Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets

被引:5
作者
Yu, Jing [1 ]
Peng, Shu [2 ]
Zhang, Weiwei [3 ]
Kang, Shun [4 ]
机构
[1] China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China
[2] Natl Geomat Ctr China, Beijing 100830, Peoples R China
[3] Suzhou Univ Sci & Technol, Sch Environm Sci & Engn, Suzhou 215011, Peoples R China
[4] Hubei Polytech Univ, Sch Elect & Elect Engn, Huangshi 435003, Hubei, Peoples R China
关键词
land cover heterogeneity; landscape metrics; complexity; information theory; LANDSCAPE METRICS; BOLTZMANN ENTROPY; FRAGMENTATION; PATTERN; INFORMATION; VALIDATION; COMPLEXITY; INDICATORS; DIVERSITY; HABITATS;
D O I
10.3390/ijgi9080483
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 57 条
[1]   A new approach to spatial entropy measures [J].
Altieri, L. ;
Cocchi, D. ;
Roli, G. .
ENVIRONMENTAL AND ECOLOGICAL STATISTICS, 2018, 25 (01) :95-110
[2]   Complexity of two-dimensional patterns [J].
Andrienko, YA ;
Brilliantov, NV ;
Kurths, J .
EUROPEAN PHYSICAL JOURNAL B, 2000, 15 (03) :539-546
[3]  
[Anonymous], 2012, PERSPECTIVES ELECT S, DOI DOI 10.1007/978-3-642-20180-6_8
[4]  
[Anonymous], 2011, SRS136 DEP AGR FOR S
[5]   Entropy increase of fragmented habitats: A sign of human impact? [J].
Bogaert, J ;
Farina, A ;
Ceulemans, R .
ECOLOGICAL INDICATORS, 2005, 5 (03) :207-212
[6]   Handling heterogeneous bipolar information for modelling environmental syndromes of global change [J].
Bordogna, G. ;
Boschetti, M. ;
Brivio, P. A. ;
Carrara, R. ;
Stroppiana, D. ;
Weissteiner, C. J. .
ENVIRONMENTAL MODELLING & SOFTWARE, 2012, 36 :131-147
[7]   A standardized procedure for surveillance and monitoring European habitats and provision of spatial data [J].
Bunce, R. G. H. ;
Metzger, M. J. ;
Jongman, R. H. G. ;
Brandt, J. ;
De Blust, G. ;
Elena-Rossello, R. ;
Groom, G. B. ;
Halada, L. ;
Hofer, G. ;
Howard, D. C. ;
Kovar, P. ;
Mucher, C. A. ;
Padoa-Schioppa, E. ;
Paelinx, D. ;
Palo, A. ;
Perez-Soba, M. ;
Ramos, I. L. ;
Roche, P. ;
Skanes, H. ;
Wrbka, T. .
LANDSCAPE ECOLOGY, 2008, 23 (01) :11-25
[8]   A landscape shape index-based sampling approach for land cover accuracy assessment [J].
Chen, Fei ;
Chen, Jun ;
Wu, Hao ;
Hou, DongYang ;
Zhang, WeiWei ;
Zhang, Jun ;
Zhou, XiaoGuang ;
Chen, LiJun .
SCIENCE CHINA-EARTH SCIENCES, 2016, 59 (12) :2263-2274
[9]   Land cover and landscape diversity analysis in the West Polesie Biosphere Reserve [J].
Chmielewski, Szymon ;
Chmielewski, Tadeusz J. ;
Tompalski, Piotr .
INTERNATIONAL AGROPHYSICS, 2014, 28 (02) :153-162
[10]  
Claramunt C, 2005, LECT NOTES COMPUT SC, V3693, P218