Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets
Recognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and their...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/9/8/483 |
| _version_ | 1797559021200211968 |
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| author | Jing Yu Shu Peng Weiwei Zhang Shun Kang |
| author_facet | Jing Yu Shu Peng Weiwei Zhang Shun Kang |
| author_sort | Jing Yu |
| collection | DOAJ |
| description | Recognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and their varied distribution, a consistent, larger-scale, and standardized framework for heterogeneity information extraction from this complex perspective is still lacking. Consequently, we developed a new Land Cover Complexity Index (LCCI), which is based on information-theory. The LCCI contains two foundational aspects of heterogeneity, composition and configuration, thereby capturing more comprehensive information on land cover patterns than any single metric approach. In this study, we compare the performance of the LCCI with that of other landscape metrics at two different scales, and the results show that our newly developed indicator more accurately characterizes and distinguishes different land cover patterns. LCCI provides an alternative way to measure the spatial variation of land cover distribution. Classification maps of land cover heterogeneity generated using the LCCI provide valuable insights and implications for regional conservation planning. Thus, the LCCI is shown to be a consistent indicator for the quantification of land cover heterogeneity that functions in an adaptive way by simultaneously considering both composition and configuration. |
| first_indexed | 2024-03-10T17:39:42Z |
| format | Article |
| id | doaj.art-5fad1ee89d974daea535c1490752f04a |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T17:39:42Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-5fad1ee89d974daea535c1490752f04a2023-11-20T09:44:11ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-08-019848310.3390/ijgi9080483Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover DatasetsJing Yu0Shu Peng1Weiwei Zhang2Shun Kang3College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, ChinaNational Geomatics Center of China, Beijing 100830, ChinaSchool of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, ChinaSchool of Electrical and Electronics Engineering, Hubei Polytechnic University, Huangshi 435003, ChinaRecognizing land cover heterogeneity is essential for the assessment of spatial patterns to guide conservation planning. One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics. However, due to the diversity of land cover types and their varied distribution, a consistent, larger-scale, and standardized framework for heterogeneity information extraction from this complex perspective is still lacking. Consequently, we developed a new Land Cover Complexity Index (LCCI), which is based on information-theory. The LCCI contains two foundational aspects of heterogeneity, composition and configuration, thereby capturing more comprehensive information on land cover patterns than any single metric approach. In this study, we compare the performance of the LCCI with that of other landscape metrics at two different scales, and the results show that our newly developed indicator more accurately characterizes and distinguishes different land cover patterns. LCCI provides an alternative way to measure the spatial variation of land cover distribution. Classification maps of land cover heterogeneity generated using the LCCI provide valuable insights and implications for regional conservation planning. Thus, the LCCI is shown to be a consistent indicator for the quantification of land cover heterogeneity that functions in an adaptive way by simultaneously considering both composition and configuration.https://www.mdpi.com/2220-9964/9/8/483land cover heterogeneitylandscape metricscomplexityinformation theory |
| spellingShingle | Jing Yu Shu Peng Weiwei Zhang Shun Kang Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets ISPRS International Journal of Geo-Information land cover heterogeneity landscape metrics complexity information theory |
| title | Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets |
| title_full | Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets |
| title_fullStr | Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets |
| title_full_unstemmed | Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets |
| title_short | Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets |
| title_sort | index for the consistent measurement of spatial heterogeneity for large scale land cover datasets |
| topic | land cover heterogeneity landscape metrics complexity information theory |
| url | https://www.mdpi.com/2220-9964/9/8/483 |
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