Leveraging Digital Elevation Modeling and Urban Planning to Design Future Cities
What is a Digital Elevation Model (DEM)?
The United States Geological Survey (USGS), a renowned organization among geospatial professionals, defines a DEM as a digital file with terrain elevations of ground positions at regular horizontal intervals. Simply put, a DEM carries information about the surface topography of the bare Earth; while excluding any surface objects whether natural or manmade including rivers, trees, buildings, and more.
A DEM can be generated from satellite imagery, or aerial photos taken at regular intervals with a precision that allows the calculation of the slope of each ground’s position, relative to one another. The factors that influence the level of accuracy in a DEM include:
- The resolution of the data source
- The quality of the processing software
- The level of detail required by the user
Types of Digital Elevation Models
There are two variations of the Digital Elevation Model: The Digital Terrain Model (DTM), and the Digital Surface Models (DSM). Each of these models are best suited for particular GIS applications; but generally, they are popularly used in land management, construction, transportation, agriculture, and mining, among many others.
Digital Terrain Models (DTMs)
The Digital Terrain Model is a more detailed representation of the Earth’s surface than the DEM. In addition to the bare earth topography, it also captures the vector features of the natural terrain such as ridges, rivers, and mountains. Conclusively, we can say a DTM is simply a DEM that also includes features of the natural terrain. It is thus possible to interpolate a DTM and produce a DEM, since technically a DEM is already contained in a DTM, but it is impossible to generate a DTM from a DEM, since a DEM contains lesser details.
Digital Terrain Models are a versatile tool for many different types of applications and modeling needs. They can be used in flood or drainage modeling, land use studies, geological applications, and planetary science.
Digital Surface Models (DSMs)
A Digital Surface Model captures both natural and man-made structures on the surface of the Earth. This means that in addition to what the DTM shows, a DSM further includes information on the vegetation, water bodies, buildings, and any other feature on the Earth’s surface. Typically, a DSM captures all the reflective surfaces of features that are elevated above the bare-earth. This makes DSMs a great tool for urban planning since they show the earth’s terrain along with all the surface features.
With 3D surface models, it is easier to understand and explain built up areas which are continuously changing due to urban expansion. DSMs are the most detailed and hence very useful in monitoring urban changes and planning cities of the future. The sections that follow below will thus focus on DSMs, explaining how they are generated, and highlighting their application in urban planning. We will also demonstrate the contribution of DSMs to urban planning by including a step by step guide on how they can be used in 3D city modeling.
Methods of Generating Digital Surface Models
Generating DSMs Using LiDAR
As mentioned above, DSMs can be created from cloud points of laser scanning with specific wavelengths of light. This makes LiDAR (Light Detection and Ranging) a handy tool for this method. The cloud points are generated by the LiDAR unit by sending light pulses from the laser scanning system to the ground. When the pulses hit objects on the earth’s surface they are reflected back to the sensor of the LiDAR unit. The time it took each pulse to return to the sensor is used to calculate the distance covered by the pulse. This distance, along with the LiDAR unit’s position and angle of tilt, are used in the 3D reconstruction of the point at which the pulse hit an object. In this way, LiDAR produces a point cloud of elevation for the region under study—capturing the ground elevation data along with that of the tree canopies, buildings, and other features.
The huge point cloud data captured from LiDAR units is futile when in a two-dimensional plane, but when these points are modeled in a 3D surface, they open more possibilities for further analysis as both natural and built-up features of the region take their digital form.
LiDAR’s precision and efficiency in capturing feature data make it the most preferred data collection method for DSM generation, but unfortunately it is also very expensive. For this reason, it is mostly feasible to use in high-value regions like cities.
Generating DSMs Using Stereo Photogrammetry
Alternatively, DSMs can be generated from automated image matching of stereo-photogrammetry or high-resolution optical stereo images. A process called stereo-matching is used to find the corresponding pixels in a pair of images and facilitate 3D reconstruction by triangulation, but this is only possible if the interior and exterior orientations are known.
Stereo images can be obtained from either aerial photography or satellite remote sensing. When using oriented images, it is possible to measure the object heights manually for use as reference. The final results are derived by applying Computer vision algorithms to the images.
There are various open-source and commercial tools available in the market that can programmatically derive elevation data from stereo images. Therefore, generating DSMs from stereo photography is a more accessible and scalable method as opposed to using LiDAR. The Semi-Global Matching (SGM) algorithm is the most commonly used and well-known algorithm.
Applications of DSM in Urban Planning
Digital Surface Modeling can be used in various ways to contribute to the development of smart cities and planning effective land utilization. Some of these ways are expanded below:
1. Analyzing Existing Geography
Digital Surface Modeling assists in the analysis, storage, and manipulation of physical, economic, and social data of the area of interest; which is useful in visualizing the present scenario of the region under study. It further assists in identifying the areas of conflict in land development and the economically sensitive areas.
The information garnered from analyzing the existing geography of an area enriches decision making processes for that area and impact both the present and future planning activities.
2. Developing Land-use Plans
By analyzing the present conditions of an area, it is possible to develop land-use maps that proposes how best the land can be utilized. These maps can act as a community’s guide to building plans, infrastructure, and public spaces in the future. With increasing concerns on sustainable development, environmental conservation, and resilient cities, land-use maps can be leveraged to develop plans that account for environmental conservation, mitigate pollution, improve transportation, and prevent urban sprawl.
A DSM can also be used in predictive data techniques to explore plausible scenarios for the future. When used in this manner, a DSM can pave the way toward planning a thoughtful, sustainable, and sound land-use map for the future.
3. Site Selection and Land Suitability Analysis
Before constructing an airport or any other crucial infrastructure, it is always mandatory to carry out a prior analysis of the suitability of the location and its surroundings. At this point, we can rely on DSM when performing a land suitability analysis to determine the best site for the construction of new infrastructure and amenities.
We can also use DSMs in spatial queries and current environmental analysis to uncover areas of environmental sensitivity. By overlaying existing land development maps on generated land suitability maps, we can easily discover areas of conflict between the environment and potential development.
Guide to DSM Generation for 3D City Modelling
Digital Surface Models unlock more possibilities for analysis and planning when used to model 3D cities. In this section we will take a closer look at how this is done.
DSM Generation Method
First, we have to make a decision on the method of DSM generation that will be used by considering things like the accessibility, efficiency and budget. In this guide, the chosen method for DSM generation is that of using stereo-photogrammetry and will follow a format used in a case study of the Fez region of Morocco. This method requires two (stereo) images of the same region captured at specific time intervals in order to reconstruct a 3D stereo model.
Stereo images are required because they make it possible to extract altimetric information of the features captured. These images can be obtained from aerial or satellite imagery for a particular area of interest.
Ideally, there are three steps involved in the generation a DSM from stereo-photogrammetry:
- Reflecting the relationship between ground points and image pixels by setting up a mathematical model
- Obtaining disparity map by image matching
- Calculating the altitude of all the points
Let’s now look at how these steps can be implemented to generate a DSM for 3D city modeling in more details below:
Step 1: Determining Ground Point Coordinates
For this step, the point measurement tool is used to collect Ground Control Points (GCPs) from the stereo images and tie the common points in both images to be used in correlation.
For those using IKONOS imagery, the RPC file with the images will contain all the valuable information and so you will not need a large number of control points.
A useful tip for improving the results of orthorectification is to choose the right GCPs and generating the tie points accurately.
Step 2: Digital Image Matching for Digital Surface Model
Digital Image Matching is the process of identifying the ground points appearing in the overlap portion of the stereo images. The output of this exercise should give you an image location of ground points that appear within the DSM.
Step 3: Constructing the DSM
The basis for DSM construction are the automatically extracted and calculated mass points, but it is worth noting that all DSMs are not constructed in the same way. The ultimate decision on how to construct a DSM depends on the defined output type and the software in use.
When using the LPS software of Leica Geosystems to extract the DSM from aerial photogrammetry, the process will distinctly involve the following:
Create/Open Block File: This operation is for the selection of the sensor model and defining its block properties, adding imagery to the bock file, collecting GCPs, generating tie points, and refining the model.
DSM Extraction Process: This step, is for setting the DSM extraction properties. We need to check the advanced extraction properties; generate and view the DSM from aerial image stereo pairs. We also need to check the contour map towards the end.
The quality of Digital Surface Models is measured by the accuracy of the elevation at each pixel, and how accurate the presentation of the morphology is. Several factors play a vital role in the resulting quality of DSM derived products. They include:
- The roughness of the terrain and the analysis algorithm
- Interpolation algorithm
- Pixel size and vertical resolution
- Sampling density
Model the Future With Digital Elevation Models!
3D surface models can visualize the present and trigger a vision for the future. Leveraging them makes it possible to develop smart cities by efficient planning.
DEMs are resourceful tools that can cater towards analyzing the present situation to develop future land-use maps; plan resource inventory, determine effective sites for specific usage, and analyze socio-economic and environmental data.