Mapping of Tree Damage Classification in the Western Part of Medan City Green Belts Using Geographic Information System
Mapping of Tree Damage Classification in the Western Part
of Medan City Green Belts Using Geographic Information System 1*1
1
1 Rahmawaty , I E P Sembiring , R Batubara and P Patana
Forestry Study Program, Faculty of Forestry, University of Sumatera Utara Jl. Tri Dharma Ujung No. 1 Kampus USU, Medan 20155, Indonesia Em
Abstract. The existence of trees in the cities is very important. Trees play an important role
as an absorber of CO 2 and a storage facility for carbon (C). This study aimed to classify and map the tree damage in the Western Part of Medan City Green Belts. The experiment was conducted using the Forest Health Monitoring (FHM) and the classification of tree damage classes was determined based on the scoring of index values based on USDA Forest Service. The results showed that there were 46 very healthy trees, 976 healthy trees, 1114 lightly damaged trees, 167 medium trees and 9 dead trees. The level of tree damage was dominated by the lightly damaged trees class. If the health of the tree is well preserved, then the tree can perform its function properly. Therefore, it is necessary to carry out this research to provide important information about the damage of the trees then it can be used as a reference for the proper trees care activities.
1. Introduction
Medan City is the third largest city in Indonesia. As a metropolitan city, Medan experiences constant transportation activity. Therefore, the existence of trees in the cities is extremely important. Trees have the ability to reduce air pollutants [1]. One of the city government efforts to create comfort in Medan City is to build a green belt along the main and secondary roads. The green belts were located either along the edges or median strips of roads or solely along the edges of the road. Green belts along median strips function to assist steering along the road, to assist forming views and restricting glare from other vehicles; those on the edges of roads serve as pollution-absorbent, shade- providing and noise-cancelling barriers as well as wind breakers [1-5]. The primary requirements for landscaping plants in streets as stipulated by the Regulation of the Ministry of Public Works (1996) No. 033 are (1) their roots do not damage the road construction, (2) they are easy to maintain, (3) their stems and branches are not easily broken, (4) their leaves do not easily shed and (5) they are safe and offer comfort to motorists and other road users [1].
The trees need to be maintained and should be detected early by knowing the level of damage assessed in terms of damage types, damaged tree location and severity of damage. Early detection allows treatment of unhealthy trees to minimize damage to trees and avoid accidents caused by tree falling [6].The decrease in tree quality is predicted due to air pollution, human activity, biological factors and increasing age of trees. Decrease in quality can be observed from the level of damage suffered by the constituent trees. Damages can be caused by diseases, insect pests, weeds, fire,
Tree damage classification in the Western Part of Medan City Green Belts can implement Mangold modification concept [6]. Trees as the main object of the composition of green belt are expected to be guaranteed its health to provide a sense of security and comfort for the community.
The tree damage in the Western Part of Medan City Green Belts can be presented in the form of maps using Geographic Information System (GIS) technology. The GIS is a system-oriented operation relating to the conventional collection, storage and manipulation of referenced geographical data by computers (hardware and software) capable of handling this data. Among other functions of such mapping is the capacity to show the spatial distribution of geographical phenomena, including the nature and characteristics of their different positions on the surface of the earth [7]. GIS system can
be developed a multi techniques and used to compared the field trees mapping survey result
accuracy, not just for display a map field data survey result only [8,9] . The model can be develop
using another indirect factor such as pixel and whole tree scale, vegetation index, AVIRIS or NDVI
statistical analysis [10].Since information regarding the tree damage in the Western Part of Medan City Green Belts is lacking, conducting this research is of great importance. This study aimed to classify and map the tree damage in the Western Part of Medan City Green Belts. This study is expected to provide information that will assist the government in Medan City in determining a management plan for the environmental development of Medan City.
2. Data and Method
This study was conducted from April to October 2016 in the Western Part of Medan City Green Belts. This research was conducted in 11 main roads that were located in five sub-districts, namely: Medan Barat, Medan Baru, Helvetia, Medan Petisah and Medan Sunggal (Figure 1 and Table 1).
Figure 1.Study site map
Table 1. Name of the road at five sub district in WesternPart of Medan City
No. Road name Sub district
1 Jl. Gagak Hitam Medan Sunggal
2 Jl. Pinang Baris Medan Sunggal
3 Jl. Sunggal Medan Sunggal
4 Jl. Setia Budi Medan Sunggal
5 Jl. Yos Sudarso Medan Barat
6 Jl. Tengku Amir Hamzah Medan Barat
7 Jl. Putri Hijau Medan Barat
8 Jl. Adam Malik Medan Barat
9 Jl. Kpt. Muslim Medan Helvetia
10 Jl. Jend Gatot Subroto Medan Petisah
11 Jl. Let.Jend. Jamin Ginting Medan Baru The green belts for each sub-district of Medan City were determined using a purposive sampling technique. A tree inventory was compiled for all tree species (via a census method) located in the selected green belts. The GPS was used to record the coordinate points of the trees and GIS was used
to analyse the distribution of the tree damage in green belts [11].
The experiment was conducted using the Forest Health Monitoring (FHM), which is monitoring forest stand conditions to analyse the present and the future, and provide recommendations for improving management. The classification of tree damage classes was determined based on the scoring of index values [12]. The 12 codes and damages type, 10 codes and locations of damage, 10 codes and classes of severity of damage and weights of tree damage index also refers to index values [12].
Damage assessment used criteria based on the FHM method [6,13,14]. Data obtained from the damage assessment was calculated by Damage Index Value (DIV) with the code and the weight of the DIV. Damage assessment calculation (1) used criteria based on previous study [6,13,14], namely:
= ( Xi. Yi. Zi) (1)
Where: DIV : Damage Index Value at the tree level Xi : The weight value on the type of damage Yi : The weight value on the part / location of the damaged tree Zi : The weight value on the severity of the damage
The class of damage for the tree based on the weight of the index value with the following criteria: healthy class: 0 - <5, class of lightly damage: 6 – 10, medium damage class: 11-15, and class of heavy damage: 16 - > 21. The final calculation results (DIV) was classified as: healthy class, lightly class, medium class and heavy class.
3. Results and Discussion
The tree species found on the study site were 13 species (Table 2), with 2,313 numbers of individual trees. Pterocarpus indiscus was the dominant tree species found in the study site (54.71%) in accordance to the results of previous study [11,15], followed by Swietenia macrophylla (20.66%) and Swietenia mahagoni (17.59%).
Table 2. Tree species found at the study site
There are 10 types of damage from 13 types of damage proposed by previous study [6] . Of the 10 types of damage (Figure 2), the most common type of damage was vandalism (34%), due to research conducted in urban areas with many advertising activities, such as: sticking banners using nails or wire. The result is in contrast to previous study [16 ] which found that the most damage type was further decay of the trees. This is because the research was conducted in the Bogor Botanical Gardens where the trees were old.
34% broken branches
12% Vandalism
1% Exudation
Wounds (open)
1% Over branching 12%
15% Malformations
4% Broken leaf
1% further weathering
Leaf colored (not green)
Cancer 18%
The percentage of tree damage types can be observed in Figure 3. A total of 2,312 individual trees on 11 arterial roads found in 5 sub-districts in Medan City, the most affected part of trees was on the bottom of stem (41%), because it was easily accessible to humans. In contrast to previous study [16 ],
Figure 2. Percentage of damage type
Total 2313 100.00%
No. Name of tree Scientific name Number of tree Percentage
13 Waru Hibiscus tiliaceus 4 0.17%
12 Beringin Ficus benjamina 3 0.13%
11 Asam jawa Tamarindus indica 55 2.38%
10 Saga Adenathera pavonina 14 0.61%
9 Petai cina Leucaena leucocephala 7 0.30%
8 Melur Podocarpus elongates 1 0.04%
7 Sengon Paraserianthes falcataria 1 0.04%
6 Glodokan Polyalthia longifolia 60 2.59%
5 Tanjung Mimusops elengi 9 0.39%
4 Mangga Mangivera indica 9 0.39%
3 Mahoni daun lebar Swietenia macrophylla 478 20.66%
2 Mahoni Swietenia mahagoni 407 17.59%
1 Angsana Pterocarpus indiscus 1264 54.71%
2% the most commonly found tree parts are in the root and stump part, because many trees were old and easily fallen.
Roots (open) and Leaf stump Bottom root and 17%
0% stem 9%
Branch 13%
Canopy stem 3%
Bottom of stem 41%
Top of stem Bottom and top
2% of the stem 15%
Figure 3.Percentage of damage location
There were three tree damage classifications in the Western Part of Medan City Green Belts, namely: healthy, lightly damaged, and medium trees. Heavy damage classification was not found in the western part of Medan City Green Belts (Table 3). was dominant tree in the
Pterocarpus indicus
study sites (1,232 individual trees). A total of 655 individuals were classified as lightly damage. A total of 455 individuals were healthy and 107 individuals trees were classified as medium.
Table 3. Damage classes based on tree types
Very Number
No Name of tree healthy lightly Medium Heavy Dead healthy of trees
Pterocarpus
1 1232
indiscus
8 - 455 655 107
7
2 439
Swietenia mahagoni
13 - 175 - 219
32 Swietenia
3 478
macrophylla
22 258 180 16 -
2
4 Mangivera indica
7
2 - - - 9 -
- 5 Mimusops elengi
4
3
2
9 Polyalthia
6
60
longifolia
3
33
21
3 - -
Paraserianthes
7 1 1 -
- falcataria
Podocarpus
8
1
1 - - - - - elongates
Leucaena
9
8
1
5
2 - - - leucocephala
Adenathera
10
14
- pavonina
3
9 2 - -
11
55
36
17 2 - - - Tamarindus indica
12
3
2 1 - - - - Ficus benjamina
13
3
2
1 - - - - Hibiscus tiliaceus
Total 2312
46 976 1114 167
9 Based on FHM criteria, there were 976 healthy trees, 1114 lightly damaged trees, and 167 medium trees. The Percentage of Damage Class can be observed in Figure 4 while Map of Tree Damage Distribution on 11 arterial roads in Five Sub District in Medan City can be observed in Figure 5.
Heavy Dead
0% Very
1% Medium
Healthy 7%
2% Healthy
42% Lightly
48%
Figure 4. Percentage of damage class
Figure 5. Map of tree damage distribution on 11 arterial roads in five sub district in Medan city
The level of tree damage was dominated by the lightly damaged trees class ( Table 3 and Figure 5). Based on these conditions, it will require intensive maintenance, such as watering and trimming. Another thing that that should be a concern in the area was vandalism (destructive trees) that was commonly found in the trees along the western part of Medan City Green Belts.
4. Conclusion
There were three tree damage classifications in the Western Part of Medan City Green Belts, namely: healthy, lightly damaged, and medium trees. Heavy damage classification was not found in this location. The level of tree damage was dominated by the lightly damaged trees class. The most common type of damage was vandalism and most damage locations were found on the bottom of the stem.
Acknowledgement
We are grateful to the Indonesian Directorate General of Higher Education (DIKTI) and the University of Sumatera Utara (USU) for providing financial assistance, as well as to the organising th committee of the7 International Symposium for Sustainable Humanosphere 2017, for supporting the presentation of this work on 1-2 November 2017, at the Salak Tower Hotel, Bogor. We also thank the students of the Faculty of Forestry at the USU (especially for Indra) who has assisted with field work.
5. References
[1] Rawat JS and Banerjee SP 1996 Urban forestry for improvement of environment Energy
Environment Monitor.12 (2) 109-116 [2] Ministry of Public Works 1996 Planning procedure of technique landscape road No.
033/TBM/1996. The Directorate General of Highways; Ministry of Public Works Jakarta. pp
58
[3] Sharma SC, Sharga and Roy RK 1994 Abatement of industrial pollution by landscaping Indian
Journal of Environmental Protection.14(2) pp 95-97
[4] Nowak DJ, Stevens JC, Susan MS and Christopher JL 2002 Effects of urban tree management and species selection on atmospheric carbon dioxide Journal of Arboriculture.28 113-121 [5] Rauf A, Rahmawaty and Syofyan A 2016 Technology-based land use for watershed management.USU Press.pp26 [6] Mangold R 1997 Forest Health Monitoring: Field Methods Guide United States Department of
Agriculture Forest Service. Washington [7] Prahasta E 2004 Geographic information system: Tutorial ArcView.CV. Informatika Bandung.
pp456 [8]
Diem JE 2002 Remote Assessment of Forest Health in Southern Arizona, USA: Evidence for Ozone-Induced Foliar Injury. Environ.l Manage. 29 pp 373–384
[9] Xiao QF 2005 Tree health mapping with multispectral remote sensing data at UC Davis,
California Urb. Ecosyst. 8 pp 349–361
[10] Xiao QF, Ustin SL and Mc Pherson EG 2004 Using AVIRIS data and multiple-masking
techniques to map urban forest tree species. Int. J. Remote Sens. 25 pp 5637–5654
[11] Rahmawaty, Sitorus NA and Rauf A 2017 Distribution, above-ground biomass and carbon stock of the vegetation in Taman Beringin Urban Forest, Medan City, North
Sumatra, Indonesia. The Malaysian Forester 80 (1) pp 73-84
[12] USDA Forest Service 2001 Forest Health Monitoring to Monitor the Sustainability of-
Indonesian Tropical Rain Forest SEAMEO BIOTROP. Indonesia
[13] Khoiri S 2004 Study of tree damage level in Srengseng Urban Forest, West Jakarta (Studi
tingkat kerusakan pohon di Hutan Kota Srengseng Jakarta Barat) . Thesis, Department of Forest Resource Conservation, Faculty of Forestry, Bogor Agricultural University (SkripsiJurusan Konservasi Sumberdaya Hutan Fakultas Kehutanan Institut Pertanian Bogor).
[14] Noviady I and Rivai R R 2015 Identification of shade plants health condition in
Ecopark, Cibinong Science Center-Botanic Gardens (Identifikasi kondisi kesehatan pohonpeneduh di Kawasan Ecopark. Cibinong Science Center-Botanic Gardens ). Proceedings of National Seminar of Biodiversity Society of Indonesia (Prosiding Seminar Nasional Masyarakat Biodiversity Indonesia) .1(6) pp 1385-1391
[15] Rahmawaty, Patana P and Latifah S 2017 Spatial analysis on distribution of green belt to reduce
impacts of climate change in Medan City, North Sumatra. Malays. Appl. Biol.46(2) pp 67–76[16] Miardini A 2006 Analysis of Health Tree at Bogor Botanical Garden (Analisis Kesehatan
Pohon di Kebun Raya Bogor ).Thesis, Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, Bogor Agricultural University (Skripsi Departemen Konservasi Sumberdaya Hutan dan Ekowisata Fakultas Kehutanan Institut Pertanian Bogor).
No Part (line) Reviewer evaluation Authors response (Modification)
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1 Line 25-26; 75-76; 77; 98; 104; 107; ...
Point to note the reference, no need to write the author, for example : The classification of tree damage classes was determined based on the scoring of index values based on USDA Forest Service (2001) [8] should be written as: The classification of tree damage classes was determined based on the scoring of index values [8] The result is in contrast to Miardini's study [12] Should be written as: The result is in contrast to previous study [12]
The classification of tree damage classes was determined based on the scoring of index values [12]. The 12 codes and damages type, 10 codes and locations of damage, 10 codes and classes of severity of damage and weights of tree damage index also refers to index values [12].
Pterocarpus indiscus was the dominant tree
species found in the study site (54.71%) in accordance to the results of previous study [11,15], followed by Swietenia macrophylla (20.66%) and Swietenia mahagoni (17.59%).
There are 10 types of damage from 13 types of damage proposed by previous study [6]. Of the 10 types of damage (Figure 2), the most common type of damage was vandalism (34%), due to research conducted in urban areas with many advertising activities, such as: sticking banners using nails or wire. The result is in contrast to previous study [16]...... ......... In contrast to previous study [16], the most commonly found tree parts are in the root and stump part, because many trees were old and easily fallen.
2 Line 82 Alignment of mathematics should be pointed by equation numbers ( (1),...) and referred in the manuscript. For example : Damage
Damage assessment calculation (1) used criteria based on previous study [6,13,14], namely:
= ( Xi . Yi. Zi) (1) assessment calculation (1) used criteria based .....
3 Line 98 Manuscript should be all the Indonesian words have been written in English, please translated translate all the please see table 3 and references Indonesian words beside a name such as Mahoni daun lebar etc.
4 Line 133 We can’t find Table 4 at The Correct one is Table 3 the manuscript draft.
5 Authors can enrich these GIS system can be GIS system can be developed a multi research using developed a multi techniques and used to compared the field comparison method to techniques and used to trees mapping survey result accuracy, not just make a more precisely compared the field trees for display a map field data survey result only assessment for tree mapping survey result [8,9]. The model can be develop using damage mapping in the accuracy, not just for another indirect factor such as pixel and future. display a map field data whole tree scale, vegetation index, AVIRIS survey result only. The or NDVI statistical analysis [10]. model can be develop using another indirect factor such as pixel and whole tree scale, vegetation index, AVIRIS or NDVI statistical analysis etc ( Diem 2002; Xiao and McPherson, 2005).
Mapping of Tree Damage Classification in the Western Part
of Medan City Green Belts Using Geographic Information System1
1
1
1 Rahmawaty , I E P Sembiring , R Batubara and P Patana
Forestry Study Program, Faculty of Forestry, University of Sumatera Utara Jl. Tri Dharma Ujung No. 1 Kampus USU, Medan 20155, Indonesia E-mail: rahma2107usu@gmail.com
Abstract. The existence of trees in the cities is very important. Trees play an important role as an absorber of CO and a storage facility for carbon (C). This study aimed to classify and
2
map the tree damage in the Western Part of Medan City Green Belts. The experiment was conducted using the Forest Health Monitoring (FHM) and the classification of tree damage classes was determined based on the scoring of index values based on USDA Forest Service. The results showed that there were 46 very healthy trees, 976 healthy trees, 1114 lightly damaged trees, 167 medium trees and 9 dead trees. The level of tree damage was dominated by the lightly damaged trees class. If the health of the tree is well preserved, then the tree can perform its function properly. Therefore, it is necessary to carry out this research to provide important information about the damage of the trees then it can be used as a reference for the proper trees care activities.
1. Introduction
Medan City is the third largest city in Indonesia. As a metropolitan city, Medan experiences constant transportation activity. Therefore, the existence of trees in the cities is extremely important. Trees have the ability to reduce air pollutants [1]. One of the city government efforts to create comfort in Medan City is to build a green belt along the main and secondary roads. The green belts were located either along the edges or median strips of roads or solely along the edges of the road. Green belts along median strips function to assist steering along the road, to assist forming views and restricting glare from other vehicles; those on the edges of roads serve as pollution-absorbent, shade-providing and noise-cancelling barriers as well as wind breakers [1-5]. The primary requirements for landscaping plants in streets as stipulated by the Regulation of the Ministry of Public Works (1996) No. 033 are (1) their roots do not damage the road construction, (2) they are easy to maintain, (3) their stems and branches are not easily broken, (4) their leaves do not easily shed and (5) they are safe and offer comfort to motorists and other road users [1].
The trees need to be maintained and should be detected early by knowing the level of damage assessed in terms of damage types, damaged tree location and severity of damage. Early detection allows treatment of unhealthy trees to minimize damage to trees and avoid accidents caused by tree falling [6].The decrease in tree quality is predicted due to air pollution, human activity, biological suffered by the constituent trees. Damages can be caused by diseases, insect pests, weeds, fire, weather, animals and human activities [6].
Tree damage classification in the Western Part of Medan City Green Belts can implement Mangold modification concept [6]. Trees as the main object of the composition of green belt are expected to be guaranteed its health to provide a sense of security and comfort for the community.
The tree damage in the Western Part of Medan City Green Belts can be presented in the form of maps using Geographic Information System (GIS) technology. The GIS is a system-oriented operation relating to the conventional collection, storage and manipulation of referenced geographical data by computers (hardware and software) capable of handling this data. Among other functions of such mapping is the capacity to show the spatial distribution of geographical phenomena, including the nature and characteristics of their different positions on the surface of the
earth [7]. GIS system can be developed a multi techniques and used to compared the field trees
mapping survey result accuracy, not just for display a map field data survey result only [8,9] . The model can be develop using another indirect factor such as pixel and whole tree scale, vegetation index, AVIRIS or NDVI statistical analysis [10].
Since information regarding the tree damage in the Western Part of Medan City Green Belts is lacking, conducting this research is of great importance. This study aimed to classify and map the tree damage in the Western Part of Medan City Green Belts. This study is expected to provide information that will assist the government in Medan City in determining a management plan for the environmental development of Medan City.
2. Data and Method
This study was conducted from April to October 2016 in the Western Part of Medan City Green Belts. This research was conducted in 11 main roads that were located in five sub-districts, namely: Medan Barat, Medan Baru, Helvetia, Medan Petisah and Medan Sunggal (Figure 1 and Table 1).
Figure 1.Study site map Table 1. Name of the road at five sub district in WesternPart of Medan City No. Road name Sub district
1 Jl. Gagak Hitam Medan Sunggal
2 Jl. Pinang Baris Medan Sunggal
3 Jl. Sunggal Medan Sunggal
4 Jl. Setia Budi Medan Sunggal
5 Jl. Yos Sudarso Medan Barat
6 Jl. Tengku Amir Hamzah Medan Barat
7 Jl. Putri Hijau Medan Barat
8 Jl. Adam Malik Medan Barat
9 Jl. Kpt. Muslim Medan Helvetia
10 Jl. Jend Gatot Subroto Medan Petisah
11 Jl. Let.Jend. Jamin Ginting Medan Baru The green belts for each sub-district of Medan City were determined using a purposive sampling technique. A tree inventory was compiled for all tree species (via a census method) located in the selected green belts. The GPS was used to record the coordinate points of the trees and GIS was used to analyse the distribution of the tree damage in green belts [11].
The experiment was conducted using the Forest Health Monitoring (FHM), which is monitoring forest stand conditions to analyse the present and the future, and provide recommendations for improving management. The classification of tree damage classes was determined based on the scoring of index values [12]. The 12 codes and damages type, 10 codes and locations of damage, 10 codes and classes of severity of damage and weights of tree damage index also refers to index values [12].
Damage assessment used criteria based on the FHM method [6,13,14]. Data obtained from the damage assessment was calculated by Damage Index Value (DIV) with the code and the weight of the DIV. Damage assessment calculation (1) used criteria based on previous study [6,13,14], namely:
(1) = (Xi. Yi. Zi)
Where: DIV : Damage Index Value at the tree level Xi : The weight value on the type of damage Yi : The weight value on the part / location of the damaged tree Zi : The weight value on the severity of the damage
The class of damage for the tree based on the weight of the index value with the following criteria: healthy class: 0 - <5, class of lightly damage: 6 – 10, medium damage class: 11-15, and class of heavy damage: 16 - > 21. The final calculation results (DIV) was classified as: healthy class, lightly class, medium class and heavy class.
3. Results and Discussion
The tree species found on the study site were 13 species (Table 2), with 2,313 numbers of individual trees. Pterocarpus indiscus was the dominant tree species found in the study site (54.71%) in accordance to the results of previous study [11,15], followed by Swietenia macrophylla (20.66%) and Swietenia mahagoni (17.59%).
Table 2. Tree species found at the study site No. Name of tree Scientific name Number of tree Percentage
There are 10 types of damage from 13 types of damage proposed by previous study [6]. Of the 10 types of damage (Figure 2), the most common type of damage was vandalism (34%), due to research conducted in urban areas with many advertising activities, such as: sticking banners using nails or wire. The result is in contrast to previous study [16] which found that the most damage type was further decay of the trees. This is because the research was conducted in the Bogor Botanical Gardens where the trees were old.
34% broken branches
12% Vandalism
1% Exudation
Wounds (open)
1% Over branching 12%
15% Malformations
4% Broken leaf
1% further weathering
Leaf colored (not green)
Cancer 18%
Figure 2. Percentage of damage type The percentage of tree damage types can be observed in Figure 3. A total of 2,312 individual trees on 11 arterial roads found in 5 sub-districts in Medan City, the most affected part of trees was on the bottom of stem (41%), because it was easily accessible to humans. In contrast to previous study [16], the most commonly found tree parts are in the root and stump part, because many trees were old and easily fallen.
2313 100.00%
1 Angsana Pterocarpus indiscus 1264 54.71%
13 Waru Hibiscus tiliaceus 4 0.17% Total
12 Beringin Ficus benjamina 3 0.13%
11 Asam jawa Tamarindus indica 55 2.38%
10 Saga Adenathera pavonina 14 0.61%
9 Petai cina Leucaena leucocephala 7 0.30%
8 Melur Podocarpus elongates 1 0.04%
7 Sengon Paraserianthes falcataria 1 0.04%
6 Glodokan Polyalthia longifolia 60 2.59%
5 Tanjung Mimusops elengi 9 0.39%
4 Mangga Mangivera indica 9 0.39%
3 Mahoni daun lebar Swietenia macrophylla 478 20.66%
2 Mahoni Swietenia mahagoni 407 17.59%
2%
Roots (open) and Leaf stump
Bottom root and 17%
0% stem 9%
Branch 13%
Canopy stem 3%
Bottom of stem 41%
Top of stem Bottom and top
2% of the stem 15%
Figure 3.Percentage of damage location There were three tree damage classifications in the Western Part of Medan City Green Belts, namely: healthy, lightly damaged, and medium trees. Heavy damage classification was not found in the western part of Medan City Green Belts (Table 3). Pterocarpus indicus was dominant tree in the study sites (1,232 individual trees). A total of 655 individuals were classified as lightly damage. A total of 455 individuals were healthy and 107 individuals trees were classified as medium.
Table 3. Damage classes based on tree types Very
Number No Name of tree healthy healthy lightly Medium Heavy Dead of trees
Pterocarpus
1 1232 8 455 655 107
7 - indiscus
2 Swietenia mahagoni 13 175 219 - - 32 439 Swietenia
3 478 macrophylla
22 258 180
16 2 -
4
9
7 Mangivera indica 2 - - - -
5
9
4 Mimusops elengi 3 -
2 Polyalthia
6 60 longifolia
3
33
21
3 - - Paraserianthes
7
1
1 - - - - - falcataria Podocarpus
8 1 elongates
1 - - - - - Leucaena
9
8
1
5
2 - - - leucocephala Adenathera
10 14 pavonina - -
3 -
9
2
11
36
17
2 - - 55 - Tamarindus indica
12 Ficus benjamina 2 -
1 - 3 - -
13
3
2
1 - - - - Hibiscus tiliaceus Total 46 976 1114 167 9 2312
Based on FHM criteria, there were 976 healthy trees, 1114 lightly damaged trees, and 167 Damage Distribution on 11 arterial roads in Five Sub District in Medan City can be observed in Figure 5.
Heavy Dead
0% Very
1% Medium
Healthy 7%
2% Healthy
42% Lightly
48% Figure 4. Percentage of damage class
Figure 5. Map of tree damage distribution on 11 arterial roads in five sub district in Medan city The level of tree damage was dominated by the lightly damaged trees class (Table 3 and Figure 5). Based on these conditions, it will require intensive maintenance, such as watering and trimming. Another thing that that should be a concern in the area was vandalism (destructive trees) that was commonly found in the trees along the western part of Medan City Green Belts.
4. Conclusion
There were three tree damage classifications in the Western Part of Medan City Green Belts, this location. The level of tree damage was dominated by the lightly damaged trees class. The most common type of damage was vandalism and most damage locations were found on the bottom of the stem. Acknowledgement We are grateful to the Indonesian Directorate General of Higher Education (DIKTI) and the University of Sumatera Utara (USU) for providing financial assistance, as well as to the organising committee of the7
th
International Symposium for Sustainable Humanosphere 2017, for supporting the presentation of this work on 1-2 November 2017, at the Salak Tower Hotel, Bogor. We also thank the students of the Faculty of Forestry at the USU (especially for Indra) who has assisted with field work.
5. References
12 (2) 109-116 [2] Ministry of Public Works 1996 Planning procedure of technique landscape road No. 033/TBM/1996. The Directorate General of Highways; Ministry of Public Works Jakarta. pp 58
25 pp 5637–5654
Proceedings of National Seminar of Biodiversity Society of Indonesia (Prosiding Seminar Nasional
Ecopark, Cibinong Science Center-Botanic Gardens (Identifikasi kondisi kesehatan pohon peneduh di Kawasan Ecopark. Cibinong Science Center-Botanic Gardens).
[13] Khoiri S 2004 Study of tree damage level in Srengseng Urban Forest, West Jakarta (Studi tingkat kerusakan pohon di Hutan Kota Srengseng Jakarta Barat). Thesis, Department of Forest Resource Conservation, Faculty of Forestry, Bogor Agricultural University (Skripsi Jurusan Konservasi Sumberdaya Hutan Fakultas Kehutanan Institut Pertanian Bogor). [14] Noviady I and Rivai R R 2015 Identification of shade plants health condition in
[12] USDA Forest Service 2001 Forest Health Monitoring to Monitor the Sustainability of- Indonesian Tropical Rain Forest SEAMEO BIOTROP. Indonesia
carbon stock of the vegetation in Taman Beringin Urban Forest, Medan City, North Sumatra, Indonesia. The Malaysian Forester 80 (1) pp 73-84
[11] Rahmawaty, Sitorus NA and Rauf A 2017 Distribution, above-ground biomass and
[10] Xiao QF, Ustin SL and Mc Pherson EG 2004 Using AVIRIS data and multiple-
masking techniques to map urban forest tree species. Int. J. Remote Sens.
[3] Sharma SC, Sharga and Roy RK 1994 Abatement of industrial pollution by landscaping Indian Journal of Environmental Protection.
[1] Rawat JS and Banerjee SP 1996 Urban forestry for improvement of environment Energy Environment Monitor.
[9] Xiao QF 2005 Tree health mapping with multispectral remote sensing data at UC
29 pp 373–384
[8] Diem JE 2002 Remote Assessment of Forest Health in Southern Arizona, USA: Evidence for Ozone-Induced Foliar Injury. Environ.l Manage.
Agriculture Forest Service. Washington [7] Prahasta E 2004 Geographic information system: Tutorial ArcView.CV. Informatika Bandung. pp456
14(2) pp 95-97 [4] Nowak DJ, Stevens JC, Susan MS and Christopher JL 2002 Effects of urban tree management and species selection on atmospheric carbon dioxide Journal of Arboriculture. 28 113-121 [5] Rauf A, Rahmawaty and Syofyan A 2016 Technology-based land use for watershed management.USU Press. pp26 [6] Mangold R 1997 Forest Health Monitoring: Field Methods Guide United States Department of
Davis, California Urb. Ecosyst. 8 pp 349–361
[15] Rahmawaty, Patana P and Latifah S 2017 Spatial analysis on distribution of green belt to reduce impacts of climate change in Medan City, North Sumatra. Malays. Appl. Biol. 46(2) pp 67–76
[16] Miardini A 2006 Analysis of Health Tree at Bogor Botanical Garden (Analisis Kesehatan Pohon di Kebun Raya Bogor). Thesis, Department of Forest Resources Conservation
and Ecotourism, Faculty of Forestry, Bogor Agricultural University (Skripsi
Departemen Konservasi Sumberdaya Hutan dan Ekowisata Fakultas Kehutanan Institut Pertanian Bogor).
Invitation Letter Ref. no : The 7th ISSH/HSS 2017/2017/1508129935
To whom it may concern On behalf of the organizer of the The 7th International Symposium for Sustainable Humanosphere held at Bogor, Indonesia at November 1-2, 2017, I certify that :
Name : Rahmawaty
Institution : Universitas Sumatera Utara Address : Faculty of Forestry, University of Sumatera Utara.
Jl. Tri Dharma Ujung No. 1 Kampus USU, Medan 20155, Indonesia has registered as a participant to the meeting. We have also approved his/her registration to attend the meeting as a speaker with a title of TREE DAMAGE
CLASSIFICATION IN THE WESTERN PART OF MEDAN CITY GREEN BELTS FOR REDUCING THE IMPACTS OF CLIMATE CHANGE.
I do hope that this invitation letter would help the person mentioned above to complete any administrative requirement needed for attending the meeting. Thank you for your attention and kind help.
The 7th ISSH/HSS 2017 - Organizer Dr. Riksfardini Annisa Ermawar
Chairman
Info : http://situs.opi.lipi.go.id/hss2017/
12/2/2018 Gmail - [ISSH 2017] Submission Acknowledgement Rahmawaty PhD <rahmawaty1974@gmail.com> [ISSH 2017] Submission Acknowledgement
1 message
Tue, Oct 31, 2017 at 11:19 AM
Dr. Maya Ismayati <issh@biomaterial.lipi.go.id>
To: Rahmawaty Rahmawaty <rahmawaty1974@gmail.com> Rahmawaty Rahmawaty: Thank you for your submission, "MAPPING OF TREE DAMAGE CLASSIFICATION IN THE WESTERN PART OF MEDAN CITY GREEN BELTS USING GEOGRAPHIC INFORMATION SYSTEM" to International Symposium for Sustainable Humanosphere. With the online conference management system that we are using, you will be able to track its progress through the editorial process by logging in to the conference web site: Submission URL:
Username: rahmawaty If you have any questions, please contact me. Thank you for considering this conference as a venue for your work.
Dr. Maya Ismayati International Symposium for Sustainable Humanosphere ________________________________________________________________________ The 7th International Symposium for Sustainable Humanosphere
12/2/2018 Gmail - IOP Proceeding Review-rahmawaty revision Rahmawaty PhD <rahmawaty1974@gmail.com>
IOP Proceeding Review-rahmawaty revision 1 message
Sun, Feb 18, 2018 at 7:43 PM
Rahmawaty PhD <rahma2107usu@gmail.com>
To: The 7th ISSH Organizing Committee <issh@biomaterial.lipi.go.id> Cc: rahmawaty <rahmawaty@usu.ac.id>, Rahmawaty PhD <rahma2107usu@gmail.com>, Rahmawaty Hamsuddin <rahmawaty1974@gmail.com>
Dear Editor in Chief, please find my revision as attached. Thanks and Best Regards,
- ================= Rahmawaty, Ph.D Faculty of Forestry University of Sumatera Utara Jl. Tri Dharma Ujung No. 1 Kampus USU Medan 20155 Sumatera Utara
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