remote sensing - sensors & platforms

8/11/2019 Remote Sensing - Sensors & Platforms

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GIANNI GORGOGLIONE 1

URBAN MAPPINGHigh-resolution satellite IKONOS & Aerial photography

Gianni Gorgoglione

Abstract

This study strives to understand how satellite imagery with high-resolution is applied to urbanplanning and if there are relevant differences compared to the aerial photography. I found most of theinformation on peer-review articles from international journals.

Introduction

Today there is a need of more accurate information of demographic development in urban area due to

a rapid population increasing. Modern technology in remote sensing helps urban manager planners totake decisions faster and more accurately in order to observe spatial distribution of land uses, housecharacteristics and demographic growth. Besides these data can be used into infrastructure planning,damage evaluation in natural disasters, controlling of human deforestation and more generallymonitoring human activities.

Aim

How does remote sensing use high-resolution satellite systems for urban applications?

Can high-resolution satellite imagery replace aerial photography?

Methods

To succeed in accomplishing this study, I looked for relevant articles from international journals. I putfocus on high-resolution satellites such as Ikonos and aerial photography articles.

Theory

In urban application, objects are classified as impervious surfaces. According to Bauer andSlonecker these ones are defined as any materials that water cannot infiltrate and is primarilyassociated with human activities and habitation through construction of transportation andbuildings(Slonecker 2001, Bauer 2004).

Bright buildings roofs have a high reflectance on the Ikonos composite image and roads or dark roofshave a low reflectance because they absorb major part of visible light, near IR and shortwave IR. Sincethere are problems to distinguish between dark water surfaces from buildings-cast shadows (See figure2) there are many classification methods. This is why in many cases NIR and NDVI index are used to

classify different shadowed categories. Some of these classification and extraction methods forimpervious surfaces are: high-albedo and low-albedo images extraction, per-pixel supervisedclassification, normalization of vegetation cover with impervious faces and decision tree classifier

(DTC).1

In the following lines I try to describe moreabout the classification method of DTC (See

1Lu, Dengsheng and Weng, Qihao(2009)'Extraction of urban impervious surfaces from an IKONOS image', International Journal of RemoteSensing,30:5,1297 1311

Figure 1 Figure 2 False composite image from Ikonos with bands 4, 3 and 2(R, G, B) showing the complexity of impervious objects detection.

(Lu,Dengsheng and Weng, Qihao,2009))


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figure 1). In the case of extraction of impervious surfaces from an Ikonos image it is possible to createtree classifiers for three levels of reflectance. NDVI is useful to distinguish vegetation class from

impervious surfaces. Then visible band permit to classify medium and high spectral reflectance ofimpervious surfaces. On the other hand low spectral reflectance is elaborated with NIR. At the end,this method cannot separate distinctly water and shadows from the rest of the other covers. Thus, in

support of DTC method is keen to apply another approach like for example using unsupervisedISODATA classification that separates into many signatures those pixels that belong to water and

shadows.1

Figure 2. Example of procedure for extraction of impervious surfaces using the combination of a decision tree classifier and an

unsupervised ISODATA classifier (Lu, Dengsheng and Weng, Qihao(2009)'Extraction of urban impervious surfaces from an IKONOS

image',International Journal of Remote Sensing,30:5,1297 1311)

Different researches about IKONOS images show that high-resolution images can be used for maps of1:10000 by extracting roads, water surfaces, railways and buildings. Despite this it was not possible to

detect smaller objects like fences or walls.2

This is one reason that at time satellite imagery is not enough to accomplish a specific mission.

Therefore it is necessary the use of photography from aerial airborne that has many advantagescompared with high-resolution imagery (See table 1 & 2).

Today, in urban applications, the use of aerial photography and satellite imagery with 3th generationsatellites like Ikonos 2 are complementary.

3

Table 1 HIGH-RESOLUTION SATELLITES

Advantages DisadvantagesLarge coverage area, short revising time Lower resolution than aerial photography. Maximum spatial

resolution is circa 50 cm per pixel.The high-resolution remote sensing satelliteprovides better opportunities for slanting observation thanperpendicular observation

4

One critical step is to extract dark impervious surface areasand shadowed impervious surfaces, whichare often confused with water and shadows cast by treecrowns.

5

2 Dejan Grigillo, Mojca Kosmatin Fras & Duan Petrovi(2012) Automated building extraction from IKONOS images in suburban areas,

International Journal of Remote Sensing, 33:16, 5149-5170, DOI: 10.1080/01431161.2012.659356

3 D. Maktav Corresponding author , F. S. Erbek & C. Jrgens (2005), Remote sensing of urban areas, International Journal of Remote

Sensing, 26:4, 655-659, DOI: 10.1080/01431160512331316469

4Sotaro Tanaka &Toshiro Sugimura,(2010) A new frontier of remote sensing from IKONOS images, International Journal of Remote

Sensing,Volume 22,Issue 1,2001, DOI:10.1080/014311601750038802

5 Dengsheng Lu & Qihao Weng (2009) Extraction of urban impervious surfaces from an IKONOS image, International Journal of Remote

Sensing, 30:5, 1297-1311, DOI: 10.1080/01431160802508985
http://www.tandfonline.com/action/doSearch?Contrib=Tanaka%2C+Shttp://www.tandfonline.com/action/doSearch?Contrib=Sugimura%2C+Thttp://www.tandfonline.com/loi/tres20?open=22#vol_22http://www.tandfonline.com/toc/tres20/22/1http://www.tandfonline.com/toc/tres20/22/1http://www.tandfonline.com/loi/tres20?open=22#vol_22http://www.tandfonline.com/action/doSearch?Contrib=Sugimura%2C+Thttp://www.tandfonline.com/action/doSearch?Contrib=Tanaka%2C+S


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Speed. Location of satellite can move faster than aerialimage. Satellite can take a larger amount of data that meansless time.

The tall buildings-cast shadows and tree crowns in the highspatial resolution imagery represent a problem for extractingimpervious surfaces. They look like water or wet lands.

Weather condition can determinate the result of satelliteimagery

Difficult to change cameras onboard

higher cost

Table 2 AERIAL PHOTOGRAPHY

Advantages DisadvantagesMaximum spatial resolution up to 2.5 cm per pixel Need of bigger space storage

Weather condition Airplanes can take photographs whereSatellite sensors cannot work properly

The aircraft body is tilted in order to take slanting picturesbecause position can vary

Older archive of imagery collection from the past. While newsatellite observations started in 1972

Time consuming process. However, now modern camerascan capture strip of data and not only a frame.

Easy maintenance for technical service

Installation of multi spectral cameras that worksimultaneously

Lower cost

ResultsThe mapping of urban area is a complex subject that requires different methods to reach an acceptableresult representing the reality with right accuracy. One of most difficult problem is to separate water

and shadows-cast from other categories. According to the research conducted by Lu, Dengsheng,Weng and Qihao the most accurate method to extract impervious surfaces is the combination of non-parametric decision tree classification and unsupervised ISODATA classifier. Nevertheless, there arelimits for high-resolution imagery that can be supplied by the complementary use of aerialphotography. Higher resolution imagery combined with the flexibility of aerial photography is still an

advantage for remote sensing and urban mapping despite the higher cost. Thus, when it is necessaryaerial photography comes into account in the image processing.

Discussion

In conclusion, today the increasing technology of digital cameras make more complex decision overwhich device is more suitable for imagery production depending on the circumstances. High-resolution satellite imagery offers faster solutions in one world where rapid changes need fasteranalysis. But it is still not excellent according to above-mentioned reasons which leads to a forced wayto come to a compromise between aerial photography and satellite imagery.

References

Dengsheng Lu & Qihao Weng (2009) Extraction of urban impervious surfaces from an IKONOSimage, International Journal of Remote Sensing, 30:5, 1297-1311, DOI: 10.1080/01431160802508985

Dejan Grigillo, Mojca Kosmatin Fras & Duan Petrovi (2012), Automatedbuilding extraction fromIKONOS images in suburban areas, International Journal of Remote Sensing, 33:16, 5149-5170, DOI:10.1080/01431161.2012.659356

D. Maktav Corresponding author , F. S. Erbek & C. Jrgens (2005),Remote sensing of urban areas,International Journal of Remote Sensing, 26:4, 655-659, DOI: 10.1080/01431160512331316469


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Sotaro Tanaka &Toshiro Sugimura,(2010) A new frontier of remote sensing from IKONOS images,International Journal of Remote Sensing, Volume 22,Issue 1, 2001, DOI:

10.1080/014311601750038802
http://www.tandfonline.com/action/doSearch?Contrib=Tanaka%2C+Shttp://www.tandfonline.com/action/doSearch?Contrib=Sugimura%2C+Thttp://www.tandfonline.com/loi/tres20?open=22#vol_22http://www.tandfonline.com/toc/tres20/22/1http://www.tandfonline.com/toc/tres20/22/1http://www.tandfonline.com/loi/tres20?open=22#vol_22http://www.tandfonline.com/action/doSearch?Contrib=Sugimura%2C+Thttp://www.tandfonline.com/action/doSearch?Contrib=Tanaka%2C+S

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