Designing and Implementing a Custom Blockchain for Spatial Data Sharing

Abstract. With the expansion in the volume and variety of spatial data and the increasing reliance of geospatial information systems (GIS) on web-based platforms, the need for secure, transparent, and trustworthy structures for data storage and exchange has become more pressing than ever. Conventional centralized architectures, despite their ease of implementation and management, face challenges such as centralization, security vulnerabilities, and reduced accessibility. This study investigates the utilization of blockchain technology as a decentralized and tamper-resistant platform to address these challenges. First, the study reviews the related literature on the integration of blockchain with GIS and analyzes the shortcomings of existing blockchains in meeting the specific requirements of this domain. Then, an initial design of a blockchain-based GIS is presented, with its architecture specifically tailored to the sharing of spatial data within this framework. In this system, the Well-Known Binary (WKB) format is selected for storing spatial data, and a simplified Proof-of-Work consensus algorithm is employed to coordinate among nodes. The system is implemented at the proof-of-concept level using the Python programming language and the Flask framework. The proposed approach can serveas an effective step toward the development of dedicated blockchains for the exchange and sharing of spatial data and provides a suitable foundation for future research aimed at enhancing the scalability and performance of GIS.

Authors

Institutions

Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2026-05-29
DOI
https://doi.org/10.5194/isprs-annals-x-4-w8-2025-655-2026
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Designing and Implementing a Custom Blockchain for Spatial Data Sharing

Ali Zare Zardiny, Saleh Saeidi
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Blockchain Technology Applications and Security
article

Designing and Implementing a Custom Blockchain for Spatial Data Sharing

Ali Zare Zardiny, Saleh Saeidi
article en

Abstract

Abstract. With the expansion in the volume and variety of spatial data and the increasing reliance of geospatial information systems (GIS) on web-based platforms, the need for secure, transparent, and trustworthy structures for data storage and exchange has become more pressing than ever. Conventional centralized architectures, despite their ease of implementation and management, face challenges such as centralization, security vulnerabilities, and reduced accessibility. This study investigates the utilization of blockchain technology as a decentralized and tamper-resistant platform to address these challenges. First, the study reviews the related literature on the integration of blockchain with GIS and analyzes the shortcomings of existing blockchains in meeting the specific requirements of this domain. Then, an initial design of a blockchain-based GIS is presented, with its architecture specifically tailored to the sharing of spatial data within this framework. In this system, the Well-Known Binary (WKB) format is selected for storing spatial data, and a simplified Proof-of-Work consensus algorithm is employed to coordinate among nodes. The system is implemented at the proof-of-concept level using the Python programming language and the Flask framework. The proposed approach can serveas an effective step toward the development of dedicated blockchains for the exchange and sharing of spatial data and provides a suitable foundation for future research aimed at enhancing the scalability and performance of GIS.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-4/W8-2025
University of Tehran (IR)
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.