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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (2) : 112-121     DOI: 10.6046/zrzyyg.2022163
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Construction of 3D landscape indices based on tilt photogrammetry: A case study of Tianheng Island in Shandong Province
WANG Jue1,2(), GUO Zhen1,2(), ZHANG Zhiwei1,2, XU Wenxue1,2, XU Hao2
1. Coastal Science and Marine Policy Center, First Institute of Oceanography, MNR, Qingdao 266061, China
2. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
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Abstract  

Landscape indices are quantitative indices used to reflect the composition and spatial configuration of a landscape ecological structure. Current landscape index systems are generally constructed based on the characterization of 2D spatial characteristics, thus their evaluation results fail to accurately reflect the pattern and composition of a real 3D landscape system. Accordingly, there is an urgent need to develop an index system used to describe the 3D landscape characteristics of islands and a whole-process evaluation method. With Tianheng Island in Shandong Province as a case study and based on the point clouds of unmanned aerial vehicle (UAV) tilt photogrammetry, as well as the classification and processing of point clouds using the deep learning method, this study constructed six basic 3D landscape indices covering type and landscape scales to quantitatively describe the 3D landscape features of the island. Moreover, this study established the building landscape indices to evaluate the impacts of the construction activities of human beings on the island ecosystem. The results are as follows: ① As revealed by the analysis of basic 3D landscape indices, the buildings on Tianheng Island are characterized by small 3D volumes and dense spatial distribution. Furthermore, tall vegetation exhibits high isolation, regularity, and spatial aggregation, while low vegetation exhibits high diversity, compactness, and connectivity; ② Due to the difference in dimension, 3D landscape indices contain more spatial information than 2D landscape indices and are greatly affected by terrain undulation; ③ In the case of the same landscape type, the landscape shape index (TLSI) is more sensitive to the change in height (sensitivity index: 7.480). In the case of the same landscape index, the building type changes more greatly than vegetation with irregular spatial characteristics (sensitivity index: 5.861) and is influenced by the design characteristics of buildings; ④ Tianheng Island has a 3D building index (TBI) of 0.523, which increases with an increase in the density and complexity of buildings. Compared with building density and spatial congestion indices, TBI can better reflect the influence of artificial structures on the 3D landscape pattern of the island. This study aims to provide methodological support and a case study for the construction of 3D landscape indices based on modern surveying and mapping technology, as well as the planning of 3D spatial landscapes and the development of their management and evaluation system.
Keywords 3D landscape index      tilt photogrammetry      building landscape index      island      3D landscape pattern     
ZTFLH:  TP79  
  P901  
Issue Date: 07 July 2023
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Jue WANG
Zhen GUO
Zhiwei ZHANG
Wenxue XU
Hao XU
Cite this article:   
Jue WANG,Zhen GUO,Zhiwei ZHANG, et al. Construction of 3D landscape indices based on tilt photogrammetry: A case study of Tianheng Island in Shandong Province[J]. Remote Sensing for Natural Resources, 2023, 35(2): 112-121.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022163     OR     https://www.gtzyyg.com/EN/Y2023/V35/I2/112
Fig.1  Location of Tianheng Island
Fig.2  3D perspective of Tianheng Island
Fig.3  3D perspective of local Tianheng Island
Fig.4  Land use type of Tianheng Island
Fig.5  3D landscape index construction technology roadmap
Fig.6  DSM of Tianheng Island
Fig.7  Classification of point cloud on Tianheng Island
景观尺度 指数名称 计算公式 公式说明
类型 三维斑块密度TPD T P D = N i V i 　 描述单位体积上的斑块数,是描述景观破碎化的重要基础指标,表示三维景观内的空间异质性和均匀性
三维形状指数TLSI T L S I = 0.25 S i L V i V i 　 描述斑块形状与相同面积的规则圆形或正方形之间的偏差,测量其形状复杂程度
三维斑块占比指数TPLAND T P L A N D = S i E ×100% 描述各景观类别在海岛区域景观格局中的比重,量化了各斑块类型在景观中的比例丰度
三维最大斑块指数TLPI T L P I = V m a x V ×100% 描述各类景观中最大斑块所占该类景观的体积之比,有助于确定景观的优势类型,其大小决定着景观的丰富度或地物占比情况
景观 斑块占比 P i P i = V i V i类斑块所占体积比,反映斑块类型(类)占景观的比例,是景观多样性统计中的基础
三维香农多样性指数TSHDI T S H D I = - ∑ i = 1 m ( P i l n P i ) 减去所有斑块类型中各斑块类型的丰度比例乘以该比例的总和,用以表示海岛区域内不同斑块类型的多少,即丰富度问题
三维香农均匀度指数TSHEI T S H E I = - l n m ∑ i = 1 m ( P i l n P i ) 香农多样性指数除以给定景观丰度下的最大可能多样性,TSHEI=0表明景观仅由一种斑块组成,无多样性; TSHEI=1表明各斑块类型均匀分布,有最大多样性
其他 BCR B C R = E b V b 建筑物表面积和建筑物体积之间的量度
MBSI M B S I = S b h 建筑物面积和建筑物高度比值
PR P R = V b V 区域内的地上建筑物总面积与净用地面积的比率
TBI T B I = B C R + 10 3 / M B S I + P R 描述景观尺度内建筑物空间分布格局对原有空间的影响程度
BVD B V D = ∑ p = 1 k S p - H p S 用于量化建筑物密度程度的指数,其值高度依赖于岛屿的总面积
SCD S C D = ∑ p = 1 k V p A m a x { H p } 所有建筑物的体积累加值占研究区体积的百分比,反映了三维空间中建筑物的拥堵
Tab.1  3D landscape index formula and explanation
景观
尺度		 景观指数 低等高
度植被		 中等高
度植被		 高等高
度植被		 建筑物
类型 TPD 9.334 6.121 13.796 1.345
TLSI 21.409 25.061 54.887 37.764
TLPI 8.360 3.296 1.074 0.016
TPLAND 0.355 0.275 0.116 0.037
景观尺度 景观指数 海岛
景观 TSHDI 0.732
TSHEI 0.614
TBI 0.523
Tab.2  Index calculation results of different scales
景观类型/指数 维度 PD/TPD LSI/TLSI LPI/TLPI PLAND/TPLAND SHDI/TSHDI SHEI/TSHEI GSC
低等高度植被 二维 5.467 7.342 6.022 0.237 — — 1.877
三维 9.334 21.409 8.360 0.355 — —
中等高度植被 二维 7.870 6.521 3.115 0.178 — — 1.806
三维 6.121 25.061 3.296 0.275 — —
高等高度植被 二维 4.283 8.639 0.840 0.384 — — 2.789
三维 13.796 54.887 1.074 0.116 — —
建筑物 二维 0.247 2.243 0.112 0.123 — — 5.681
三维 1.345 37.764 0.016 0.037 — —
海岛尺度 二维 — — — — 0.568 0.663 —
三维 — — — — 0.732 0.614 —
ESC — 2.788 7.487 0.967 0.911 1.289 0.926 —
Tab.3  Comparison of 2D and 3D index calculation results
Fig.8  Scene model display diagram
Fig.9  Scenario analysis results
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