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Article

Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution

1
Center for Environmental Science of IPB University (PPLH), PPLH Building, Jalan Lingkar Akademik, IPB University, Dramaga, Bogor 16680, Indonesia
2
Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, IPB University, Dramaga, Bogor 16680, Indonesia
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World Resources Institute Indonesia (WRI Indonesia), Wisma PMI Building 7th Floor, Jalan Wijaya I, No. 63, Kebayoran Baru, Jakarta 12170, Indonesia
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Center for Remote Sensing Technology and Data, Deputy of Remote Sensing Affairs, Indonesian National Institute of Aeronautics and Space (LAPAN), Jalan LAPAN No. 70, Pekayon, Pasar Rebo, Jakarta 13710, Indonesia
*
Author to whom correspondence should be addressed.
Academic Editors: Joanne N. Halls, Weidong Li and Chuanrong Zhang
Received: 2 October 2021 / Revised: 19 November 2021 / Accepted: 27 November 2021 / Published: 29 November 2021
(This article belongs to the Special Issue Geographic Data Analysis and Modeling in Remote Sensing)
This article demonstrated an easily applicable method for measuring the similarity between a pair of point patterns, which applies to spatial or temporal data sets. Such a measurement was performed using similarity-based pattern analysis as an alternative to conventional approaches, which typically utilize straightforward point-to-point matching. Using our approach, in each point data set, two geometric features (i.e., the distance and angle from the centroid) were calculated and represented as probability density functions (PDFs). The PDF similarity of each geometric feature was measured using nine metrics, with values ranging from zero (very contrasting) to one (exactly the same). The overall similarity was defined as the average of the distance and angle similarities. In terms of sensibility, the method was shown to be capable of measuring, at a human visual sensing level, two pairs of hypothetical patterns, presenting reasonable results. Meanwhile, in terms of the method′s sensitivity to both spatial and temporal displacements from the hypothetical origin, the method is also capable of consistently measuring the similarity of spatial and temporal patterns. The application of the method to assess both spatial and temporal pattern similarities between two deforestation data sets with different resolutions was also discussed.
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Keywords: deforestation hotspots; generic method; similarity; spatial pattern; temporal pattern deforestation hotspots; generic method; similarity; spatial pattern; temporal pattern
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MDPI and ACS Style

Suyamto, D.; Prasetyo, L.; Setiawan, Y.; Wijaya, A.; Kustiyo, K.; Kartika, T.; Effendi, H.; Permatasari, P. Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution. Geomatics 2021, 1, 464-495. https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics1040027

AMA Style

Suyamto D, Prasetyo L, Setiawan Y, Wijaya A, Kustiyo K, Kartika T, Effendi H, Permatasari P. Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution. Geomatics. 2021; 1(4):464-495. https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics1040027

Chicago/Turabian Style

Suyamto, Desi, Lilik Prasetyo, Yudi Setiawan, Arief Wijaya, Kustiyo Kustiyo, Tatik Kartika, Hefni Effendi, and Prita Permatasari. 2021. "Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution" Geomatics 1, no. 4: 464-495. https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics1040027

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