A study of satellite-based mapping of real estate price and its applications

• Project/Area Number: 19H02256
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Single-year Grants
• Section: 一般
• Review Section: Basic Section 22050:Civil engineering plan and transportation engineering-related
• Research Institution: The University of Tokyo
• Principal Investigator: Shibasaki Ryosuke 東京大学, 空間情報科学研究センター, 教授 (70206126)
• Co-Investigator(Kenkyū-buntansha): Seetharam KE 東京大学, 空間情報科学研究センター, 客員教授 (10817290)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Project Status: Completed (Fiscal Year 2021)
• Budget Amount: ¥17,420,000 (Direct Cost: ¥13,400,000、Indirect Cost: ¥4,020,000); Fiscal Year 2021: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000); Fiscal Year 2020: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000); Fiscal Year 2019: ¥7,150,000 (Direct Cost: ¥5,500,000、Indirect Cost: ¥1,650,000)
• Keywords: 衛星画像解析 / 住環境 / 地価 / 大都市 / 途上国 / 深層学習 / 空間情報科学 / 衛星画像 / 都市開発 / 不動産価格 / 大都市圏 / マッピング / データ解析

Outline of Research at the Start

都市開発等により都市は常に変容しているが、それを駆動する最も重要な変数の一つである不動産価格（地価等）を衛星画像から推定することを試みる。東京を参照しつつバンコク、マニラ、ムンバイと、所得水準やインフラの整備状況、建物粒度等が異なるアジアの都市に適用し精度、利用可能性を実証的に明らかにする。その際、近年進展著しい深層学習等を用い、いわゆる地物等の抽出に加え、その密度・配置、高さ、緑地・空地との関係性など多面的な特徴を衛星画像から抽出することを試みる。土地価格はインフラ整備の効果を金額的に評価するために利用でき、不動産開発の計画、デザイン、都市財源の確保といった観点からも非常に重要である。

Outline of Final Research Achievements

Since the Covid-19 has caused major obstacles to the collection of urban land price data in developing countries, we have focused on the advancement of satellite image analysis to obtain detailed urban environmental information from satellite images and clarified the relationship with domestic land price data. We have developed advanced techniques for extracting buildings and detecting the changes using high-resolution imagery, as well as those for automatically extracting slum areas (i.e., areas with significantly low environmental quality and land prices) using mainly medium-resolution satellite imagery. These methods were found to achieve a significant improvement in accuracy.
We also obtained a large amount of available land price data in Japan and analyzed the relationship with environmental factors obtained from satellite images. From these results, we have obtained a prospect to estimate land prices in large cities in developing countries from satellite images.

Academic Significance and Societal Importance of the Research Achievements

多様な衛星画像を利用して建物の自動抽出や変化の自動検出、あるいは住環境の劣悪な貧困地域の自動抽出など、都市環境の詳細情報を抽出する研究は他に少なく、手法開発研究としても、実証的な意味でも非常に有益な成果が得られた。
途上国の都市開発においても、固定資産価値の上昇は、都市の経済成長や都市整備のための公的財源の原資として非常に重要である。資産価値情報を衛星画像などのオープンなデータを用いてある程度推定できるようになれば、長期的には都市財政の安定化や公共サービスの高度化に貢献できる。

Research Products

• [Int'l Joint Research] University of Dhaka(バングラデシュ)
• [Int'l Joint Research] University of Eduardo Mondlane(モザンビーク)
• [Int'l Joint Research] アジア工科大学院(タイ)
• [Int'l Joint Research] ハルビン工業大学(中国)
• [Journal Article] Understanding the urban environment of developing countries from satellite images with new classification methods - focusing on formal and informal (2022)
  • Author(s): Qianwei Cheng, Moinul Zaber, AKM Mahbubur Rahman, Haoran Zhang, Zhiling Guo, Akiko Okabe and Ryosuke Shibasaki
  • Journal Title: Sustainability 2022, 14(7), 4336 Volume: 14 Issue: 7 Pages: 4336-4336
  • DOI: 10.3390/su14074336
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Understanding rooftop PV panel semantic segmentation of satellite and aerial images for better using machine learning (2021)
  • Author(s): Peiran Li, Haoran Zhang, ,Zhiling Guo, Suxing Lyu, Jinyu Chen, Wenjing Li, XuanSong Ryosuke Shibasaki, Jinyue Yan
  • Journal Title: Advances in Applied Energy Volume: 4 Pages: 100057-100057
  • DOI: 10.1016/j.adapen.2021.100057
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] GRAPH NEURAL NETWORK BASED MULTI-FEATURE FUSION FOR BUILDING CHANGE DETECTION (2021)
  • Author(s): Wei Yuan, FanZipei, Ryosuke Shibasaki et al.
  • Journal Title: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., Volume: XLIII-B3-2021 Pages: 377-382
  • DOI: 10.5194/isprs-archives-xliii-b3-2021-377-2021
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Learn to Extract Building Outline from Misaligned Annotation through Nearest Feature Selector. (2020)
  • Author(s): Yuxuan Wang, Guangming Wu, Yimin Guo, Yifei Huang and Ryosuke Shibasaki.
  • Journal Title: Remote Sensing, 12(17), 2020. Volume: 12 Issue: 17 Pages: 12-17
  • DOI: 10.3390/rs12172722
  • Int'l Joint Research
• [Journal Article] A Stacked Fully Convolutional Networks with Feature Alignment Framework for Multi-Label Land-cover Segmentation. (2019)
  • Author(s): Guangming Wu, Yimin Guo, Xiaoya Song, Zhiling Guo, Haoran Zhang, Xiaodan Shi, Ryosuke Shibasaki and Xiaowei Shao
  • Journal Title: International Journal of Remote Sensing Volume: 11 Issue: 9 Pages: 1051-1051
  • DOI: 10.3390/rs11091051
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Presentation] Geosr: A Computer Vision Package for Deep Learning Based Single-Frame Remote Sensing Imagery Super-Resolution (2019)
  • Author(s): Zhiling Guo,Guangming Wu,Xiaodan Shi,Mingzhou Sui,Xiaoya Song,Yongwei Xu,Xiaowei Shao,Ryosuke Shibasaki
  • Organizer: In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 3376-3379). IEEE.
  • Int'l Joint Research
• [Book] Economics and Finance (R0) Part of the India Studies in Business and Economics book series (2021)
  • Author(s): Yoshino, N., Gopakumar, K.U., Paramanik, R.N., Taghizadeh-Hesary, F., Revilla, M.L., Ram, K.E.S.
  • Total Pages: 21
  • Publisher: Springer, Singapore
  • ISBN: 9789811670626