Automatic Extraction for Land Parcels Based on Multi-Scale Segmentation

Fei Liu, Huizhong Lu, Lilei Wu, Rui Li, Xinjun Wang and Longxi Cao ()
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Fei Liu: College of Earth Science, Chengdu University of Technology, Chengdu 610059, China
Huizhong Lu: National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210029, China
Lilei Wu: College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China
Rui Li: College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China
Xinjun Wang: China Academy of Transportation Sciences, Beijing 100029, China
Longxi Cao: College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China

Land, 2024, vol. 13, issue 2, 1-24

Abstract: Different land parcels possess unique microclimates, soils, and biological conditions, which in turn significantly influence the land parcels themselves, impacting biodiversity, hydrological relationships, land degradation, geological disasters, and other ecological environments. Therefore, researching an efficient and accurate method capable of extracting land parcels with the least internal heterogeneity at the macro, meso, and micro scales is extremely important. Multi-scale segmentation, based on scale and resolution analysis techniques, is a bottom-up merging technology that minimizes internal heterogeneity within regions and maximizes heterogeneity between different units. This approach is extensively applied in multi-scale spectral feature extraction and classification and is further combined with deep learning techniques to enhance the accuracy of image classification. This study, using Xinghai County in Qinghai Province as an example, employs multi-scale segmentation and hydrological analysis methods to extract land parcels at different spatial scales. The results show (1) that the land parcels extracted using the hydrological analysis method are catchment units centered around rivers, including slopes on both sides of the river. In contrast, multi-scale segmentation extracts regions comprising land parcels with similar properties, enabling the segregation of slopes and channels into independent units. (2) At a classification threshold of 19, multi-scale segmentation divides the study area into five different types of land parcels, reflecting the heterogeneity of terrain undulations and their hydrological connections. When the classification threshold is set to 31, the study area is divided into 15 types of land parcels, primarily highlighting micro-topographic features. (3) Multi-scale segmentation can merge and categorize areas with the least heterogeneity in land parcels, facilitating subsequent statistical analysis. Therefore, mesoscale land parcels extracted through multi-scale segmentation are invaluable for analyzing regional Earth surface processes such as soil erosion, sediment distribution and transportation. Microscale land parcels are significantly important for identifying high-risk areas in relation to geological disasters like landslides and collapses.

Keywords: multi-scale segmentation; land parcels; hydrological analysis method; principal component analysis; Rstoolbox (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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