25 JUNI 2018 - AMSTERDAM

ANALYSIS OF SUBSIDENCE IN CITY PARKS IN AMSTERDAM A CASE STUDY FOR FOUR DIFFERENT PARKS

BENTHE TIMMERMANS - 11037016 UNIVERSITY OF AMSTERDAM Dr. H. Seijmonsbergen WORDS: 5147 Benthe Timmermans – Bachelor Thesis, 2018

Abstract

City parks are important green areas for cities. They provide cooler microclimates, recreation areas, improve biodiversity and buffer surface runoff. However, the parks in Amsterdam experience long- term subsidence due to the natural consolidation property of peat and clay. Subsidence leads to runoff and causes higher groundwater tables. This may negatively affect vegetation and water storage capacity. The aim of this research is to obtain insight in the spatial distribution of subsidence in four city parks: the Vondelpark, Flevopark, Oosterpark and Sarphatipark. Subsidence will be related to both lithology and trees, because recent studies have proven they both influence subsidence. To provide a subsidence map, elevation maps of the Netherlands will be used (Algemeen Hoogtebestand Nederland). The subsidence statistics that are obtained are compared with the geological map of Amsterdam and tree distribution. The research concludes that all the four parks show differential subsidence. The Sarphatipark has the highest average of subsidence and the lowest minimum hotspot of subsidence. Whereas, the Flevopark shows different spatial distribution, the subsidence is on average above zero. It is concluded that patterns in subsidence cannot directly be related to lithology for the four parks. Furthermore, there is no significant relation with tree heights. Although, natural subsidence will continue in city parks in Amsterdam, variation within parks exists, and will require further research to cover a full explanation.

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Benthe Timmermans – Bachelor Thesis, 2018

Content

Content ...... 2

List of abbreviations ...... 3

1. Introduction ...... 4 1.1 Background ...... 4 1.2 Research aim & questions ...... 5

2. Methods and Data ...... 7 2.1 Study area ...... 7 2.2 Data ...... 7 2.3 Methods ...... 8 2.3.1 AHN & ZEB-REVO data ...... 8 2.3.2 GeoTOP data ...... 8 2.3.3 Trees file ...... 9

3. Results ...... 10 3.1 Height change map ...... 10 3.2 Lithology of the parks ...... 12 3.3 Tree correlation ...... 13 3.3.1 Tree height ...... 13 3.3.2. Tree species ...... 13

4. Discussion ...... 14 4.1 Interpretation of the results ...... 14 4.2 Methodological discussion ...... 15 4.3 Further research ...... 15

5. Conclusion ...... 17

Acknowledgements ...... 18

Literature list ...... 19

Appendices ...... 22 Appendix A: Height change map of different parks ...... 22 Appendix B: ZEB-REVO data ...... 26 Appendix C: Lithology occurrence ...... 27 Appendix D: Tree height ...... 28 Appendix E: Tree species ...... 29 Appendix F: Matlab Code ...... 30

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Benthe Timmermans – Bachelor Thesis, 2018

List of abbreviations

AHN Algemeen Hoogtebestand Nederland

DEM Digital Elevation Model

DTM Digital Terrain Model

GeoTOP Geologisch toplagen

GIS Geographical Information System

IDW Inverse Distance Weighting

LiDAR Light detection and ranging

NaN Not a Number

NAP Normaal Amsterdams Peil

RD Rijksdriehoeks

STD Standard Deviation

ZEB-REVO GeoSLAM ZEB-REVO RT (hand-held LiDAR system)

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Benthe Timmermans – Bachelor Thesis, 2018

1. Introduction 1.1 Background Nowadays, more than 80% of the population in northern Europe is living in urban areas, and this number is expected to be around 90% in 2030 (Antrop, 2004). This urbanization is an issue, because cities may experience an urban heat island, where air temperature is higher than in rural areas (Valsson & Bharat, 2009; Mentens et al., 2006). Furthermore, one of the major problems of urbanization is that it interrupts the natural hydrological cycle, since urban areas replace vegetation (Mentens et al., 2006; Bulkeley, 2013). Vegetation has important functions such as better infiltration, water storage functions, evaporative cooling, shading and rainfall interception and can therefore partly absorb problems that arise with urbanisation (Gill, et al., 2007; Whitford et al., 2001). Vegetated areas such as parks can function as water sponges, since they reduce surface water runoff (Gill et al, 2007; Rainproof, n.d.; Bolund & Hunhammer, 1999). As an illustration, vegetated areas have only 10- 15% runoff whereas urban areas can experience runoff to 60% of the precipitation (Bolund & Hunhammer, 1999). This reduction of runoff is important, since the Netherlands expects an increase of 10-15% in heavy precipitation due to climate change (Frich et al., 2002; Houghton, 2009). Moreover, parks provide cooler microclimates which counter the urban heat island effect (Zhang et al., 2012). Lastly, parks are important for biodiversity of a city and provide recreation areas (Savard, et al., 2000, Kurpershoek & Ligtelijn, 2001). However, green urban spaces can experience subsidence that results in different problems. Amsterdam is an area where this subsidence is occurring, which is caused by the fact that Amsterdam is located in a peaty area (Van Trik & Ahrens, n.d.). Peat has a property to lower over time due to secondary consolidation (Barden, 1968; Gans, 2011). Therefore, all parts in Amsterdam are raised with sand or supported with poles, however this raising is not executed for all urban parks (Gans, 2011; Grontmij, 2011). Subsequently, many parks inside the ring road of Amsterdam lie around 2 meters lower than surrounding areas (Gans, 2011) (fig. 1 & fig, 2). Therefore, the water table in these parks will rise, since water of the surrounding areas will flow to the parks. In the long run, this causes different problems such as dying of vegetation and lower water storage capacity (Dumuzere et al., 2014; Kos & Grobbe, 1995). In addition, this subsidence can lead to nuisance in the surrounding areas such as subsidence of houses (Kos & Grobbe, 1995). However, it is unclear how subsidence changed over the years in Amsterdam and whether this subsidence has accelerated.

Figure 1. Height of a part of Amsterdam relative to Normaal Amsterdams Peil (NAP). Derived from the Actual Height of the Netherlands. The three parks that are visualized lie below the surrounding areas. - 4 -

Benthe Timmermans – Bachelor Thesis, 2018

In addition, water management plays an important role in the prevention of subsidence (Bronswijk, 1988; Wösten & Ritzema, 2001). The method of drainage in parks in Amsterdam is very relevant, since the volume of peat and clay is sensitive to changes in water table (Gans, 2011; Grontmij, 2011). The water table can be influenced by trees, who use water for their growth (Biddle, 2001; Freeman, Littlejohn & Driscoll, 1994). Subsequently, the water table lowers and may trigger peat shrinkage and surface subsidence (Prince & Schlotzhauer, 1999; Whittington & Price, 2006). Some researchers state that particular trees are more responsible for subsidence, e.g. willow trees and oak trees use more water than others (Crilly, 2001; Thom, 2013; Bakker et al., 1995). However, other researchers claim that tree height plays a more important role in inducing subsidence (Williams, 2006). Assessment of the role of trees in subsidence of city parks has not been the focus of research before.

Figure 2. Two cross-sections of Amsterdam with both Vondelpark and Flevopark (up) and the Oosterpark (down) showed. The lower location of all parks relative to its surroundings is clearly identified (Gans, 2011).

1.2 Research aim & questions The aim of this paper is to construct a subsidence map of four different parks in Amsterdam and to relate subsidence to the lithology of the substratum and the presence of trees. The paper will focus on four parks as case study. Mapping of subsidence has not been focussed on specific parks in urban areas. The newly prepared subsidence map could give better insight in the spatial distribution of subsidence within and between parks, which may be important for the municipality of Amsterdam. The municipality could adapt their current park management based on the results provided by this research. In addition, the methodology could be used for other cities to assess the subsidence of parks. To reach this aim, this research will focus on two questions: (i) What is the spatial variability of subsidence between and within different parks in Amsterdam and (ii) can subsidence be related to - 5 -

Benthe Timmermans – Bachelor Thesis, 2018 lithology and/or trees? This research only addresses natural causes of subsidence and disregards human induced subsidence. This question will be answered by answering different sub questions. The first sub question is a technical question and will indicate the height change over the years by answering the following sub question: (iii) What is the spatial variability of subsidence between and within different parks in Amsterdam between 2010 and 2014 and how accurate is this assessment? This sub question will be answered by using the different AHN versions which were made in 2010 and 2014 and the accuracy of the AHN’s will be assessed by using a LiDAR hand scanner. The methods of this sub question will be explained in the methods and data section (chapter 3). The second sub question will focus on to achieve more insight in the geological ground of the different parks. As stated before, peat has the property to be more prone to subsidence than other geological units. Every geological unit has different properties in water retention and permeability (Poland, 1984; Walczak, Roydan & Witkowska-Walczak, 2002). For example, sand almost does not experience subsidence, whereas clay and peat show secondary consolation (Poland, 1984). The sub question subsequently will be: (iv) What is the subsurface vulnerability of lithology to subsidence of different parks in Amsterdam? To answer this sub question, a tool made by ‘DINOloket’ (https://www.dinoloket.nl/ondergrondmodellen) will be utilized, which will be explained in the methods and data section (chapter 3). The last sub question will try to explain the subsidence of different parks by comparing the height change with the trees in the park. Both tree species and tree height have shown relation with subsidence. This relation will be assessed by answering the following question: (v) What is the role of height and species of trees on subsidence in parks in Amsterdam? This will be answered by performing different statistical tests on the data. The answers of all these three sub questions (iii, iv and v) will provide an answer to what extent the different parks are facing subsidence. The hypothesis is that parks are facing subsidence, since peat has induced subsidence in other parts of the Netherlands (Kooi, 2000; Nieuwenhuis & Schokking, 1997). In addition, trees have shown influence with subsidence in different studies and the parks in Amsterdam accommodate many trees (Kurpershoek & Ligtelijn, 2001). Therefore, a correlation between both lithology as trees and subsidence is expected to be found.

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Benthe Timmermans – Bachelor Thesis, 2018

2. Methods and Data 2.1 Study area The first park that is evaluated on the subsidence is the Oosterpark (table 1). The Oosterpark is vulnerable to subsidence, because of its high water table and high soil density as acknowledged by different researchers (Akker, 2011; Groenlinks, 2013; Kurpershoek & Ligtelijn, 2001). Next, the Vondelpark has shown signs of subsidence and elevation of ground water (Stam, 2010; Municipality of Amsterdam, n.d.,). This subsidence is partly resolved but the park is still interesting to discuss in order to clarify the change these renovations made. In addition, the Vondelpark is the oldest park of the four (table 1), hence it has had the most time to lower. The next park that is looked into is the Sarphatipark, which is the smallest park of the four (table 1), but has most visitors relative to its size (Municipality of Amsterdam, 2015.) This park is multiple times per year too wet, which can be addressed to the poor water management (Municipality of Amsterdam, 2016). Furthermore, this park is built on low quality material (Municipality of Amsterdam, 2015). Lastly, the Flevopark will be analysed and also the youngest park (table 1). This park has not shown significant subsidence, because it was raised in 1921 with dredger sludge obtained by constructing the Coentunnel (ibid). Therefore, it could be interesting as counterpart to the other parks to see differences.

Table 1. The four parks that are evaluated in this research, data obtained from Kurpershoek & Ligtelijn (2001) Park Size Year of construction Oosterpark 14,4 ha 1891 Vondelpark 48 ha 1865 Sarphatipark 4 ha 1885 Flevopark 23 ha 1928

2.2 Data For this research, various datasets are used (table 2). The first dataset that is important is the Algemeen Hoogte Nederland (AHN). This is a height map made by the government with the help of LiDAR technique (Van der Velden, 2010). The time between laser sending and receiving is measured and a dataset of points with the point heights is made. This delivers a grid where buildings etc. are filtered out (Van der Velden, 2010). The height map is available online, which consists of three publications of the Netherlands that are made in different time periods: AHN1, AHN2 and AHN3 (table 2). The point density and therefore accuracy improved over the years and subsequently all AHN’s have different resolutions and detail. AHN1 has no filtering of buildings and trees, which makes AHN1 not usable for this research, since a terrain height is needed (Van der Zon, 2013). The other two AHN’s (AHN2 and AHN3) are more accurate and have a filtering of buildings conducted (Van der Zon, 2013; Bregt et al., 2016). The difference between these datasets is that AHN3 is made more recently than AHN2 (table 2), which makes it even more accurate. Table 2. Overview of the metadata and its sources

Sub- Description Data Coordinate Smallest scale Publication Source index type system date AHN2 Recent height model of Raster Amersfoort/ 0.5 x 0.5 m 2010 PDOK Netherlands RD New AHN3 Most recent height Raster Amersfoort/ 0.5 x 0.5 m 2014 PDOK model of Netherlands RD New ZEB- Detailed map of height Point Relative GPS - 2018 Self-made REVO in 2018 cloud system Geo Detailed map of Raster Amersfoort/ 1:50.000 2009-2011 DINOloket TOP underground RD New (100 x 100 m) Tree File with all trees in Points Amersfoort/ - 2018 (updated Municipality file Amsterdam RD New every year) of Amsterdam

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Benthe Timmermans – Bachelor Thesis, 2018

In addition to the AHN files a map of the subsurface (GeoTOP) distributed via the ‘DINOloket’ has been used (table 2). This data file is made by collecting different drillings derived from the DINO database (DINOloket, n.d.). This data file shows the subsurface to a maximum of 50 meters below NAP (ibid). For this research only 20 meters depth is used, since it is assumed that the clay and peat in Amsterdam are not located below 20 meters (Roekel, 2013). This subsurface map shows the different layers in the substratum such as the occurrence of peat and clay. (Stafleu & Voxels, 2015). The raster size of the GeoTOP layer is 100x100m (table 2). The tree point data file of Amsterdam consists of all trees, annotated with their location, height and species information (maps.amsterdam.nl, 2018). In addition to the existing maps, a map was made by the using the GeoSLAM ZEB-REVO RT (ZEB-REVO) 3D laser scanning system. This scanner was operated in a small area, since it records approximately 43200 points per second and has a range of 10 meters (Dewez et al., 2017). The data that is collected by this scanner needs to be calibrated, which will be explained in the following section. After the adjusting of data, the ZEB-RVO is used to check the accuracy of the AHN’s, since the ZEB- REVO gives even more accurate and updated data than AHN3 (table 2).

2.3 Methods For this research, all metadata is imported in ArcGIS, which is a Geographical Information System (GIS). However, each dataset needs to be pre-processed 2.3.1 AHN & ZEB-REVO data In order to answer the first sub question, the data of AHN needs to be adjusted. The dataset is available for the whole Netherlands, but for this research the data is clipped into the four parks that this research focusses on. To see height change over the four years, the two different AHN’s are subtracted with the ArcGIS minus tool. Subsequently, the height change map between 2010 and 2014 was obtained, which can be seen in the results. The ZEB-REVO data was obtained in a small part in the Oosterpark (figure B2 in appendix B), since this data was purely used for an accuracy check. To determine the area where the ZEB-REVO needed to be made, the height change map of 2010-2014, that was obtained by subtracting AHN3 by AHN3, was used. The zone (highlighted in figure 5) where the Oosterpark showed the most subsidence was measured with the ZEB-REVO. This data which is obtained with the ZEB-REVO comes in a las file (figure B1 in appendix B). However, this data needs to be converted into a digital terrain model (DTM) which is done by using different tools in LAStools (figure 3). To create the DTM, the settings proposed by Haacke (2018) were used (table B1 in appendix B). In the end, the data was made into a DTM of 0,5 x 0,5 meters to conform to the AHN’s raster size.

Figure 3. The workflow for the adjusting of the ZEB-REVO data

The Zeb-REVO data only has relative height and no absolute height. Therefore, it is needed to correlate the Zeb-REVO to the most recent AHN. This is done by connecting the ZEB-REVO data to the height of the road of AHN3 (highlighted in figure B2 in appendix B), since it is assumed that the road height did not change that much since 2014. Thereafter, the AHN3 was subtracted with the ZEB-REVO data with the minus tool in ArcGIS. This subtraction gave a height change map from 2014-2018 for that part of the Oosterpark. To get statistics on the height change between 2010-2014 of the different parks, zonal statistics is applied, which provides statistics such as mean and minimum of the different parks.

2.3.2 GeoTOP data The GeoTOP data does not need much adjustment, since it comes in a raster file. However, the GeoTOP data needs to be clipped to the different parks size. The GeoTOP data consists of a layer file

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Benthe Timmermans – Bachelor Thesis, 2018 with a different layer for every meter’s depth, which means that there are twenty different files. To visualize this, the data is imported into ArcScene in order to see the layers in depth. Thereafter, the data is added to excel to determine occurrence of all lithology.

2.3.3 Trees file The tree file was obtained by Robert van Eeden which works at the department of public space at the municipality of Amsterdam. This data was send in four different excel files, each file covering one park. However, this data was in Rijksdriehoek (RD) coordinates and was changed with ArcGIS into WGS coordinates. To analyse a possible correlation between both tree species / tree height and subsidence, a buffer around the trees was made. The buffer was made around trees, since different studies discuss that the influence of trees is not only corresponding with the specific place the tree was planted, but that trees have radial zones of influence (Williams, 2006, Bakker et al., 1995). About the radius of influence of trees on subsidence is no consensus, some articles state that this radius is equal to the height of the tree (Williams, 2006), whereas others affirm that this is specific per tree species (García, 2014). However, for this research 5 different buffers are used: 1 meter, 5 meters, 10 meters, 15 meters and one variable buffer equal to the height of the specific tree. Those different buffers were chosen, to observe the results of different radiuses on tree / subsidence influence. Thereafter, the mean subsidence of every buffer zone was calculated (figure 4) and added to the existing tree file. Thereafter, the statistics were calculated with MATLAB.

Figure 4. The workflow used for the tree data

For the correlation between tree species and subsidence, the data was adjusted by combining different tree species into one tree species (Appendix E). For example, the white willow was changed into the willow. All the species were added into 22 different subgroups (table E1 in appendix E). Thereafter, the data was put into MATLAB (Appendix F) in order to perform an ANOVA-test on the tree species and subsidence. The ANOVA-test was used to check differences in means in subsidence for different species / heights.

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Benthe Timmermans – Bachelor Thesis, 2018

3. Results 3.1 Height change map In this part the results of the first sub question are presented. Subsequently, a height change map from 2010-2014 of each of the four parks is developed (figure 5). These results are also included enlarged in appendix A (figures A1-A4). As can been seen in figure 5, the Sarphatipark has a hotspot with negative values in the north west near to the Sarphati monument, which is indicated with red colours. In addition, a smaller hotspot with negative values can been seen in the east of the Sarphatipark. Furthermore, the Oosterpark shows a small hotspot with red values (-0,25 – 0,15 m) in the east of the park. The north-west hotspot is due to building construction. The Vondelpark has a small hotspot with red values in the middle of the park. The Flevopark does not have large areas with negative values, since it shows mostly yellow areas (-0.05 – 0 m). In all parks some green areas are visible, which indicate raising or no change in height. All parks have white areas, which are water bodies or trees.

Figure 5. The height change map of the four different parks that this research focusses on: Flevopark, Sarphatipark, Oosterpark & Vondelpark. The circle in the Oosterpark indicates the location of the ZEB-REVO data. The white areas indicate no data. This no data can be trees or water areas.

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Benthe Timmermans – Bachelor Thesis, 2018

In table 3, the statistics of the four parks are presented. The Sarphatipark has the highest percentage of negative change values in the whole park. Furthermore, the Sarphatipark has the lowest mean of subsidence, but highest minimum. Different from the Flevopark, which has the lowest minimum, but highest mean of subsidence. Furthermore, the Flevopark has the lowest percentage of total negative change raster cells within the park. The Sarphatipark and Vondelpark have the highest percentage of negative change raster cells.

Table 3. Different statistics of all parks rounded to 2 decimals (except for mean and standard deviation, which are rounded to 4 decimals). All values are in meters. Minimum Maximum Range Mean Percentage negative STD height change cells within park Sarphatipark -0.74 1.86 2.60 -0.0324 71 % 0.0805 Vondelpark -2.71 2.08 4.79 -0.0092 56 % 0.0754 Oosterpark -1.49 1.40 2.89 -0.0222 70 % 0.0588 Flevopark -3.38 1.46 4.84 0.0111 44 % 0.0977

For the accuracy check of the AHN data the DTM of the ZEB-REVO data was used (figure 6), which was made from the point cloud that was obtained (figure B1 in Appendix B). The data shows that the height is highest at the outer parts of the park and lower in the middle of the park (figure 6 & figure B2 in Appendix B). In addition, the specific part of the Oosterpark shows subsidence from the period 2014- 2018 (figure 6).

Figure 6. The digital terrain model (left) and height change between 2014-2018 (right). The specific location of the measurement is visualized in figure B2, appendix B.

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Benthe Timmermans – Bachelor Thesis, 2018

3.2 Lithology of the parks In this part, the results of the lithology are shown. The lithology to a depth of 20 meters below the surface is visualized (figure 7). The units are merged into subgroups (figure 8). The original graph is visualized in figure C1, appendix C.

Figure 7. The lithology of 20 meters depth of the four different parks

45% 40%

35% 30% 25%

20% 15% 10%

5% 0% Clay / organic Sandy clay Sand / gravel Shells

Sarphatipark Vondelpark Oosterpark Flevopark

Figure 8. The occurrence of different lithology units merged into subgroups.

The Vondelpark shows the highest occurrence of sandy layers, but the lowest occurrence of clay / organic material. The Sarphatipark and Flevopark both have a high amount of clay / organic layers in their lithology. Oosterpark is somewhat in-between the other parks. The amount of shells is for the four parks approximately the same value.

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Benthe Timmermans – Bachelor Thesis, 2018

3.3 Tree correlation 3.3.1 Tree height In this part, the results of the percentages of tree height (figure 9) represented in each park are displayed. The Vondelpark and Oosterpark have the lowest percentage of small (0-9 meter) trees, whereas the Flevopark has the highest percentages of large (15 meters and up) trees. These tree heights were merged into different subgroups, the original data is shown in the appendix (figure D1 in appendix D). There was some correlation, with a buffer of 1 meter and in the parks Vondelpark, Flevopark and Sarphatipark (table D1 in appendix D). However, almost no significant difference between means was found when all trees of all the parks were combined, only for the tree height buffer a strong difference in mean was found. 60%

50%

40% Vondel

30% Flevopark Oosterpark 20% Sarphati

10%

0% 0 to 9 meters 9 to 15 meters 15 meters and up

Figure 9. The tree heights in the four different parks merged into subgroups

3.3.2. Tree species In this part the results of all the tree species (table E1 in Appendix E) are presented. The maple is most represented in all the parks, with the exception of the Flevopark where the Ash tree is most represented (figure E1 in appendix E). The ANOVA test that was conducted results in a significant difference in mean when all trees of the four parks were taken into account (table 5). For the parks, only the Oosterpark showed for all the different buffers significant difference in mean. The Sarphatipark did not show any significant difference in mean of subsidence for different tree species.

Table 4. ANOVA of trees species and subsidence, the significant differences are in blue and rounded to two decimals Oosterpark Vondelpark Flevopark Sarphatipark All parks 1 meter buffer 0.0021 4.13 x 10 -9 0.13 0.06 6.14 x 10-6 5 meters buffer 1.70 x 10-4 8.52 x 10 -6 4.35 x 10-4 0.22 4.67 x 10-7 10 meters buffer 0.0045 8.56 x 10 -7 0.25 0.90 3.33 x 10-6 15 meters buffer 2.1 x 10-10 0.08 0.12 0.69 8.06 x 10-13 Variable height of 4.15 x 10-7 3.2 x 10-3 0.55 0.33 1.59 x 10-11 trees buffer

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Benthe Timmermans – Bachelor Thesis, 2018

4. Discussion 4.1 Interpretation of the results The results show subsidence for three of the four parks: Vondelpark, Sarphatipark and Oosterpark (figure 5 & table 3). The Flevopark has restricted some subsidence areas but did not show an average decrease in height (table 3). This could be due to the fact that the Flevopark is the newest park or to the method of raising the park as discussed before. The Sarphatipark appears to be have most subsidence in average and in percentage (table 3). The subsidence hotspot that is visible is located around the Sarphati monument. This monument could have influenced the subsidence, because different studies have discussed the increase of subsidence as consequence of extra weight on peat (Bakker et al., 1995; Van Asselen & Bos, 2009; Van Gerven, 2004). Furthermore, both AHN’s have a systematic and stochastic error of 5 cm (Van der Zon, 2013; Swartvast, 2010), which could imply that the results that the subsidence map show have an error of 10 cm in total. This possible error is supported by the fact that the height change map show some areas with increase of heights (figure 5), which was not expected. Given these points, it can be inferred that the parks show subsidence. However, there can be criticized on the specific height change that was identified. The ZEB-REVO data that was presented in the results (figure 6), suggests that the data of the height change is accurate. The height change for the area that was looked into in the Oosterpark was around 15 cm in the four years 2010-2014. Therefore, it is assumed this relation of consolidation of peat is linear in time, since it is impossible to assess the phase of consolation. In addition, some studies discuss a linear relation of clay / peat shrinkage in the Netherlands (Gofar & Sutejo, 2007). Therefore, it would mean that this trend would pursue in the four years. This trend of decrease of 15 cm in 4 years can be also seen in the results of the ZEB-REVO, which means the subsidence assessment is accurate for the Oosterpark. However, the accuracy of the other parks is not specified, since all different parks have different properties. The data for the second sub question can be interpreted as that the Sarphatipark and Flevopark should experience the most subsidence based on their lithology (figure 7 & 8). Although this may be true for the Sarphatipark, the height change that is observed in the Flevopark is in contrasts with these findings (figure 5). The Vondelpark shows the highest occurrence of sand and the lowest organic / peat which should mean it experiences the fewest subsidence, which is also in contrast with the height change map. However, this could be due to the fact that the Vondelpark had a lot of raising with sand in the past (Kurpershoek & Ligtelijn, 2001). It can be inferred that the subsurface vulnerability is the highest for the Sarphatipark, which is be supported by the height change map (figure 5 & 7). However, there is no clear relation between lithology and height change. This could be due to the fact that the parks in Amsterdam have artificial raising (Kurpershoek & Ligtelijn, 2001; Grontmij, 2011; Dendelft, 2017). Gans (2011) highlights in his research the influence of the weight of artificial layers on subsidence. This artificial raising could result in distorted results on the relationship between lithology and subsidence. The tree height differed per park, the Flevopark had almost 50% of big trees, whereas the Vondelpark had more small trees (figure 9). This could be due to the fact that the Flevopark has better drainage, which results in better tree growth conditions for many tree species (Kurpershoek & Ligtelijn, 2001). Still, the heights of trees cannot be correlated to subsidence areas. Higher trees would potentially lead to increased subsidence (Williams, 2006; Bakker et al., 1995). This cannot be distinguished in the presented results, since the Flevopark does not show the highest average of subsidence. On the other hand, the ANOVA-test for the Flevopark was significant for three buffers (table D1, appendix D) (1, 5 and 10). Subsequently, the height of trees plays a role in the subsidence for some radius around the trees. Although, this rate of significance was not found for every park, in every park some significant differences in mean were found (table D1, appendix D). The combination of all the trees in all parks only gave one significance (variable height of trees). With no significance for all buffers in mind, the tree height cannot be correlated with subsidence. Equally important as the tree heights were the results of the tree species. The ANOVA-test that was conducted for the tree species showed many significances for every park. Especially when all

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Benthe Timmermans – Bachelor Thesis, 2018 the trees of the parks were combined, for every buffer a significance difference in mean was found (table 4). Subsequently, tree species have influence on the subsidence of the parks, although no significance relation was found for the Sarphatipark. In addition, it is hard to conclude which species have the most influence on subsidence, but this was not the question for this research. However, it has to be taken in mind that the trees in the parks in Amsterdam are maximum 50 years old (Kurpershoeks & Ligtelijn, 2001). Therefore, the trees have had relative few time in comparison with the age of the parks (table 3) to influence subsidence. In addition, Jones & Jefferson (2012) argue that trees influence subsidence less when water fluctuations are reduced. This could be the case for the parks in Amsterdam, since few influence of trees on subsidence is observed and the municipality improved the drainage of e.g. the Oosterpark (Grontmij, 2011). In conclusion, it is hard to state that trees do not influence subsidence based on this research.

4.2 Methodological discussion For the assessment of the subsidence in the parks, AHN2 and AHN3 are used. Both AHN’s were filtered on building, trees and other objects that did not belong to the ground level (van der Zon, 2013; Swartvast, 2010). Subsequently, errors could exist in determination of ground level (Bregt et al., 2016). This statement of wrongly filtering trees out, is supported by the fact that the height change maps (figure 5) do not show white areas (no data) on all the locations with trees (digital appendix). In addition, to compose AHN PDOK used the Inverse Distance Weighting method to compose the DTM, however, different studies propose the use of kriging for interpolating LiDAR data as best method (Guo et al., 2010; Lloyd & Atkins, 2002). The ZEB-REVO data only has relative heights and no absolute height. Subsequently, the connection of the ZEB-REVO to the AHN data was done by georeferencing by hand, which can induce errors. On top of that, the georeferencing was based both vertically as horizontally on AHN3 which could have changed in the 4 years. Lastly, the DTM that was developed from the point cloud was based on the parameters proposed by the ZEB-REVO guide by Haacke (2018) (table B1, appendix B). However, the parameters as proposed for a city by the LAStools itself were different than the ones used in this research. Furthermore, the GeoTOP data was used to predict the lithology of the parks. However, this data has a relative coarse raster size when compared to the other data (table 2) and the size of the parks (table 1), which could deliver errors in the results. In addition, this data only represents the majority of units that are present in a certain layer (Stafleu et al., 2012, Stafleu & Voxels, 2015). Therefore, the soil under the parks could consist of other material than now presented. Lastly, the tree buffers were made with the buffer tool, which draws a radius around every tree. Thereafter, the statistics of the height in this area were calculated. However, when the radius was partly outside the clipped area of a park the statistics were sometimes calculated as not a number (NaN). Subsequently, the higher the buffer zone, the more tree statistics were left out. With this in mind, the data of especially the small parks and coarse buffer zones result in a distorted outcome.

4.3 Further research The analysis period in this research was only four years, which could be too short to give reliable results. Therefore, in further research the AHN1 could be added, which was created in 1997-1998 (van der Zon, 2013; PDOK, 2015) and could subsequently contribute to a longer time period. This longer period can also be reached by adding future ZEB-REVO data. However, no accurate method currently exists to connect this data to absolute data, but could be achieved by connection the ZEB-REVO data to the bolts network of the Netherlands. This bolts network consists of absolute heights relative to NAP (Rijkswaterstaat, 2016). Furthermore, the data of the trees that was obtained by the municipality of Amsterdam only consists of trees that are in ownership of the municipality itself. This does not include private trees, which are for example located in the cemetery of the Flevopark. This could be added in further research.

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Benthe Timmermans – Bachelor Thesis, 2018

This method that was used in this research has only be tried for the four parks in Amsterdam that this research focusses on. Other parks can be added and compared with this research to assure the validly of the method that is been used in this research.

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Benthe Timmermans – Bachelor Thesis, 2018

5. Conclusion This research tried to give an answer to two questions (i): What is the spatial variability of subsidence between and within different parks in Amsterdam and (ii) can this be related to lithology or trees? The hypothesis was that both lithology and trees contributed to subsidence and that all the four parks in this research suffered from subsidence. The first sub question was related to the spatial variability of subsidence between the years 2010 and 2014 and whether this assessment was accurate. It is concluded that there is spatial variability in mean and minimum subsidence between the four parks. Moreover, it is concluded that the spatial variability within parks differs as well. For example, the Sarphatipark showed a clear hotspot of subsidence. As a final conclusion, the accuracy of at least the Oosterpark is acceptable based on detailed LiDAR based elevation data, collected with the ZEB-REVO system. The second question analysed the lithology of the four parks by assessing the subsurface vulnerability. All parks did have clayish and organic attributes, which have the property to consolidate over time. The Sarphatipark has the highest percentage of organic and clay, whereas the Vondelpark has the highest percentage of sand. However, it is concluded that lithological variation this data cannot be correlated to the average and percentage subsidence. The third sub question was related to the influences of both tree species as tree height on subsidence. The influence of tree height on subsidence cannot be discovered. However, there was influence of tree species on subsidence discovered. However, to define which species have the most influence on subsidence, further research on specific species influence is needed. In summary, three out of four parks do show variations in minimum and average subsidence. However, subsidence cannot be related to either lithology or tree height. There is an influence of trees, although the type of species cannot be indicated. The hypothesis therefore is not proven, but interesting new insights were obtained.

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Benthe Timmermans – Bachelor Thesis, 2018

Acknowledgements The completion of my bachelor thesis could not have been possible without the help of Dr. Harry Seijmonsbergen. His contribution and skills were very appreciated and very important. In addition, I want to thank Peter Haacke for his help and skills with the ZEB-REVO scanner. The development of a DTM from the ZEB-REVO data could not have been possible without his guidance. Furthermore, I want to acknowledge the service of the Municipality of Amsterdam and specifically Robert van Eeden who provided the tree file of the specific parks that were used for this research. Lastly, I greatly appreciate the GIS-Studio of the University of Amsterdam, which helped a lot for finishing the different maps.

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Benthe Timmermans – Bachelor Thesis, 2018

Literature list Akker, J.J.H, Borst, L., Muntjewerff, R. Straalen, B. & Zintel, A. (2011). Samenvatting Verdubbeling Oosterpark - Een park voor de toekomst. Onderzoek en Plan van Aanpak verzakkingen. Antrop, M. (2004). Landscape change and the urbanization process in Europe. Landscape and urban planning, 67(1-4), 9-26. Bakker, J. W., Van den Akker, J. J. H., Cornelissen, P., & Boels, D. (1995). Oorzaak en preventie van schade aan wegen door vochtonttrekking door bomen. Barden, L. (1968). Primary and Secondary Conslidation of Clay and Peat. Geotechnique, 18(1), 1-24. Biddle, G. (2001). Tree root damage to buildings. In Expansive Clay Soils and Vegetative Influence on Shallow Foundations (pp. 1-23). Bolund, P., & Hunhammar, S. (1999). Ecosystem services in urban areas. Ecological economics, 29(2), 293-301. Bronswijk, J. J. B. (1988). Modeling of water balance, cracking and subsidence of clay soils. Journal of Hydrology, 97(3-4), 199-212. Bregt, A. K., Grus, L., van Beuningen, T., & van Meijeren, H. (2016). Wat zijn de effecten van een open Actueel Hoogtebestand Nederland (AHN)?. Wageningen University & Research. Bulkeley, H. (2013). Cities and climate change. Routledge. Crilly, M. (2001). Analysis of a database of subsidence damage. Structural survey, 19(1), 7-15. Demuzere, M., Orru, K., Heidrich, O., Olazabal, E., Geneletti, D., Orru, H., ... & Faehnle, M. (2014). Mitigating and adapting to climate change: Multi-functional and multi-scale assessment of green urban infrastructure. Journal of Environmental Management, 146, 107-115. Dendelft (2017). Vondelpark Amsterdam: famous city park in the Netherlands. Derived on 29 june 2018 from: https://dendelft.nl/en/blog/2017/01/08/the-vondelpark-in-amsterdam/ Dewez, T. J., Yart, S., Thuon, Y., Pannet, P., & Plat, E. (2017). Towards cavity-collapse hazard maps with Zeb-Revo handheld laser scanner point clouds. The Photogrammetric Record. DINOloket. (n.d.). Detaillering van de bovenste lagen met GeoTOP. Derived on 5 May 2018, van https://www.dinoloket.nl/detaillering-van-de-bovenste-lagen-met-geotop Freeman, T. J., Littlejohn, G. S., & Driscoll, R. M. (1994). Has your house got cracks?: a guide to subsidence and heave of buildings on clay. Thomas Telford. Frich, P., Alexander, L. V., Della-Marta, P. M., Gleason, B., Haylock, M., Tank, A. K., & Peterson, T. (2002). Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate research, 19(3), 193-212. Gans, W. D. (2011). De bodem onder Amsterdam: een geologische stadswandeling. TNO. García, O. (2014). Siplab, a spatial individual-based plant modelling system. Computational Ecology and Software. 4. 215-222. Gill, S. E., Handley, J. F., Ennos, A. R., & Pauleit, S. (2007). Adapting cities for climate change: the role of the green infrastructure. Built environment, 33(1), 115-133. Gofar, N., & Sutejo, Y. (2007). Long term compression behavior of fibrous peat. Malaysian Journal of Civil Engineering, 19(2), 104-116. Groenlinks. (2013, October 24). Opknappen van het Oosterpark. Retrieved May 22, 2018, from https://amsterdamoost.groenlinks.nl/nieuws/opknappen-van-het-oosterpark Grontmij (2011). Samenvatting Verdubbeling Oosterpark – Een park voor de toekomst. Onderzoek en Plan van Aanpak in verband met de grondwaterproblematiek en verzakkingen in het Oosterpark te Amsterdam. Derived from: https://www.amsterdam.nl/publish/pages/406992/gm-0029441_1_samenvatting.pdf Guo, Q., Li, W., Yu, H., & Alvarez, O. (2010). Effects of topographic variability and lidar sampling density on several DEM interpolation methods. Photogrammetric Engineering & Remote Sensing, 76(6), 701-712. Haacke, P. (2018). Zeb-Revo guide: information on the use of the Zeb-Revo handheld laser scanner and the possible applications and processing of the Zeb-Revo point cloud data. University of Amsterdam.

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Benthe Timmermans – Bachelor Thesis, 2018

Houghton, J. (2009). Global warming: the complete briefing (Vol. 4). Cambridge: Cambridge University Press. Jones, L. D., & Jefferson, I. (2012). Expansive soils (pp. 413-441). ICE Publishing Kooi, H. (2000). Land subsidence due to compaction in the coastal area of The Netherlands: the role of lateral fluid flow and constraints from well-log data. Global and Planetary Change, 27(1-4), 207-222. Kurpershoek E., & Ligtelijn, M. (2001). De parken van Amsterdam (Rev. Ed.) Amsterdam, the Netherlands: Bas Lubberhuizen. Kos, A. A. & Grobbe, H.W. (1995). “Help het park verdrinkt”: (Grond)wateroverlast in Amsterdamse stadsparken en consequenties van ontwateringsmaatregelen. Stromingen (1), 2 Lloyd, C. D., & Atkinson, P. M. (2002). Deriving DSMs from LiDAR data with kriging. International Journal of Remote Sensing, 23(12), 2519-2524. Mentens, J., Raes, D., & Hermy, M. (2006). Green roofs as a tool for solving the rainwater runoff problem in the urbanized 21st century?. Landscape and urban planning, 77(3), 217-226. Municipality of Amsterdam. (n.d.). Renovatie Vondelpark 1999-2010. Retrieved May 22, 2018, from https://www.amsterdam.nl/toerisme-vrije-tijd/parken/vondelpark/renovatie_1999-2009/ Municipality of Amsterdam. (2015). Agenda Groen 2015-2018. Investeren in de Tuin van de Amsterdammer. Retrieved from https://www.bondvanvolkstuinders.nl/bestanden/concept_agenda_groen_vrijgegeven_b_w _9_april_2015.pdf Municipality of Amsterdam. (2016, August 4). Pad tot huidige pagina Home Bouw- en verkeersprojecten Oosterpark: meer ruimte, voor bewoners en bezoekers Aanpak wateroverlast Oosterpark. Retrieved April 17, 2018, from https://www.amsterdam.nl/projecten/oosterpark/aanpak-wateroverlast/ Nieuwenhuis, H. S., & Schokking, F. (1997). Land subsidence in drained peat areas of the Province of Friesland, The Netherlands. Quarterly Journal of Engineering Geology and Hydrogeology, 30(1), 37-48. PDOK. (2015, September 10). Nieuw hoogtebestand AHN3 op PDOK. Retrieved May 23, 2018, from https://www.pdok.nl/nl/actueel/nieuws/artikel/10sep15-nieuw-hoogtebestand-ahn3-op- pdok Poland, J. F. (1984). Guidebook to studies of land subsidence due to ground-water withdrawal. Price, J. S., & Schlotzhauer, S. M. (1999). Importance of shrinkage and compression in determining water storage changes in peat: the case of a mined peatland. Hydrological Processes, 13(16), 2591-2601. Rainproof. (n.d.). Stadsparken: de groene longen van Amsterdam. Retrieved April 17, 2018, from https://www.rainproof.nl/stadsparken-de-groene-longen-van-amsterdam Rijkswaterstaat (2016). Toelichting gebruik van NAP-Peilmerken Roekel (2013). Mysterie bodem opgelost. Kennislink. Retrieved 24 jun. 18 from: https://www.nemokennislink.nl/publicaties/mysterie-bodem-opgelost/ Savard, J. P. L., Clergeau, P., & Mennechez, G. (2000). Biodiversity concepts and urban ecosystems. Landscape and urban planning, 48(3-4), 131-142. Stafleu, J., Maljers, D., Busschers, F. S., Gunnink, J. L., Schokker, J., Dambrink, R. M., ... & Schijf, M. L. (2012). GeoTop modellering. TNO report, 10991. Stafleu, J., & Voxels, P. (2015). Ondergrondmodel GeoTOP. Stam, J. (2010, April 31). Het nieuwe Vondelpark zweeft. Retrieved May 22, 2018, from https://www.volkskrant.nl/economie/het-nieuwe-vondelpark-zweeft~a985208/ Swartvast. (2009). Actueel Hoogtebestand Nederland (AHN): verschillen tussen AHN-1 en AHN-2. Retrieved May 23, 2018, from http://www.swartvast.nl/ahn_1_vs_2.php Thom, A. (2013, May 17). What are the four worst trees for causing subsidence? Retrieved May 11, 2018, from https://www.assetsure.com/what-are-the-four-worst-trees-for-causing- subsidence/

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Williams, A. (2006, December 7). The distance at which trees can affect a building is quite significant. Retrieved May 11, 2018, from https://www.assetsure.com/what-are-the-four-worst-trees- for-causing-subsidence/ Valsson, S., Bharat, A. (2009). Urban Heat Island: Cause for microclimate variations. Architecture – Time Space & People Van Asselen, S., & Bos, I. (2009). Veen in de Rijn-Maas delta: groei, afbraak en compactie. Grondboor & hamer, 63(3/4), 54-61. Van der Velden, R. (2010). AHN: wat is het? [Presentation]. Retrieved May 23, 2018, from http://www.ahn.nl/binaries/content/assets/hwhahn/nieuws/2010/06/ahncongres2010vand ervelden.pdf Van der Zon, N. (2013). Kwaliteitsdocument AHN2. Retrieved from http://www.ahn.nl/binaries/content/assets/hwhahn/common/wat+is+het+ahn/kwaliteitsdo cument_ahn_versie_1_3.pdf Van Gerven, K. A. J. (2004). Dijkdoorbraken in Nederland. Onstaan, voorkómen en bestrijden Van Trikt, J., & Ahrens, H. (n.d.). Veenbodem. Retrieved May 23, 2018, from http://www.geologievannederland.nl/ondergrond/bodems/veenbodem-veenlandschap Walczak, R., Rovdan, E., & Witkowska-Walczak, B. (2002). Water retention characteristics of peat and sand mixtures. International agrophysics, 16(2), 161-166. Whitford, V., Ennos, A. R., & Handley, J. F. (2001). “City form and natural process”—indicators for the ecological performance of urban areas and their application to Merseyside, UK. Landscape and urban planning, 57(2), 91-103. Whittington, P. N., & Price, J. S. (2006). The effects of water table draw-down (as a surrogate for climate change) on the hydrology of a fen peatland, Canada. Hydrological Processes, 20(17), 3589-3600. Wösten, J. H. M., & Ritzema, H. P. (2001). Land and water management options for peatland development in Sarawak, Malaysia. International Peat Journal, 11, 59-66. Zhang, B., Xie, G., Zhang, C., & Zhang, J. (2012). The economic benefits of rainwater-runoff reduction by urban green spaces: A case study in Beijing, China. Journal of environmental management, 100, 65-71.

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Appendices Appendix A: Height change map of different parks

Vondelpark - height change 2010 -2014 ¯

Meters 0 125 250 500 750 1,000

Legend Height change parks in meters (2010-2014) -20.6 (min) - -1.5 -1.5 - -1 -1 - -0.5 -0.5 - -0.25 -0.25 - -0.15 -0.15 - -0.1 -0.1 - -0.05 -0.05 - 0 0 - 0.25 0.25 - 0.5 0.5 - 1 1 - 1.5 (max)

Figure A1. The height change of the Vondelpark in 2010-2014

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Benthe Timmermans – Bachelor Thesis, 2018

Sarphatipark - height change 2010 -2014 ¯

Meters 0 20 40 80 120 160

Legend Height change parks in meters (2010-2014) -20.6 (min) - -1.5 -1.5 - -1 -1 - -0.5 -0.5 - -0.25 -0.25 - -0.15 -0.15 - -0.1 -0.1 - -0.05 -0.05 - 0 0 - 0.25 0.25 - 0.5 0.5 - 1 1 - 1.5 (max)

Figure A2. The height change of the Sarphatipark in 2010-2014

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Benthe Timmermans – Bachelor Thesis, 2018

Flevopark - height change 2010 -2014 ¯

Meters 0 90 180 360 540 720

Legend Height change parks in meters (2010-2014) -20.6 (min) - -1.5 -1.5 - -1 -1 - -0.5 -0.5 - -0.25 -0.25 - -0.15 -0.15 - -0.1 -0.1 - -0.05 -0.05 - 0 0 - 0.25 0.25 - 0.5 0.5 - 1 1 - 1.5 (max)

Figure A3. The height change of the Flevopark in 2010-2014

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Benthe Timmermans – Bachelor Thesis, 2018

Oosterpark - height change 2010 -2014 ¯

Meters 0 40 80 160 240 320

Legend Height change parks in meters (2010-2014) -20.6 (min) - -1.5 -1.5 - -1 -1 - -0.5 -0.5 - -0.25 -0.25 - -0.15 -0.15 - -0.1 -0.1 - -0.05 -0.05 - 0 0 - 0.25 0.25 - 0.5 0.5 - 1 1 - 1.5 (max)

Figure A4. The height change of the Oosterpark in 2010-2014

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Benthe Timmermans – Bachelor Thesis, 2018

Appendix B: ZEB-REVO data

Figure B1. The point cloud of the ZEB-REVO that was obtained in a part of the Oosterpark

Figure B2. The location where the ZEB-REVO data was obtained, the marking indicates the height on which the data was based (road)

Table B1. The parameters for the creation of the DEM as proposed by Haacke (2018)

Parameters Value Step 1 Bulge 0.2 Spike 0.1 Down Spike 1 Offset 0.02

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Benthe Timmermans – Bachelor Thesis, 2018

Appendix C: Lithology occurrence

Lithology occurence in parks in Amsterdam of different lithology units

25%

20%

15%

10%

5%

0% Antropogene Organic Clay Clayic sand / Sand (fine) Sand (middle) Sand (coarse) Gravel Shells sandy clay

Sarphatipark Vondelpark Oosterpark Flevopark

Figure C1. The occurrence of every lithology unit in different parks in Amsterdam

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Benthe Timmermans – Bachelor Thesis, 2018

Appendix D: Tree height 30%

25%

20%

15%

10%

5%

0% To 6 m 6 to 9 m 9 to 12 m 12 to 15 m 15 to 18 m 18 to 24 m from 24 m

Sarphatipark Oosterpark Flevopark Vondelpark

Figure D1. All the percentages of tree heights in different parks in Amsterdam

Table D1. ANOVA of height of trees and subsidence rounded to two decimals, the significant data is in blue Oosterpark Vondelpark Flevopark Sarphatipark All four parks 1 meter buffer 0.39 2.1 x 10-3 5.58 x 10-5 2.7 x 10-2 0.28 5 meters buffer 0.80 0.18 0.02 0.43 0.52 10 meters buffer 0.13 0.03 4.65 x 10-4 0.88 0.12 15 meters buffer 0.12 0.29 0.48 0.29 0.31 Height of trees buffer 0.01 0.19 0.07 0.34 8.32 x 10-5

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Appendix E: Tree species Table E1. Tree species in Dutch in alphabetical order. Species (Dutch) Species (English) Abeel Poplar (a) Acacia Acacia Appel Apple Berk Birch Beuk Beech Cipres Cypress Eik Oak Els Alder Esdoorn Maple Hulst Holly Iep Elm Kastanje Chestnut Kers Cherry Linde Linden Meidoorn Hawthorn Peer Pear Plataan Platan Populier Poplar (b) Pruim Plum Vleugelnoot Wingnut Wilg Willow Anders Diverse

Sarphatipark Oosterpark Flevopark Vondelpark

25%

20%

15%

10%

5%

0%

Eik Els Es Iep Berk Beuk Kers Peer Vlier Wilg Abeel Acacia Appel Cipres Hulst Linde Pruim Esdoorn Kastanje Plataan Populier ANDERS Hazelaar Meidoorn Vleugelnoot Figure E1. Different tree species in the four parks

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Benthe Timmermans – Bachelor Thesis, 2018

Appendix F: Matlab Code clear close all clc

%data load load('Vondel_1m.mat'); load('Vondel_5m.mat'); load('Vondel_10m.mat'); load('Vondel_15m.mat'); load('Vondel_Max.mat'); load('Flevo_1m'); load('Flevo_5m'); load('Flevo_10m'); load('Flevo_15m'); load('Flevo_Max'); load('Ooster_1m'); load('Ooster_5m'); load('Ooster_10m'); load('Ooster_15m'); load('Ooster_Max'); load('Sarphati_1m'); load('Sarphati_5m'); load('Sarphati_10m'); load('Sarphati_15m'); load('Sarphati_Max'); load('AlleParken_1m'); load('AlleParken_5m'); load('AlleParken_10m'); load('AlleParken_15m'); load('AlleParken_Max');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Oosterpark %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Height % 1 meter anova1(Ooster_1m.MEAN_1, Ooster_1m.Boomhoogteklasse)

% 5 meter anova1(Ooster_5m.MEAN_1, Ooster_5m.Boomhoogteklasse)

% 10 meter anova1(Ooster_10m.MEAN_1, Ooster_10m.Boomhoogteklasse)

% 15 meter anova1(Ooster_15m.MEAN_1, Ooster_15m.Boomhoogteklasse)

% Height of tree anova1(Ooster_Max.MEAN_1, Ooster_Max.Boomhoogteklasse)

%% Species % 1 meter anova1(Ooster_1m.MEAN_1, Ooster_1m.Tree_Species)

% 5 meter anova1(Ooster_5m.MEAN_1, Ooster_5m.Tree_Species)

% 10 meter anova1(Ooster_10m.MEAN_1, Ooster_10m.Tree_Species)

% 15 meter anova1(Ooster_15m.MEAN_1, Ooster_15m.Tree_Species)

% Height of tree anova1(Ooster_Max.MEAN_1, Ooster_Max.Tree_Species)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Vondelpark %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Height % 1 meter anova1(Vondel_1m.MEAN, Vondel_1m.Boomhoogteklasse)

% 5 meter anova1(Vondel_5m.MEAN, Vondel_5m.Boomhoogteklasse)

% 10 meter

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Benthe Timmermans – Bachelor Thesis, 2018

anova1(Vondel_10m.MEAN, Vondel_10m.Boomhoogteklasse)

% 15 meter anova1(Vondel_15m.MEAN, Vondel_15m.Boomhoogteklasse)

% Height of tree anova1(Vondel_Max.MEAN, Vondel_Max.Boomhoogteklasse)

%% Species % 1 meter anova1(Vondel_1m.MEAN, Vondel_1m.Tree_Species)

% 5 meter anova1(Vondel_5m.MEAN, Vondel_5m.Tree_Species)

% 10 meter anova1(Vondel_10m.MEAN, Vondel_10m.Tree_Species)

% 15 meter anova1(Vondel_15m.MEAN, Vondel_15m.Tree_Species)

% Height of tree anova1(Vondel_Max.MEAN, Vondel_Max.Tree_Species)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Flevopark %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Height % 1 meter anova1(Flevo_1m.MEAN, Flevo_1m.Boomhoogteklasse)

% 5 meter anova1(Flevo_5m.MEAN, Flevo_5m.Boomhoogteklasse)

% 10 meter anova1(Flevo_10m.MEAN10mBuffer, Flevo_10m.Boomhoogteklasse)

% 15 meter anova1(Flevo_15m.MEAN, Flevo_15m.Boomhoogteklasse)

% Height of tree anova1(Flevo_Max.MEAN, Flevo_Max.Boomhoogteklasse)

%% Species % 1 meter anova1(Flevo_1m.MEAN, Flevo_1m.Tree_Species)

% 5 meter anova1(Flevo_5m.MEAN, Flevo_5m.Tree_Species)

% 10 meter anova1(Flevo_10m.MEAN10mBuffer, Flevo_10m.Tree_Species)

% 15 meter anova1(Flevo_15m.MEAN, Flevo_15m.Tree_Species)

% Height of tree anova1(Flevo_Max.MEAN, Flevo_Max.Tree_Species)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Sarphatipark %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Height % 1 meter anova1(Sarphati_1m.MEAN, Sarphati_1m.Boomhoogteklasse)

% 5 meter anova1(Sarphati_5m.MEAN, Sarphati_5m.Boomhoogteklasse)

% 10 meter anova1(Sarphati_10m.MEAN, Sarphati_10m.Boomhoogteklasse)

% 15 meter anova1(Sarphati_15m.MEAN, Sarphati_15m.Boomhoogteklasse)

% Height of tree anova1(Sarphati_Max.MEAN, Sarphati_Max.Boomhoogteklasse)

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Benthe Timmermans – Bachelor Thesis, 2018

%% Species % 1 meter anova1(Sarphati_1m.MEAN, Sarphati_1m.Tree_Species)

% 5 meter anova1(Sarphati_5m.MEAN, Sarphati_5m.Tree_Species)

% 10 meter anova1(Sarphati_10m.MEAN, Sarphati_10m.Tree_Species)

% 15 meter anova1(Sarphati_15m.MEAN, Sarphati_15m.Tree_Species)

% Height of tree anova1(Sarphati_Max.MEAN, Sarphati_Max.Tree_Species)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% All parks %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Height % 1 meter anova1(AlleParken_1m.MEAN, AlleParken_1m.Boomhoogteklasse)

% 5 meter anova1(AlleParken_5m.MEAN, AlleParken_5m.Boomhoogteklasse)

% 10 meter anova1(AlleParken_10m.MEAN, AlleParken_10m.Boomhoogteklasse)

% 15 meter anova1(AlleParken_15m.MEAN, AlleParken_15m.Boomhoogteklasse)

% Height of tree anova1(AlleParken_Max.MEAN, AlleParken_Max.Boomhoogteklasse)

%% Species % 1 meter anova1(AlleParken_1m.MEAN, AlleParken_1m.Tree_Species)

% 5 meter anova1(AlleParken_5m.MEAN, AlleParken_5m.Tree_Species)

% 10 meter anova1(AlleParken_10m.MEAN, AlleParken_10m.Tree_Species)

% 15 meter anova1(AlleParken_15m.MEAN, AlleParken_15m.Tree_Species)

% Height of tree anova1(AlleParken_Max.MEAN, AlleParken_Max.Tree_Species)

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