Ke-Sheng Cheng, Wei-Chun Hung

Comparing landcover patterns in Tokyo, Kyoto, and Taipei using ALOS multispectral images
Ke-Sheng Cheng, Wei-Chun Hung Department of Bioenvironmental Systems Engineering National Taiwan University Yen-Ching Chen Department of Landscape Architecture Fu-Jen Catholic University 5/28/2018 2011 ACRS Conference, Taipei

2011 ACRS Conference, Taipei
Introduction Urbanization is a process of transforming natural landscapes to built environments which typically contain large amounts of impervious surfaces. As the process of urbanization evolves, landcover pattern, namely the types of landcover and their proportions, present in a city and its proximity may also change over time. 5/28/2018 2011 ACRS Conference, Taipei

Many studies have found that changes in landcover pattern can have significant impacts on urban ecosystems. Not only are landcover changes the most apparent effect of urbanization, but also the driving force of many ecological consequences of urbanization. Thus, characterizing the landcover pattern in a region is crucial for assessing the effects of urbanization. 5/28/2018 2011 ACRS Conference, Taipei

This study aims to Explore the feasibility of characterizing landcover patterns using landscape metrics and other indices derived from remote sensing images and, Compare landcover patterns in cities of different degrees of urbanization. Specifically, we seek to develop an index which can provide a quantitative representation of the degree of urbanization for different cities. 5/28/2018 2011 ACRS Conference, Taipei

Study Areas and Data Three regions (Tokyo and Kyoto in Japan and Taipei in Taiwan) of different degrees of urbanization were chosen for this study. A subregion centered at the Tokyo Metropolis Government Kyoto city and its vicinity, and Taipei city and its vicinity. 5/28/2018 2011 ACRS Conference, Taipei

Kyoto study area Tokyo study area The Tokyo metropolis is composed of 23 more urbanized special zones in the east and also a huge suburban area including several local cities in the west. Our Tokyo study area only encompasses some of the specialized zones in the east. Taipei study area Each study area has a spatial coverage of 15km x 15km. 5/28/2018 2011 ACRS Conference, Taipei

ALOS satellite multispectral images of these studies areas were collected. These images were acquired by the AVNIR2 sensor onboard the ALOS satellite with a spatial resolution of 10 m x 10 m. AVNIR2 sensor acquires images in four spectral bands blue (B, 0.42 – 0.50 m) green (G, 0.52 – 0.60 m) red (R, 0.61 – 0.69 m) near infrared (IR, 0.76 – 0.89 m). 5/28/2018 2011 ACRS Conference, Taipei

Landuse/landcover classification
Priori to landcover pattern analysis, landuse/landcover (LULC) classification needs to be conducted for each study area. In this study an indicator kriging approach for LULC classification was adopted. The indicator kriging (IK) classification is a nonparametric supervised classification approach that can achieve high classification accuracy for training data set. 5/28/2018 2011 ACRS Conference, Taipei

Indicator kriging for LULC classification
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Two-dimensional three-class feature space
Indicator variogram Class 1 Class 2 Class 3 11/16/2010

Four landcover classes Woods (land surface covered by forest, trees, and shrubs) grass/crop (areas covered by grass, paddy field, and vegetable crops) built-up (buildings, paved surface, and bare soil) water bodies 5/28/2018 2011 ACRS Conference, Taipei

Confusion matrices (Training pixels)
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Area percentages of individual landcover types
Tokyo study area has a dominant area percentage of built-up coverage, whereas Kyoto has a more balanced built-up and vegetation (including woods and grass/crop) coverage. Comparing to Tokyo, Taipei has a less dominant percentage of built-up coverage and a significantly higher percentage of vegetation coverage. 5/28/2018 2011 ACRS Conference, Taipei

Tokyo study area Landcover images of the three study areas. Kyoto study area Taipei study area Water Built-up Woods Grass/Crop 5/28/2018 2011 ACRS Conference, Taipei

Landcover pattern analysis
Landscape metrics Landcover patterns in coverage-ratio space NDVI-based landcover pattern analysis 5/28/2018 2011 ACRS Conference, Taipei

(1) Landcover pattern analysis using landscape metrics
Landcover pattern is an integrated reflection of the available natural resources, dynamic natural processes, and anthropogenic activities in a region. Generally speaking, it can be characterized by three key aspects number of different landcover types, relative proportions of landcover types, and spatial distribution of these landcover types. 5/28/2018 2011 ACRS Conference, Taipei

In this study landcover pattern analysis is achieved by assessing two aspects landcover heterogeneity within individual local cells (1 km x 1 km or 10,000 pixels), and variation of such landcover heterogeneity over the whole study area. Landcover heterogeneity within a cell is expressed by the Shannon diversity index (SHDI) defined as 5/28/2018 2011 ACRS Conference, Taipei

SHDI values are influenced by richness and evenness of landcover types. Richness (total number of landcover types present in a cell) and evenness (relative areal proportion among different landcover types) respectively represent the compositional and structural components of diversity. SHDI equals zero when a cell contains only one landcover type (i.e., no diversity). A cell with a dominant landcover type has a very low or near zero SHDI. SHDI increases as the number of different landcover types increases and/or the area percentages among landcover types becomes more equitable. 5/28/2018 2011 ACRS Conference, Taipei

There are a number of cells within each study area and each cell corresponds to an SHDI value. Thus, variation of cell-level landcover heterogeneity over the study area is characterized by the empirical cumulative distribution function (ECDF) of SHDI. Using SHDI at cell scale and ECDF of SHDI, the three key aspects of landcover pattern can be investigated. 5/28/2018 2011 ACRS Conference, Taipei

Spatial variation of cell-level SHDI in different study areas

ECDF of cell-level SHDI

Cell-level SHDI values of the Tokyo study area are more homogeneous in space. It indicates that both the landcover type richness and evenness are low in most of the Tokyo study area. The Tokyo study area is highly urbanized and built-up landcover accounts for 86 % of its spatial coverage. Built-up is the single dominant landcover type in almost all cells. By contrast, Kyoto and Taipei study areas have more significant spatial variation of cell-level SHDI. 5/28/2018 2011 ACRS Conference, Taipei

Landcover patterns of Kyoto and Taipei show more diversified landcover distribution, i.e. in addition to cells for which woods and built-up are dominant landcover types (with very low SHDI), there are also significant amount of high-SHDI cells which have mixed and non-dominant landcover types. 5/28/2018 2011 ACRS Conference, Taipei

(2) Landcover patterns in coverage-ratio space
Each cell is associated with four area percentages (i.e. coverage ratios) corresponding to landcover types of woods, crop/grass, built-up, and water bodies. 5/28/2018 2011 ACRS Conference, Taipei

Neglecting the coverage ratio of water bodies, all cells should fall on a plane (hereafter referred to as the coverage-ratio plane) defined by three vertices (points A, B, and C) of dominant landcover types. 5/28/2018 2011 ACRS Conference, Taipei

Urbanization can be viewed as a process of cells on the coverage-ratio plane merging from points B (woods dominant) and C (crop/grass dominant) towards the confluence point A (built-up dominant). The more concentrated these cells near point A, the higher degree of urbanization the city is. 5/28/2018 2011 ACRS Conference, Taipei

Scatter plot of cells in a coverage-ratio space

The Tokyo study area is most urbanized with very low coverage ratio of woods or grass/crop landcover type. The Taipei study area has most of its cells concentrated near built-dominant point A, although there are also many cells falling along a curved path near the AB line. Such pattern is a reflection of the fact that the Taipei study area encompasses mountainous regions at its northeastern and southeastern corners. For the Kyoto study area, cells are more widely spread over the coverage-ratio plane, indicating a good mixture of different landcover types. It also indicates that the Kyoto study area is least urbanized among the three study areas. 5/28/2018 2011 ACRS Conference, Taipei

(3) NDVI-based landcover pattern analysis
Cell-average NDVI ( ) was calculated for individual cells of the three study areas. 5/28/2018 2011 ACRS Conference, Taipei

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Relationship between cell-average NDVI and cell-level SHDI

Criteria for delineation of areas with different dominant landcover types Implementation of such method of dominant-landcover-areas delineation does not require an a priori LULC classification, and thus is particularly useful when good training data for LULC classification are not available. 5/28/2018 2011 ACRS Conference, Taipei

Areas of different dominant landcover types in the three study areas delineated using cell-average NDVI. 5/28/2018 2011 ACRS Conference, Taipei

Assessing the degree of urbanization using an urbanization index
Although the spatial variation and ECDF of cell-level SHDI can reveal differences in landcover patterns of different study areas, they do not provide an explicit and direct measurement of urbanization. Similarly, the cell distribution in the coverage-ratio space can only serve as a visually and qualitative indicator of the degree of urbanization. An urbanization index (UI) which not only reflects the characteristics of urbanization, but also provides a comparable scale is worth pursuing. 5/28/2018 2011 ACRS Conference, Taipei

The most apparent effect of urbanization is the increase of built-up landcover. As the process of urbanization continues, the built-up dominant areas expand and the coverage ratio of built-up landcover type increases. Modern urban planning and zoning may also require establishing urban forestry or city parks and planting of road trees to alleviate the adverse effect of urbanization. Presence of trees, parks, and forestry in a neighborhood can be reflected by higher cell-average NDVI values. 5/28/2018 2011 ACRS Conference, Taipei

We propose to develop a cell-specific urbanization index by integrating the coverage-ratio of built-up landcover type and the cell-average NDVI: Theoretically, the value of cell-specific urbanization index can vary between 0 and 2. In reality, most values fall in between 0 and 1, and higher values indicate more significant effect of urbanization. 5/28/2018 2011 ACRS Conference, Taipei

Relationship between cell-specific urbanization index (UIcell) and coverage-ratio of built-up landcover type (pb). 5/28/2018 2011 ACRS Conference, Taipei

For an overall comparison of the degrees of urbanization of the three study areas, average urbanization index for each study area was calculated. Value of for the Tokyo, Kyoto, and Taipei study areas are 0.91, 0.55, and 0.72, respectively. These values are consistent with the qualitative evaluation of the degree of urbanization as described earlier. 5/28/2018 2011 ACRS Conference, Taipei

Gradient analysis of landscape spatial pattern using cell-specific urbanization index 5/28/2018 2011 ACRS Conference, Taipei

Two-dimensional gradient analysis of the cell-specific urbanization index of the Tokyo, Kyoto, and Taipei study areas. 5/28/2018 2011 ACRS Conference, Taipei

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Conclusions Both the landcover type richness and evenness are low in most of the Tokyo study area. The Tokyo study area is highly urbanized and built-up is the single dominant landcover type in almost all cells. Landcover patterns of the Kyoto and Taipei study areas show more diversified landcover distribution. In addition to cells for which woods and built-up are dominant landcover types, there are also significant amount of cells with mixed and non-dominant landcover types. 5/28/2018 2011 ACRS Conference, Taipei

Comparing to the Tokyo and Taipei study areas, Kyoto is least urbanized and enjoys a good mixture of different landcover types, based on the analysis of landcover pattern in coverage-ratio space. Area-average urbanization index for the Tokyo, Kyoto, and Taipei study areas are 0.91, 0.55, and 0.72, respectively. Such results are consistent with the results of qualitative evaluation using different landscape metrics. The cell-specific urbanization index can also be used for two-dimensional gradient analyses to show the spatial variation of the degree of urbanization within each study area. 5/28/2018 2011 ACRS Conference, Taipei

Thanks for your attention! 5/28/2018 2011 ACRS Conference, Taipei

Ke-Sheng Cheng, Wei-Chun Hung

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