{'fraction_non_alphanumeric': 0.023299426038529296, 'fraction_numerical': 0.006705688469625505, 'mean_word_length': 4.965423728813559, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 4, 'lorem ipsum': 0, 'www.': 3, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Toward City Web Mapping in developing countries using satellite and stereo aerial imagery: A Case Study

Maps are graphic demonstrations of geographic information and a worldwide means of navigation. Digital maps, which are easily accessed via smartphones, are important in daily life. However, producing or updating maps and providing web data servers in developing countries are challenging due to limitations in resources. This research focuses on using free online ortho satellite imagery for producing digital maps and comparing it with those created from stereo aerial imagery via photogrammetry. The software ArcMap is used to produce maps from satellite imagery. The stereo imagery is processed using the photogrammetric solution Summit Evolution by ground control points collected from the site. Then, the spatial features are extracted from stereo aerial imagery. Subsequently, the attributes of both data sets are added to the objects, and the digital maps are uploaded to a web ArcGIS server by using an ArcGIS Online account. A case study is conducted on the College of Engineering campus at Salahaddin University-Erbil and its surroundings, which comprise different buildings and facilities. The result shows that the maps produced from stereo aerial imagery are more precise and accurate than those from satellite imagery because the features are photogrammetrically extracted with high resolution and stereo imagery.


Introduction
Maps have evolved with technological developments-beginning as mere cave drawings and progressing as digital maps. This advancement has introduced a collection of spatial data, geographic information systems and interactive mapping technologies through mobile devices and personal computers. Accordingly, methods for visualising spatial information have been improved. Thus, paper maps have become less popular than web maps, which are available via the World Wide Web. Web maps allow geospatial data to be easily delivered via web browsers.
Online maps are an important tool for end users for sharing maps for different tasks. Pignone, Cogliano [1] presented the use of online maps for seismic locations and classifications. Online maps have also been used to strengthen a forest database by testing the possibility of implementing data provided by communities through a web application [2]. Using GIS and online mapping has become popular among people. Such processes have undergone intense modifications through educational background, techniques used in operation and the implementation settings of GIS during the last decades [3]. BCEE4 IOP Conf. Series: Materials Science and Engineering 737 (2020) 012212 IOP Publishing doi: 10.1088/1757-899X/737/1/012212 2 Various studies have been conducted to improve the implementation and visibility of the GIS platform. Poplin, Guan [3] investigated the difficulties faced by different GIS users. You et al. [4] conducted a study to increase the feasibility of web maps for users. Visibility is enhanced by the inclusion of virtual tours or Virtual Reality Modelling Language (VRML) into maps, which in turn increases the realistic sensibility of the feature [5]. Web map commercial organisations, such as Google, Yahoo, Esri, Microsoft (Bing) and TomTom, have become popular with common accessibility to the internet. Such software can be used in navigation as standalone tools without accessing feature data. OpenStreetMap is a non-profit software that can help users create and edit maps with an open-content license, and access the geodata for free [6].
Individuals use online interactive mapping platforms, such as Google Maps. Geographical information via online maps is commonly used by people to access destinations through navigation systems. People provide data to open-source platforms, such as OpenStreetMap [3]. The use of different maps, such as Google Maps, has become popular and familiar [7]. However, users need to produce maps that contain specific data, which is challenging to accomplish for developing countries, which have limited resources.
In this research, online maps are produced using satellite imagery supported by Esri and stereo aerial imagery. The pipeline is initiated by digitising maps from high-resolution satellite imagery and comparing them with those produced from stereo aerial imagery. The manner of uploading the digital maps online is subsequently discussed.

Study area
An area in the north of Iraq is selected for this research, as shown in Figure. 1. This area is located in the College of Engineering campus at Salahaddin University-Erbil. The selected area has different types of buildings that vary in elevation, including public, accommodation and residential ones. The roads that connect the facilities together are extracted in addition to the buildings. The size of the area is 1300 m × 700 m.

Methodology
The map production procedure is explained in this section. This process is divided into two parts on the basis of the type of implemented data sets.

3.1.1.
Satellite imagery datasets. Satellite imagery is a remote sensing technique and considered a significant tool for providing worldwide optical imagery data that can be used in mapping even at large scales. The satellite imagery used in this research is from the Esri database, which can be downloaded for free and comes with the software. For this purpose, an account is created by Esri for logging into the system and browsing the available data. The Esri database contains many images that can be downloaded into ArcGIS. World Imagery is selected for this study, as shown in Figure 2.
The properties of the imagery are described with the data sets. World Imagery demonstrates high resolution imagery and reaches less than 1 m in certain areas in the world. As shown in Figure 3, the images cover most of the areas of the world. Thus, this imagery can be downloaded and implemented within Esri.
The imagery that used in the study area is from WorldView-2 and has a very high resolution of 0.5 m (image sources: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, Swisstopo and GIS User Community).  3.1.2. Mapping process. The images were loaded into ArcMap from ArcGIS' online database for mapping purposes. Projection UTM-Zone 38N was selected and assigned to the database because it is a commonly used coordinate system in the country.
ArcMap was utilised to produce maps. The features were directly digitised and saved as shapefiles on the basis of the assigned UTM-Zone 38N projection system. The roofs were selected for the digitisation of the building boundaries. Consequently, the accuracy of the buildings was affected because the satellite imagery was regular-orthophoto and not true-orthophoto. Specifically, the buildings appeared to be leaning due to geometric distortion. The relief in the buildings is regarded as the main source of error in the extraction from the regular-orthophoto.
Frame and pushbroom (satellite) imagery have relief displacement, thereby causing buildings to lean toward imagery edges, as shown in Figure 4. The frame imagery presents a central perspective. Thus, the distortion is radially distributed. The geometric distortion is minimal near the nadir point and develops as the distance from the nadir point increases, as shown in Figure 4 (a). In the satellite imagery, the geometry exhibits a linear perspective. The off-nadir satellite imagery is effective owing to its ability to rapidly capture images. However, this geometry is unused in the urban area due to the high geometric distortion in the buildings because of the relief [8]. Thus, the offnadir imagery is usually avoided during image acquisition in satellite imagery that is used for object extraction. Accordingly, the buildings appear to be leaning only across the track. Along the track, buildings exhibit minimum geometric distortion, as shown in Figure 4 As shown in Figure 5, the building rooftop demonstrates an offset with the corresponding building footprint due to the geometric distortion effect inherited in the imagery. This effect is the main challenge in extracting the building from remote sensing imagery.

Mapping using stereo aerial imagery.
Aerial imagery was implemented to show the difference between the two maps in addition to using the satellite imagery for mapping.

Stereo aerial imagery.
The aerial imagery is considered to be stereo and exhibits a resolution of 10 cm. The images were captured with an Ultra-Cam-Xp camera with a focal length of 100.5 mm. Two stereo pairs were used in this research for the processing of the stereo aerial images. Eight ground control points were acquired in the area through differential GPS Leica-1200. The points are referenced to the horizontal projection UTM-Zone 38N and height to the ellipsoid WGS-84. The GCPs are used in the photogrammetric absolute orientation process, which needs to register the model generated in the relative orientation process to the ground. Prior to this operation, interior orientation, which consists of restoring the camera geometry, was conducted using a camera calibration report that accompanied with the images.

3.2.2.
Mapping from aerial imagery. After the images are processed and the aerial triangulation is completed, the user can obtain any measurement from the image by hovering the stereo mouse over any point of interest. The features are extracted using manual stereo compilation methods by hovering the stereo mouse in the left and right imagery to the edge of the building and following the boundary that exhibits the same elevation. The cursor can be hovered over the desired elevation using a stereo digitiser. Then, building extraction can be initiated using a photogrammetric workstation. The user can obtain the spatial vector of the visible features through a digital photogrammetric workstation. Accordingly, an accurate planimetric location can be obtained. Despite improvements in computer vision methods for automatically extracting features from imagery, manual data compilation is still used to accurately collect features from imagery depending on human vision and object recognition [9]. For this process, the software Summit Evolution is used; this tool can export the result as an SHP or CAD file. Thus, the data can be easily transferred to the GIS platform using ArcGIS, as shown in Figure 6. The images that are used in the stereo aerial imagery have a resolution of 10 cm, which is higher than those of satellites that give improved building discrimination. In photogrammetry, the accuracy of the measured data is increased using a high image resolution. Building identification is also improved. The geometric distortion caused by relief displacement is eliminated using stereo imagery. Thus, the building footprint can be accurately extracted because the left and right images are integrated in the photogrammetric workstation during feature extraction. As shown in Figure 7, an apparent variance exists between the extracted building boundary (red vector) and the building boundary in the left or right imagery.

Publishing maps online
After the spatial data are collected and the maps produced, the next stage is disseminating them for people to view and use.
Online sharing and viewing of maps from satellite imagery, stereo imagery or any other source have become significant tools for easy access to the maps without installing any software on computers. Publishing maps online is considered a revolutionary technology and an anticipated mechanism in the field of information processing.
The process of making maps available online is conducted through a web service, which connects information that the user can access through the internet. Using the web service to publish maps online has led to making the maps more efficient in terms of financing, required human resources and time cost, thereby enabling maps to be easily shared. Geospatial data can be interactively and dynamically distributed with lower cost than for printed maps through the internet; furthermore, it does not require the installation of complex software on computers [10].
The general framework of the architectural system platform is divided into two, namely, client and server, as shown in Figure 8. As illustrated in the diagram, the web server includes the GIS software and the server-side database. Different platforms that can be used for map browsing are available for Web-GIS. These platforms require no expert knowledge or infrastructure about the system and server from the user. The online map helps to easily share the published data for the user. Different browsers are available, such as Mangomap (https://mangomap.com/), QGIS Cloud (https://qgiscloud.com/) and ArcGIS Online (http://www.arcgis.com), of which the last one is the most popular [1].
ArcGIS Online, which can be accessed via www.arcgis.com, is used to publish the maps. Prior to map uploading, the attributes are added to the extracted objects in ArcMap. Different attributes, such as building name, are assigned for each building, and are used to navigate its main gate. Each building is assigned to individual layers to control its viewing and then uploaded to the www.arcgis.com through an online account. After the map is uploaded into the ARCGIS server, it can be shared through a given link. For the aerial stereo map, the link for the digital map is https://arcg.is/0aufPv, which is generated automatically by ARCGIS server. In addition to the attributes, the feature can be gauged on the map by using the measuring tools provided in ArcGIS Online, as shown in Figure 9.  The produced map can be embedded into an HTML personal commercial website to incorporate it with the data from the organisation. This step is conducted to provide integrated information about the produced map. The ArcGIS Online viewer will generate an embed code that can be used to embed the map to an individual website, as shown in Figure 10. The website used in this research is https://sucampus.weebly.com/. This site is created for free under the domain weebly.com, which provides sufficient tools for embedding the map on the website.
In addition to measuring the maps, changing the background using different base maps for the map background (i.e. changing the satellite imagery to imagery with labels, streets background or others) is possible in ArcGIS. Accordingly, users can visualise the objects for enhanced understanding, as shown in Figure 11.

Accuracy analysis
In this section, the result of the digitised building from stereo aerial imagery is presented using a photogrammetric workstation and free satellite imagery from Esri. The analysis shows that variance and systematic shift exist between the results of the two data sets, as shown in Figure 12.
As shown in Figure 13, the building boundary obtained from satellite imagery loses certain details because the resolution is low. Moreover, precisely identifying the features is difficult compared with that for the aerial imagery, whose resolution is five times better than that of the former. The systematic error between the maps is due to the error of satellite imagery georeferencing (because it is globally used). The stereo aerial imagery is precise because the process uses accurate GCPs, as explained in Section 3.2.1. Figure 13. Superimposed boundary of digitised building from satellite imagery over building from stereo aerial imagery. The black boundary is produced from satellite imagery, and the green one is from stereo aerial imagery. The extracted features from stereo aerial imagery are accurate because they are based on stereo digitisation and are free from geometric distortion. In the photogrammetry, the error due to relief is eliminated. The features extracted from single satellite imagery suffer from high positional errors and the elevation of the buildings is unobtainable. The objects extracted from satellite imagery suffer from geometric errors because the building is leaning, which increases with building height. As shown in Figure 7, using individual orthophoto for the building object will lead to high horizontal error and no accurate extraction can be conducted.

Conclusion
In this research, the pipeline for producing online maps from stereo aerial and free satellite imagery has been presented. The boundary is extracted from both data sets by manually digitising the features. The result shows that the maps obtained from stereo aerial imagery are precise due to the high data resolution. The details can be easily identified using stereo imagery. High productivity is also obtained due to easy identification of the objects. The precision of the stereo aerial imagery is optimal because highly accurate GCPs are used in the processing of the imagery availability of height of the data. Satellite imagery has been globally georeferenced before downloading, thereby leading to systematic errors. The stereo imagery is free of geometric distortion due to relief displacement, which still exists in the satellite imagery. This condition will also cause error in the maps. However, satellite imagery is preferred to be used in countries with limited resources and budget for obtaining stereo imagery.
The produced map can be easily published through a web service. No high skills are required because the service is provided by the Esri Company. Maps can be easily accessed by the users through mobile phones or personal computers without installing any servers. Thus, maps are easily sheared and embedded in the personal website.