart >>>>> Map for design, projects, presentation free to use as you like royalty free

Small guide: How to work with the vector map?

You can: Mass select objects by type and color - for example, the objects type "building" (they are usually dark gray) - and remove them from the map, if you do not need them in your print or design project. You can also easily change the thickness of lines (streets), just bulk selection the road by the line color.
The streets are separated by type, for example, type "residential road" are usually white with a gray stroke. Highway usually orange with a brown or dark gray stroke.
It is easy to change the font of inscriptions, all or each individually. Also, just can be make and any other manipulation of objects on the vector map in Adobe illustrator format.
Important: All the proportions on the map are true, that is, the relative sizes of the objects are true, because Map is based on an accurate GPS projection, and It transated into the (usual for all) the Mercator projection.
You can easily change the color, stroke and fill of any object on the map, zoom without loss of quality Image Verification.

Select object

select object on vector map

Bulk selection the same objects on the vector map

bulk selection the same objects on the vector map

See the bulk selected objects on the vector map

see the bulk selected objects on the vector map

Bulk delete buildungs from the vector map

Bulk delete buildungs from the vector map

Select residencial road (small street) on the vector map

Select residencial road (small street) on the vector map

Bulk selection the same lines (streets, roads) on the full map

Bulk selection the same lines on the full map

Create fat lines of the streets on the vector maps (bulk action) 1

Create fat lines of the streeta on the vector maps (bulk action) 2

Create fat lines of the streets on the vector maps (bulk action) 2

Create fat lines of the streeta on the vector maps (bulk action) 2

Create fat lines of the streets on the vector maps (bulk action) 3

Create fat lines of the streeta on the vector maps (bulk action) 3

You can easily change the color, stroke and fill of any object on the map, zoom without loss of quality Image Verification. 

Tips & Vector map News

Global Irrigated Area Mapping Data portal This is world’s first satellite sensor-based global irrigated area map (GIAM) and statistics using complex set of methods and approaches. The data used include monthly time-series images from Advanced Very High Resolution Radiometer (AVHRR) 10-km for 1997-1999, Systeme pour l’Observation de la Terra (SPOT)/VEGETATION (VGT) 1-km for 1999, Moderate Resolution Imaging Spectroradiometer (MODIS) 500-meter for 2001-2003, a suite of secondary datasets such as precipitation for 1961-2001 at 50 kilometer, digital elevation 1- km, and thermal skin temperature at 10-km for 1997-1999.
This Product has Three Main Modules:
Global Irrigated Area Mapping Data portal
http://www.iwmigiam.org/info/gmia/default.asp

Global Irrigated Area Mapping Statistics categorized into Global, Continent, National, River-Basin and India’s Sub-National level. http://www.iwmigiam.org/stats/

Global Map of Rain-fed Cropland Areas (GMRCS)
http://www.iwmigiam.org/info/gmrca/default.asp

You can access and download FREE DATA of all above products and many more at : http://www.iwmigiam.org/

INTRODUCTION: A Global irrigated area map has been produced for a nominal year of 1999 using multiple satellite sensor and secondary data. Multiple resolution time series data used in the study were: (a) AVHRR 4-band and NDVI 10-km monthly time series for 1981-1999, (b) SPOT vegetation NDVI 1-km monthly time series for 1999, and (c) East Anglia University Climate Research Unit Rainfall 50-km monthly time series for 1961-2000. Additional major global data sets used were (a) GTOPO-30 1-km elevation, (b) JERS SAR data for the rainforests during two seasons in 1996, and (c) University of Maryland Global Tree Cover 1-km data for 1992-93.

A number of new methods and techniques were developed. The study first segmented the world into climate and elevation zones and analyzed satellite images separately for these zones. The class identification and labeling process began with spectral matching technique (SMTs). Since time-series data are analogous to hyperspectral data, we adopted hyperspectral analysis techniques such as SMTs to identify, group, and label classes with similar time series characteristics. The time-series spectra of classes were also compared with the target ones obtained from ground truthed locations. The spectral correlation similarity was found to be the most useful spectral matching technique (SMT). Classes are then ?verified?, at 30-50 randomly chosen locations that are well distributed across the globe, by inspection of Google Earth images for which the resolution varies between sub-meter to 30-meter.

Multiple image interpretation techniques such as bispectral plots, space time spiral curves (ST-SCs), time-series plots of normalized difference vegetation index (NDVI), and a host of secondary data (e.g., national and global landuse and land cover data) were used, including ESRI 150-m Landsat Geocover mosaic of the world.. Broadly sourced ground truth data were used in identifying, labeling and refining classes. First: IWMI?s primary ground truth data set of nearly 2000 points that include: a) three missions conducted in 2004 and 2005 that cover the whole of India; b) extensive data from river basins with extensive irrigation areas such as the Ganges and Krishna in India, Ruhuna in Sri Lanka, Syr Darya in Central Asia and Limpopo in Southern Africa; and c) a past data catalogue from the Middle East and 14 Countries in West Africa. Second: data sourced from the Degree Confluence Project with about 4000 points that collates land use data for 1 by 1 degree tile over the globe. In addition nearly 11,000 ?zoom in views? of high or very high resolution Google earth points. Decision tree algorithms, NDVI time series plots, NDVI thresholds, principal component analysis, unsupervised clustering algorithms, and GIS spatial modeling using data such a agroecological zones, temperature, precipitation, evapotranspiration, and elevation were widely used to define and refine classes especially to resolve mixed classes.

Click here to access the COMPLETE Documentation.

Below Screen-grab shows portal’s easily navigable Statistics access interface:


The Main page of the Portal:

Source.

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Last Modified: March 9, 2017 @ 1:44 pm