OrbView-3 High Resolution Images of Pakistan for Free

OrbView-3 high resolution imagery of Pakistan is now available in public domain since January 9, 2012. The images in this catalogue have been acquired between 2003 to 2007 and include more than 2400 scenes with the resolution of 1 meter (pan) and 4 meters (multispectral) of different place in Pakistan. Map below shows coverage of the available images. One can access it via USGS’s EarthExplorer as well.Orbiew-3 Coverage Pakistan

Orbiew-3 Coverage Pakistan2

Download KML file of the Coverage:

 

An analysis of mapping potential from OrbView 3 Images is given below (extracted from GIM International)

Information Content of High-resolution Satellite Image

The information content of OrbView-3 and Ikonos imagery is compared, using the Zonguldak area in Turkey as test area. Although OrbView-3 images are qualitatively slightly inferior to Ikonos panchromatic scenes, they can be used for the generation of topographic maps at scale 1:10,000. However, they are not suited for 1:5,000 mapping, for which scale Ikonos images also show limitations.

In operation since 2004, OrbView-3 is one of the recent very high-resolution space sensors, offering images of 1m panchromatic and 4m multispectral Ground Sampling Distance (GSD). In mapping terms both geometric accur-acy and information content are important, but the required geometric accuracy can be reached without difficulty provided that images are not degraded by at-mosphere and sun-elevation effects. As a rule of thumb, the GSD should be at least 0.1mm of the map scale, corresponding to scale 1:10,000 for 1m GSD.

Visual Comparison
Examination of information content has to be done by visual inspection (Figure 1). OrbView-3 and Ikonos have approximately the same resolution, but comparison shows that edges are sharper in the Ikonos image and that whilst OrbView-3 shows cars only as blobs, structural elements are visible in Ikonos. The GSD of 0.62m offered by QuickBird enables identification of more detail. On the other hand, the 5m GSD of Spot 5 limits the use of these images to the creation of maps of smaller scale. Buildings are still visible but they cannot be mapped in detail, and sometimes back-gardens will be identified as streets. Many of these differences result from sensor configuration, radiometric resolution, recording conditions and terrain characteristics.

Sensor Configuration
OrbView-3 uses staggered CCD-lines; two CCD-lines are shifted by 0.5 pixels against each other so that the pixel size projected on the ground for nadir view is 2m and adjacent pixels overlap 50% in both directions (Figure 2). The effective GSD of 1m resulting from such over-sampled pixels differs from nominal GSD of 1m. OrbView-3 takes 2,500 double lines per second, but the satellite footprint speed is 7.1km/sec, which requires permanent change of view direction to slow down angular speed. The resulting slowdown factor is 1.4 (Figure 3). The effective GSD as determined by point-spread analysis of sharp edges does not show loss of resolution against the nominal GSD, but it can be manipulated by contrast enhancement.

Radiometric Resolution
OrbView-3, Ikonos and QuickBird have a radiometric resolution of 11bit, with which 2,048 grey valu-es can be represented. However, the grey values within one scene will not cover the whole range and a qualified change from 11bit to 8bit grey values does not lead to significant loss of information. Only in some crucial areas do differences appear between the original 11bit and the derived 8bit grey values. Figure 4 shows more details in the roof in the original 11bit image than in its 8bit counterpart. This may be important for automatic image matching, but for mapping purposes it is unimportant because in both cases the building can be sufficiently well identified in all required detail.

Recording Conditions
Haze, clouds and smoke may reduce contrast; enhancement is possible but the resulting image quality will not approach that of images taken under optimal conditions. Sun elevation and azimuth cause shadows that hinder identification of details (Figure 5). With a sun elevation angle of 63°, shadows in the OrbView-3 image are not so long as in the Ikonos image with a sun elevation angle of 41°. Shadows cause identification problems in scenes with narrow streets, high buildings and terrain inclination, as is the case in the north of the Zonguldak area, but sometimes shadows may support object identification. For example, a helicopter landing-pad might at first sight look like a roof, but missing shadow may indicate that it is on the same level as surrounding grassland.

Terrain Characteristics
Contrast is the dominant component of image interpretation, but identification of objects also depends on their characteristics. Planned areas, with larger, well-arranged buildings can be more easily mapped than unplanned areas with smaller and irregu-lar objects, especially when the latter occur in hilly terrain (Figure 6). Identification of objects in planned areas does not result in significant differences between OrbView-3 and Ikonos panchromatic images, while in unplanned areas the better image quality of Ikonos resulted in a larger number of identified objects. Not every building has a rectangular shape and, particularly in hilly terrain, walls may not be parallel. Figure 7 shows a building of irregular shape (a), a rectangular building (c) and a low building throwing little shadow (b). The latter has not been identified during the mapping exercise, mainly because of missing shadow. OrbView-3 cannot take panchromatic and colour images simultaneously as do Ikonos and QuickBird, so no direct pan-sharpening was possible. Mapping with pan-sharpened Ikonos and QuickBird images simplified object identification, but this does not mean that more objects can be identified; the number was insignificant.

Results
Table 1 summarises the detection (DET) and recognition (REC) possibilities of features and objects in OrbView-3 and Ikonos imagery. Figure 8 shows maps created from panchromatic OrbView-3 and Ikonos images. All buildings and nearly all roads have been recognised in the Ikonos image; a few roads in shadowy areas have not been recognised. In the OrbView-3 mapping 93% of the buildings and 96% of the roads mapped with Ikonos are seen, while only 33% of the pavements could be identified. These results demonstrate that OrbView-3 images are well suited for creation of 1:10,000 topographic maps.

Biography of the Author(s)
Huseyin Topan is a PhD candidate for geodesy and photogrammetry in the Ýstanbul Technical University, Turkey. His main research direction is the infor-mation content and geometry of high-resolution space imagery.

Gürcan Büyüksalih is professor in Photogrammetry at Zonguldak Karaelmas University, Turkey. He received his PhD from the University of Glasgow, UK, Department of Geography and Topographic Science. His research direction is the full range of photogrammetry, especially application of space imagery.

Karsten Jacobsen received a PhD in Photogrammetry from Leibniz University, Hanover, Germany. He is academic director of the Institute of Photogrammetry and Geo-information at the same university. His main research area is numerical photogrammetry, especially the use of space imagery.

Union Council Boundaries of Rawalpindi City and District

This GIS datasets contains polygonal boundaries for 170 union councils of Rawalpindi urban area as well as Rawalpindi District. This geo-dataset is more reliable for urban area and seems to be less accurate for rural towns.

Rawalpindi UCs Pakistan GIS

.::Click HERE to request for this data set::.

Vector Datasets (ESRI Shapefiles)

Currently following vector datasets are available in ESRI Shape files Format at this blog:

Administrative Boundaries Maps:

  1. National and Provincial Boundaries of Pakistan (Admin Level 0 and 1)
  2. District Boundaries of Pakistan (Admin Level 2)
  3. Tehsil Boundaries of Pakistan (Admin Level 3)
  4. Union Council Map (Admin level 4) of District Barkhan – Balochistan
  5. Union Council Map (Admin level 4) of District Jaffarabad – Balochistan

  6. Union Council Map (Admin level 4) of District Killa Saifullah – Balochistan

  7. Union Council Map (Admin level 4) of District Kohlu – Balochistan

  8. Union Council Map (Admin level 4) of District Loralai – Balochistan

  9. Union Council Map (Admin level 4) of District Nasirabad – Balochistan

  10. Union Council Map (Admin level 4) of District Sibi – Balochistan

Khyber Pakhtunkhwa

  1. Union Council Map (Admin level 4) of District Abbottabad – KPK

  2. Union Council Map (Admin level 4) of District Bannu – KPK

  3. Union Council Map (Admin level 4) of District Batagram – KPK

  4. Union Council Map (Admin level 4) of District Buner – KPK

  5. Union Council Map (Admin level 4) of District Charsadda – KPK

  6. Union Council Map (Admin level 4) of District Chitral – KPK

  7. Union Council Map (Admin level 4) of District Dera Ismail Khan – KPK

  8. Union Council Map (Admin level 4) of District Hangu – KPK

  9. Union Council Map (Admin level 4) of District Haripur – KPK

  10. Union Council Map (Admin level 4) of District Karak – KPK

  11. Union Council Map (Admin level 4) of District Kohat – KPK

  12. Union Council Map (Admin level 4) of District Kohistan – KPK

  13. Union Council Map (Admin level 4) of District Lakki Marwat – KPK

  14. Union Council Map (Admin level 4) of District Lower Dir – KPK

  15. Union Council Map (Admin level 4) of District Malakand P.a. – KPK

  16. Union Council Map (Admin level 4) of District Mansehra – KPK

  17. Union Council Map (Admin level 4) of District Mardan – KPK

  18. Union Council Map (Admin level 4) of District Nowshera – KPK

  19. Union Council Map (Admin level 4) of District Peshawar – KPK

  20. Union Council Map (Admin level 4) of District Shangla – KPK

  21. Union Council Map (Admin level 4) of District Swabi – KPK

  22. Union Council Map (Admin level 4) of District Swat – KPK

  23. Union Council Map (Admin level 4) of District Tank – KPK

  24. Union Council Map (Admin level 4) of District Upper Dir – KPK

Punjab

  1. Union Council Map (Admin level 4) of District Bahawalpur – Punjab

  2. Union Council Map (Admin level 4) of District Bhakkar – Punjab

  3. Union Council Map (Admin level 4) of District Dera Ghazi Khan – Punjab

  4. Union Council Map (Admin level 4) of District Jhang – Punjab

  5. Union Council Map (Admin level 4) of District Khushab – Punjab

  6. Union Council Map (Admin level 4) of District Layyah – Punjab

  7. Union Council Map (Admin level 4) of District Mianwali – Punjab

  8. Union Council Map (Admin level 4) of District Multan – Punjab

  9. Union Council Map (Admin level 4) of District Muzaffargarh – Punjab

  10. Union Council Map (Admin level 4) of District Rahim Yar Khan – Punjab

  11. Union Council Map (Admin level 4) of District Rajanpur – Punjab

Sindh

  1. Union Council Map (Admin level 4) of District Dadu – Sindh

  2. Union Council Map (Admin level 4) of District Ghotki – Sindh

  3. Union Council Map (Admin level 4) of District Hyderabad – Sindh

  4. Union Council Map (Admin level 4) of District Jacobabad – Sindh

  5. Union Council Map (Admin level 4) of District Jamshoro – Sindh

  6. Union Council Map (Admin level 4) of District Kashmore – Sindh

  7. Union Council Map (Admin level 4) of District Khairpur – Sindh

  8. Union Council Map (Admin level 4) of District Larkana – Sindh

  9. Union Council Map (Admin level 4) of District Matiari – Sindh

  10. Union Council Map (Admin level 4) of District Naushahro Feroze – Sindh

  11. Union Council Map (Admin level 4) of District Qambar Shahdadkot – Sindh

  12. Union Council Map (Admin level 4) of District Shaheed Benazirabad – Sindh

  13. Union Council Map (Admin level 4) of District Shikarpur – Sindh

  14. Union Council Map (Admin level 4) of District Sukkur – Sindh

  15. Union Council Map (Admin level 4) of District Tando Muhammad Khan – Sindh

  16. Union Council Map (Admin level 4) of District Thatta – Sindh

Urban Union Councils:

Urban Area Maps:

  1. Haripur GIS Map (ESRI Format)
  2. Peshawar GIS Map (ESRI Format)
  3. Mianwali Tehsil GIS Map (ESRI Format)
  4. Quetta GIS Map (ESRI Format)
  5. Gilgit GIS Map (ESRI Format)
  6. Nankana Sahib GIS Map (ESRI Format)
  7. Jaranwala GIS Map (ESRI Format)
  8. Pindi Bhattian GIS Map  (ESRI Format)
  9. Khangah Dogran GIS Map (ESRI Format)
  10. Chiniot GIS Map (ESRI Format)
  11. Chakwal GIS Map (ESRI Format)
  12. Attock GIS based Land use Map (ESRI Format)
  13. Faisalabad GIS based Land use Map (ESRI Format)
  14. Village Kesar Garh (District Kasur) GIS Based Landuse Map (ESRI Format)

Union Council Boundaries of Faisalabad City

This GIS map consists of polygonal boundaries for 118 union councils of Faisalabad urban area. It has been developed and generously shared by Nasar min Allah Bhalli (M.Phil) from  Department of geography, GC University Faisalabad.

Union council boundaries of faisalabad

                                   .::Click HERE to request for this data set::.

Town wise Union Council Boundaries of Lahore

This GIS map consists of polygonal boundaries for 151 union councils of Lahore urban area divided in 11 Towns.

Union council boundaries of lahore

Special thank to our very Valued Contributor for Lahore.

                                   .::Click HERE to request for this data set::.

National Geospatial Services Pakistan

 

 

Company Name

National Geospatial Services Pakistan

Address Islamabad
Head Office in City Islamabad
Branch Offices in Lahore, Faisalabad, Karachi and Peshawar
Website http://gisconsultant.com.pk/
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Contact Email ahsan@gisconsultant.com.pk
Phone +923336704571
Area of Specialization
  • GIS
  • GIS Data
  • CAD / Digitization
  • Remote Sensing
  • Software Development
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