Bare Land Referenced Algorithm from Hyper-Temporal Data (BRAH) for Land Use and Land Cover Age Estimation

Sornkitja Boonprong () and Anak Khantachawana
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Sornkitja Boonprong: Department of Geography, Faculty of Social Sciences, Kasetsart University, Bangkok 10900, Thailand
Anak Khantachawana: Department of Mechanical Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand

Land, 2023, vol. 12, issue 7, 1-13

Abstract: Determining the age of land use and land cover (LULC) using satellite imagery has long been one of the challenging tasks in remote sensing research. Accurately determining age, especially crop age, is essential for plot management, biomass calculations, and carbon sequestration. This research proposes a method for determining the age of LULC using hyper-temporal satellite data. The method is based on the assumption that “the starting point for the age count is when the latest bare land status disappears at any location”. To create a geospatial layer (referred to as the BR layer) that can be used to determine the age of any land cover at a specific location, we conditionally stacked such statuses obtained from the analysis of numerous satellite imagery data. The algorithm was tested at two study sites in Thailand, where rubber plantations dominated land use. The study revealed that all the rubber ages determined using BRAH fell accurately within the range of the local government survey data. The manuscript provides a straightforward explanation of the algorithm, including the pseudocode, accuracy assessment, implementations, robustness, and limitations.

Keywords: hyper-temporal data; stand age; change detection; BRAH (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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