Ecological structure of a tropical urban forest in Bang 2 Kachao peninsula , Bangkok

Rapid urbanization has changed the structure and function of natural ecosystems, 15 especially the floodplain ecosystems in SE Asia. This paper describes the ecological structure of 16 vegetation stands and the usefulness of satellite images to characterize a disturbed tropical urban 17 forest located in the lower floodplain of the Chao Phraya River, Thailand. Nine representative plots 18 were established in Bang Kachao peninsula in 4 tropical urban forest types: rehabilitation forest, 19 home-garden agroforestry, mangrove and park. The correlation between NDVI and LAI obtained 20 from satellite images and plant structure from field surveys were analyzed. The NDVI had the 21 highest relationship with stand factors for the number of families, number of species, Shannon22 Weiner’s diversity index and total basal area. The LAI had the highest correlation with total basal 23 area, number of canopy layers, stand density and canopy density. Linear regression predicted the 24 correlation between NDVI and LAI with stand factors as show above. The trend in NDVI and LAI 25 reflected the urban forest type, being high in rehabilitation and mangrove forests, moderate in 26 home-gardens and low in parks. Future urban planning of the Bang Kachao peninsula should focus 27 on rehabilitation to increase the biodiversity and complexity of the urban forest. 28


Introduction
Urban green space provides multiple benefits and these can be categorized as ecological, social and economic in attribute.Rapid urbanization has a significant negative impact on urban green spaces and the ecosystem services they provide [1].One important aspect of a city's functioning lies with its urban forest.The structure of urban green space is an important variable that influences urban ecosystem function and affects urban inhabitants.Characterizing the structure of the urban forest requires knowledge of tree density, tree size, tree location and spatial arrangement of forest in urban areas.The management of composition and structure of urban forests are the keys to successfully improving urban green infrastructure and human well-being.Information from tree inventories regarding species performance and native habitat can suggest general guidelines for appropriate species selection and management practices [2].Unlike in more temperate parts of the world, there is a lack of urban forest research in tropical, less urbanized, and less economically developed regions such as in parts of SE Asia [1,3].
Bang Kachao peninsula is a large (ca.1,891 ha) urban green space, located in the lowland of the Chao Phraya watershed in central Thailand, between Bangkok and Samut Prakan provinces.The Chao Phraya river basin is the largest watershed area in Thailand and is an important tropical floodplain area for conservation of freshwater swamp and tropical moist broadleaf forests in the Indo-Malay Ecoregion.An important period in the history of Bang Kachao was between the years 1982 to 1987 when H.M. King Bhumibol Adulyadej viewed the oasis from an airplane and recommended that the green area should be saved as Bangkok's green lung, protecting the citizens of Bangkok from industrial pollution generated to the south in Samut Prakan province.Pressures of urbanization and industrialization from Bangkok Metropolitan and Samut Prakan provinces have affected and changed some of the land use in Bang Kachao peninsular from green space as homegardens and swamps to urban use such as residential, official and industrial areas [4].For several reasons, it would be a tragedy for Bangkok and the entire metropolitan region if this "green lung" were to be sacrificed for more concrete and asphalt.The area not only offers a welcome, nearby retreat for nature-minded weekenders, but also plays an important role in the city's eco-and climate control systems, and could be instrumental to the city government's climate change mitigation and adaptation strategies.This means that both the pressure and the stakes are high.To enhance the functional green space, the Royal Forest Department has been undertaking restoration using enrichment planting on ca.10% of the peninsula.
Whilst there has been some research on plant species [5] and biodiversity [6] in Bang Kachao, the database and in-depth information on the structure and function of green space is still limited.This constrains the future intensive management of urban green space in the Bang Kachao peninsula.
Using representative vegetation plots, the main objective of this research is to determine the usefulness of satellite images to characterize the tropical urban forest.The results will be used to guide the future research and use of remote sensing approaches for urban forest restoration and management in Thailand.

Materials and Methods
The study was undertaken in Bang Kachao peninsula, Phra Pradaeng District, Samut Prakan province, Thailand between 13 o 39'16 "to 13 o 42'5 "N and 100 o 32'36 "to 100 o 35'28 "E.The peninsula is composed of 6 sub-districts: Song Khanong, Bang Krasop, Bang Ko Bua, Bang Kachao, Bang Nam Phueng and Bang Yo.The total area is about 1,891 ha of which around 10 percent is being rehabilitated and managed for conservation by the Royal Forest Department (RFD).The topography is a sediment flood plain, approximately 1 m above mean sea level, surrounded by 15 km length of the Chao Phraya river that flows south into the Gulf of Thailand (Figure 1).The peninsula contains 14 canals which are connected to each other and lead out to the Chao Phraya river.The connection with the ocean creates a unique brackish water wetland in which a total of 675 flora and fauna species occur in swamp forest, mangrove forest and agricultural land classified as home garden [4,6].The inter-annual variation in climate is influenced by the tropical monsoon system where average daily high temperature remains relatively constant over the year, fluctuating within a range of 31-35 o C. Like many tropical cities in the latitudinal belt between 15 and 25 o C, Bang Kachao peninsula has a 6month monsoonal wet season from May through October that ameliorates the heat.November-April is the dry season with the cooler months being November-January.Based on a 7-year (2008-2014) climate data from the nearby Bangna weather station of the Thai Meteorological Department, the average annual rainfall is 1,365 mm over 120 wet days, with the heaviest rainfall generally in September as a result of low pressure systems and typhoons in the South China Sea .The annual mean, maximum, and minimum air temperatures are 28.8, 32.7, and 24.1 o C, respectively [4].(https://earthexplorer.usgs.gov).We used the Landsat 7 ETM + satellite image data to analyze NDVI (Figure 2) by equation (1).The NDVI for each plot was determined by summing the number of pixels.
Based on NDVI, the fractional vegetation cover (FVCNDVI in Equation 2) as used by [7][8] was derived with equation ( 2): where, NDVIs represents the NDVI values for bare soil while NDVIv characterizes the NDVI values at full vegetation cover in respective images.The FVC was calculated to avoid mixed signals in satellite data.For this determination, NDVI was scaled between lowest NDVIs (bare soil) and highest NDVIv (dense vegetation) to calculate fractional vegetation cover (Equation 2).
For this model, NDVIs and NDVIv were selected through histogram evaluation.Subsequently, LAI was calculated through a given logarithmic relation (Equation 3) between respective FVCNDVI and LAI: where, ( ) is the light extinction coefficient for a specified solar zenith angle.The solar zenith angle ( ) depends on terrain geometry, solar declination, solar elevation angle, latitudinal location and day of the year [9].The light extinction coefficient is a measure of attenuation of radiation in the canopy.Nine 50 x 50 m plots were randomly established in Bang Kachao Green Space (Figure 2) in February 2012 as follows: 4 plots in rehabilitation forest, 1 plot in mangrove forest, 2 plots in homegardens and 2 plots in parks (Figure 2).The four plots of rehabilitation forest were plot 1, 2, 3 and 6.
The positions of each plot were obtained by using a global positioning system device (GPS Garmin Oregon 550, Olathe, Kansas, USA).
A census of all living trees with diameter at breast height (DBH) >4.5 cm was conducted.Tree height was measured with a VERTEX Laser VL400, DBH was measured with a diameter tape, canopy diameter was measured with a tape in 2 directions (N-S and E-W axes) for each tree and the number of canopy layers was recorded using profile diagrams [10].All trees were identified to species by collecting leaf specimens for comparison with standard specimens in the herbarium at the Department of National Parks, Wildlife and Plant Conservation.The nomenclature followed of the Flora of Thailand [11].Collected data were used to calculate stand structural characteristics of the representative Bang Kachao Green Space.
The following were calculated for each plot: • For stem density (SD), the number of trees (N) per unit are (N/ha) was counted; • The basal area (BA) as (m 2 /ha), defined as the ratio of the cross-section area of all trees in the sampling plot to the plot ground area; and • Canopy Cover (CC), define as a typically, the value used in diameter crown width modeling efforts has been the arithmetic mean of two (or occasionally more) crown width measurements [12][13].This value has no mathematically intrinsic relationship, however, to crowns that are not round.If the true shape of a crown with differing width measurements is assumed to be an ellipse, Canopy Cover (CC) is calculated using the equation (4).
where, CC is projected crown area, X and Y are the major and minor radii of the ellipse.
• Canopy density (CD): the CD refers to the proportion of an area in the field/ground that is covered by the crown of trees and is expressed in percentage of the total area.This research calculated CD from a profile diagram of each 50 x50 m plot using QGIS software to reference scale with Cartesian coordinates.
• Importance value index (IVI) for each plant species in the plot was calculated by summing up the relative percentages of basal area, density, and frequency [14].
• Shannon-Wiener index (H') was calculated as a measure of tree species diversity in each forest community [15].
Matrix correlation was used to analyze the correlation between plant factors from satellite data (NDVI and LAI) and plant factors obtained from ground survey for the nine plots.Where the correlation was significant, linear regression analysis of the relation between the dependent variable Y and the explanatory variables Xi was used as in equation ( 5): where, is the intercept, the regression coefficient of the ith independent variable, n the total number of independent variables, and a random error term that represents the unexplained variation in the dependant variable.The coefficients are typically estimated with the least squares approach, in which the error term e is minimized.relative abundance and evenness of the biodiversity across the plots (Table 1).The index was very low (0.43) for plot 9 reflecting the dominance of one species, the coconut palm.Indices for all the other plots lay in the range 1.39 to 2.58.Plot 6 had the highest H index.

NDVI and LAI
The NDVI in the rehabilitation forest (plots 1, 2, 3 and 6) ranged from 0.432 to 0.481 and the mangrove plot was 0.436 (Table 3).However, the NDVI of the home-garden plots were different from each other, being 0.170 and 0.422.The lowest NDVI occurred in the park plots.Similarly, the LAI was highest in the rehabilitation and mangrove plots but also in home-garden plot 4. The LAI of the park plots and home-garden plot 8 were lower (Table 3).

Relationship between NDVI and stand structure
The NDVI was high correlated with the number of families, number of species, Shannon-Weiner's diversity index and total basal area (p<0.05).However, NDVI was not correlated with stand density, DBH, height, canopy density, mean crown cover area per tree, and number of canopy layers.
Linear regression was used to analyze all significant relationships between NDVI and stand factors.
The measured stand structural factors were used as the dependent variable, and the NDVI factor from the remote sensing was used as the independent variable (Figure 4).The best linear equation between NDVI and plant factors was the number of families (R 2 = 0.634) and total basal area (R 2 = 0.623).

Relationship between LAI and stand structure
The LAI was highly correlated with total basal area (p<0.01),followed by stand density, canopy density and number of canopy layers (p<0.05)(Figure 5).The best equation between LAI and plant factors was total basal area (R 2 = 0.78), followed by the number of canopy layers (R 2 = 0.61), stand density (R 2 = 0.55) and canopy density (R 2 = 0.51).

Discussion
The Bang Kachao peninsula contains a range of tropical urban forest types in an urban oasis strongly affected by land use from local residents as well as by reforestation efforts in recent decades.
Regarding biodiversity, the research looked only at trees but included the coconut palm because of its prominence and stature in the area.Overall, 52 tree species in 17 families were assessed across the 9 plots and the number of species ranged from 2 to 26 per plot.Tree biodiversity varied with NDVI, with the most biodiversity in the rehabilitation and mangrove forest plots with high NDVI.
Biodiversity was moderate in the home-garden agroforestry plots and low in the park plots.
Comparison of the diversity of trees between Bang Kachao Green Space in this research with Bangkok, using [16], found that Bang Kachao (52 species) had more tree species than Bangkok (48 species).However, the number of tree species measured in the nine stands in this research was lower than the 179 tree species reported previously [5] in Bang Kachao Green Space.Therefore, over half the diversity of trees was not represented in the nine sites that were studied, indicating the need for further investigation on microclimate and forest composition.a better understanding of the rate of change, positive and negative, for management purposes into the future.

Figure 1 .
Figure 1.Satellite LANDSAT 7 false color image of Bangkok and Chaopraya River showing location of the Bang Kachao Green Space (BKGS), 25 April 2012.

Figure 2 .
Figure 2. NDVI classification image.Boundaries of the 6 sub-districts are shown.The numbers are the locations of the 9 research plots.

PreprintsFigure 3 .
Figure 3. Appearance of vegetation from the ground of study plots in Bang Kachao Green Space.Plot descriptors are given in Table 1.Plots 1 (a), 2 (b), 3 (c) and 6 (f) were rehabilitation forest, plots 4 (d) and 8 (h) were home-garden agroforestry, plot 5 (e) was mangrove forest, plot 7 (g) was in Chalerm Phra Kiat the King Bhumibhol 80 Phansa Park and plot 9 (i) was in Sri Nakhon Khuean Khan Park and Botanical Garden.

Figure 4 .
Figure 4. Linear regression between NDVI and number of families, number of species, total basal area and Shannon-Wiener's index.

Figure 5 .
Figure 5. Linear regression between LAI and stand density, total basal area, canopy density and number of canopy layers.

[ 17 ]
inventoried tree species in Bangkok at Kasetsart University, in suburban community areas in Phatum Thani province and in agricultural areas in Nakhon Phathom province located in the lower central plain of the Chao Phraya River.They recorded 395 species of trees within 60 families.Furthermore,[18] observed home-garden agroforestry in Nonthaburi province (suburban Bangkok) and found 58 species of trees.

Table 1 .
Stand characteristics for Bang Kachao Green Space study plots.The total stem basal area ranged from 22.8 m 2 /ha in plot 1 to 2.3 m 2 /ha in plot 7. The stem basal area ranged from 10.1 to 22.8 m 2 /ha in the rehabilitation forest, was 13.2 m 2 /ha in the mangrove forest plot, 12.5 and 9.6 m 2 / ha in the home-garden agroforestry plots and only 2.3 and 5.2 m 2 /ha in the park plots.The canopy density of crown cover varied across plots and urban forest types.The value of canopy density for the rehabilitation and mangrove forest plots ranged from 38.2 to 91.8% with the highest canopy densities in plots 1 and 5.The home-garden agroforestry plots had intermediate canopy density and the lowest density was in the park plots (Table1).Also, the canopy layers varied with urban forest types and plots, ranging from 1 to 4 canopy layers.There were multiple canopy layers in the rehabilitation and mangrove forest and the least number of layers in park plots.Over 80% of trees were less than 10 m in height.Trees >15 m in height were mostly Cassia siamea, Cocos nucifera, Ficus spp., Sonnerratia caseolaris, Streblus asper and Terminalia catappa.The tallest trees were Sonneratia caseolaris and Ficus sp. with 25.0 and 22.5 m in maximum height, respectively.The IVI of the top-five species in each plot suggested the dominant species as show in Table2.The dominant species of rehabilitation forest plot 1 were Cocos nucifera, Streblus asper and Cassia Stand density, DBH, total stem basal area and canopy density varied with urban forest types and plots.Stand density ranged from 104 to 1,268 trees/ha with an average for the nine plots of 774 trees/ha.Plot density was high in the rehabilitation forest (716-1,268 trees/ha), medium in the homegarden and mangrove forest (820-980 trees/ha) and low in the park (104-360 trees/ha) (Table1).The DBH ranged from a mean/plot of 8.2 to 24.7 cm.However, more than 50% of trees had diameters <10 cm (data not shown).Trees with diameters >40 cm in diameter were mostly Antidesma ghaesembilla, Cocos nucifera, Erythrina fusca, Peltophorum dasyrachis and Sonneratia caseolaris.siamea; for plot 2 Cocos nucifera, Cerbera odollam and Hibiscus tiliaceus; for plot 3 Cerbera odollam, Streblus asper and Erythrina fusca; and for plot 6 Cocos nucifera, Cerbera odollam and Pterocarpus indicus.In the mangrove forest (plot 5), the dominant species were Cerbera odollam, Sonneratia caseolaris and Hibiscus tiliaceus.The dominant species of the home-garden agroforestry plot 4 were Musa spp., Cocos nucifera Preprints (www.

Table 2 .
Importance value index for top-five main species in each plot.

Table 3 .
NDVI and LAI values for Bang Kachao Green Space study plots.