Oct 7
Tracking from Space: What is Cadastre and How is It Used?
- Gökçe Bal
- Oct 7
- 7 min read
Updated: Oct 28
To what extent do the maps we have today represent reality on the ground? This question is not merely a technical consideration; it also opens the door to a situation with economic, social, and legal implications. The up-to-dateness of cadastral maps directly impacts numerous processes, from urban planning and agricultural production to infrastructure investments and property rights. However, a significant portion of the maps we have are based on data produced with the limited technological capabilities of the past. These maps can fall short in the face of changing land uses, physical structures, and property relations over time.
This is precisely where satellite imagery comes into play. With maps and cadastre, we can monitor large areas with high accuracy and at frequent intervals. This technology keeps data current, speeds up fieldwork, significantly reduces costs, and significantly contributes to decision-making processes.
But how is this possible? How reliable are satellite images in a field as demanding as cadastral survey updates? What methods are used, and what problems do they solve? We'll explore these questions together, using examples from Türkiye and around the world. In this article, we'll explore step by step why this technology, which simplifies the work of so many people, from surveyors and urban planners to municipal teams and decision-makers, has become indispensable.
Contents
What is Cadastre?
Cadastre is the process of determining the boundaries of a country or region, and the location, size, and legal status of properties within the boundaries, and recording them in mapping and land registry systems. This practice is generally carried out by governments, but it can also receive support from private companies. In our country, the General Directorate of Land Registry and Cadastre (TKGM) conducts oversight, and when necessary, it receives support from licensed mapping offices.
How is Cadastre Done?
Today, updating cadastral maps virtually eliminates the need for extensive fieldwork. Satellite imagery provides frequently updated data covering large areas, making this process both faster and more cost-effective.
For example, a satellite can image hundreds of square kilometers simultaneously, providing a consistent stream of data from both rural and urban areas. Sources like NASA's Landsat archive or ESA's Sentinel series offer free access to up-to-date satellite data from around the world.
Advantages of Digitalized Maps and Cadastre
High-resolution satellite imagery can reveal even the smallest details on the terrain: a field boundary, a fence, the edge of a road, even an individual tree can now be discerned. For example, the Cartosat-1 satellite can scan a 30 km-wide area in detail with a resolution of 2.5 meters. Newer-generation commercial satellites offer even greater resolution, making parcel boundary markings much more clearly visible.
Another key advantage is the ability to compare over time. Satellite imagery allows for the analysis of changes in land use because it archives the same area over many years. For example, if an agricultural area has transitioned to settlement over time, this change is clearly visible in annual imagery. Tools like Google Earth Engine can process these images and perform big data analysis. Consequently, monitoring studies using satellite imagery provide engineers and planners with up-to-date and reliable information about the land.
Determination of Parcel Boundaries by Satellite
Satellite imagery also plays a significant role in clarifying parcel boundaries . Corners previously missing or incorrectly processed on cadastral maps become visible when viewed from a satellite. High-resolution imagery captures border fences, road edges, water channels, or variations in terrain texture. When these images are overlaid with existing cadastral vectors in a GIS (Geographic Information System) environment, boundary discrepancies are easily identified.
For example, if a parcel's survey sketch contains errors, comparing it with the actual boundary in a satellite image will highlight any outliers. Checking cadastral maps over satellite maps using tools like Google Earth or QGIS is a quick quality assurance method. This process is sometimes called " parcel boundary detection using satellite imagery " and is effective in uncovering illegal use or recording errors. This allows the established boundaries to be aligned with actual field conditions.
Land Use Change: Remote Sensing Analyses
Analysis of satellite imagery reveals both boundaries and overall land use. For example, NDVI (vegetation health index) calculations from the data can help determine whether agricultural land is actively cultivated. Satellite data can be used to monitor whether agricultural land in a region is being developed or abandoned over time. Similarly, clearings in forested areas, signs of new roads, or settlements can be easily identified.
The time series in the satellite archive is particularly valuable for observing forest loss or urban expansion. For example, if green space in a valley has been replaced by buildings over the years, this change is clearly visible. This allows planners to more accurately assess and intervene in the demand for new settlements or the erosion of agricultural land.
Additionally, software such as QGIS and ArcGIS are frequently used for change detection. Various district municipalities in Turkey are implementing projects using Google Earth Engine and ArcGIS to examine the conversion of agricultural lands on urban peripheries to non-agricultural uses. There are teams using Google Earth Engine to generate agricultural-tree cover maps from multi-year satellite images and conduct scenario analysis. The QGIS land use analysis toolset is also a good choice for such applications; by combining the satellite and cadastral layers in QGIS, change zones can be displayed in color.
Illegal Construction Detection: Satellite-Based Inspection
Illegal construction poses a significant problem, particularly in rapidly urbanizing surrounding areas. Satellite technology has begun to offer solutions. In Turkey, high-resolution observation satellites like the Göktürk-1, initially designed for forest inspection and disaster management, have been announced as being capable of monitoring illegal construction . This means that while monitoring forest changes, it's also possible to identify unlicensed housing or illegal construction sites.
Thanks to developing artificial intelligence and computer vision techniques, newly constructed buildings can be automatically detected from satellite imagery. It's known that, especially in countries with high property taxes, property owners add unregistered additional buildings to avoid paying taxes. Satellite imagery can detect these housing expansions as "a change compared to the previous year's image." Machine learning algorithms (CNN, K-means, etc.) can flag newly constructed structures and match them with local land registry/cadastral records. This allows for mapping illegal construction in a large-scale rural or urban area over the past 10 years. Metropolitan municipalities and other institutions are now using satellite-based systems as an early warning tool for unauthorized construction. In short, satellite imagery is becoming increasingly critical for detecting illegal construction .
Software Solutions for Cadastral Maps
Many GIS (Geographic Information System) software programs are used to perform these analyses. In the open-source world, QGIS is frequently used for analyzing satellite imagery and processing cadastral data. It is possible to download and process real-time satellite layers with plugins installed on QGIS (e.g., via the Web Map Service). On the commercial side, ArcGIS Pro and ArcGIS Online also offer high-level image classification and analysis tools. For example, ArcGIS's Smart Mapping tools can quickly transform satellite data into color land use maps.
Additionally , the Google Earth Engine (GEE) platform provides a powerful infrastructure for processing large satellite datasets. Hundreds of time-lapse images can be easily processed and analyzed with cadastral boundary layers in GEE. For example, it is possible to create snapshot maps (similar to Spatial Analyst) by combining them with population or infrastructure data. In Turkey, some organizations upload maps provided by the General Directorate of Land Registry and Cadastre to GEE to generate change maps. TKGM's free Parcel Query application allows simple users to access up-to-date parcel boundaries on satellite imagery. In summary, QGIS is a leading software tool for land use analysis, ArcGIS for spatial statistics, and GEE for historical satellite analysis.
Satellite-Assisted Cadastre Applications in Türkiye
The most frequent use of remote sensing applications in Turkey is in the detection of illegal construction . Dense construction has been observed around Istanbul's third bridge and highway; municipalities are monitoring these areas via satellite. Similarly, the emergence of new villas in villages along the Black Sea and Mediterranean coasts is being monitored using satellite imagery. In terms of cadastral land use, it is known that agricultural land is increasingly being replaced by construction sites in the Thrace region. For example, infrastructure emerging around large production farms on the Edirne-Kırklareli line is being documented through satellite recording.
The Bursa Metropolitan Municipality uses drone and satellite data in an integrated system. In recent years, unmanned aerial vehicles have been scanning the areas surrounding Osmangazi and Nilüfer, and the resulting images are used to identify illegally constructed floors and structures, marking them at the street/neighborhood scale. This data, combined with information systems, allows both the municipality and citizens to conduct land registry inquiries using satellite imagery. This allows for both property tracking and real-time updates of illegal construction statistics.
Turkish satellites like Göktürk-1 have also begun to be used in civilian cadastral surveys. High-resolution images produced to protect forests and agricultural lands also aid in tracking property boundaries. The juxtaposition of maps provided by the General Directorate of Land Registry and Cadastre with current satellite imagery can provide rapid resolution of boundary disputes. Pilot applications in this area have resulted in hundreds of parcels being re-established annually thanks to satellite monitoring in rural areas of several provinces outside Istanbul.
International Satellite-Based Mapping and Cadastre Projects
Many countries worldwide are utilizing satellite data for digital cadastral surveys. For example, in India, as part of the Digital Land Records Modernization Program (DILRMP), satellite imagery is being blended with field measurements. According to presentations, high-resolution satellite imagery is being paired with GPS-supported measurements for village-based cadastral renewals, updating maps. Similarly, in Latin America, countries like Brazil and Cuba are integrating large-scale national documents with remote sensing-supported cadastral data. Countries like Nigeria and Kyrgyzstan are also implementing satellite-based mapping projects with the support of the World Bank. In Europe, some countries like Estonia and Finland are enhancing their Geographic Information System infrastructures with satellite observations. In short, property tracking using satellite imagery has become an increasingly standard method in digitalized cadastral systems worldwide.
Satellite imagery is a powerful tool that supports cadastral updates, speeds up the process, adds accuracy, and reduces costs. Large areas can be scanned quickly, and new structures or boundary changes can be clearly identified.
By making historical comparisons with AI-powered analysis and open-source tools (e.g., Google Earth Engine), it has become possible to easily identify lost agricultural land or illegal structures. This provides a more robust foundation for decision-making in surveying engineering. In the near future, these processes will be almost completely automated with robotic systems and smarter sensors.
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