Scholarly article on topic 'Characterizing Spatial Distribution and Environments of Sumatran Peat Swamp Area Using 250 M Multi-temporal MODIS Data'

Characterizing Spatial Distribution and Environments of Sumatran Peat Swamp Area Using 250 M Multi-temporal MODIS Data Academic research paper on "Earth and related environmental sciences"

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{"tropical peat swamp" / "vegetation dynamics" / "ecosystem change" / MODIS / Sumatra}

Abstract of research paper on Earth and related environmental sciences, author of scientific article — Yudi Setiawan, Hidayat Pawitan, Lilik Budi Prasetyo, Muhammad Irfansyah Lubis, May Parlindungan, et al.

Abstract Recently, the awareness on the wetland ecosystem change in tropical regions has increased considerably, especially in highly sensitive/vulnerable areas such as peat swamp area. This study investigated the vegetation temporal patterns in peat swamp area based on multi-temporal MODIS data. We identified 23 types of significant patterns that were characterized by land cover type and peat depth. They indicate different type of ecosystem and/or different response of ecosystems to the changing environment in the areas. Considering the results, the peat swamp ecosystems can be categorized into two types, as follows: (1) developed land as the industrial forest plantation and other plantations, and 2) secondary swamp forest and swamp bush. Moreover, several patterns have changed significantly in secondary swamp forest ecosystem with a very deep peat have been identified that support natural tree covers and represent important ecosystem to be preserved. Characterization of the peat swamp area will provide baseline information on this ecosystem type and to develop management strategies to foster resilience in the remaining peat swamp forests.

Academic research paper on topic "Characterizing Spatial Distribution and Environments of Sumatran Peat Swamp Area Using 250 M Multi-temporal MODIS Data"

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Procedía Environmental Sciences 33 (2016) 117 - 127

Environmental Sciences

The 2nd International Symposium on LAPAN-IPB Satellite for Food Security and Environmental

Monitoring 2015, LISAT-FSEM 2015

Characterizing spatial distribution and environments of Sumatran peat swamp area using 250 m multi-temporal MODIS data

Yudi Setiawan^*, Hidayat Pawitanb, Lilik Budi Prasetyoc, Muhammad Irfansyah Lubisa,

May Parlindunganb, Annisa Nurdianaa

a Center for Environmental Research, Bogor Agricultural University, PPLH Building 2nd-4th Floor, Jl. Lingkar Akademik, Dramaga, Bogor

16680, Indonesia

b Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Meranti St.

Dramaga, Bogor 16680, Indonesia c Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, Bogor Agricultural University, Meranti St. Dramaga,

Bogor 16680, Indonesia

Recently, the awareness on the wetland ecosystem change in tropical regions has increased considerably, especially in highly sensitive/vulnerable areas such as peat swamp area. This study investigated the vegetation temporal patterns in peat swamp area based on multi-temporal MODIS data. We identified 23 types of significant patterns that were characterized by land cover type and peat depth. They indicate different type of ecosystem and/or different response of ecosystems to the changing environment in the areas. Considering the results, the peat swamp ecosystems can be categorized into two types, as follows: (1) developed land as the industrial forest plantation and other plantations, and 2) secondary swamp forest and swamp bush. Moreover, several patterns have changed significantly in secondary swamp forest ecosystem with a very deep peat have been identified that support natural tree covers and represent important ecosystem to be preserved. Characterization of the peat swamp area will provide baseline information on this ecosystem type and to develop management strategies to foster resilience in the remaining peat swamp forests.

© 2016 The Authors.PublishedbyElsevierB.V. Thisis an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of LISAT-FSEM2015 Keywords: tropical peat swamp; vegetation dynamics; ecosystem change; MODIS; Sumatra

* Corresponding author. Tel.: +62-811-1188-998. E-mail address: setiawan.yudi@gmail.com.

1878-0296 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of LISAT-FSEM2015 doi:10.1016/j.proenv.2016.03.063

Abstract

1. Introduction

1.1. Background

The Intergovernmental Panel on Climate Change/IPCC stated that the Southeast Asian region would face many extreme natural events caused by climate change [1]. This prediction indicates a need of adaptation and mitigation strategies on environmental management in the region, including Indonesia. Moreover, information on ecosystem characteristics and its changes are essential for many aspects of global-environment change, environment adaptation and mitigation studies. Evaluation of the carbon cycle in terrestrial ecosystems [2], climate change modeling and simulation of global warming [3] and development of groundwater conservation strategies [4] requires the characteristics of ecosystems, their complexity, structure, functioning, natural variability and boundaries.

On the other hand, information of ecosystem characteristics in Indonesia is still very limited, especially in highly vulnerable ecosystems such as peat swamp forest, lowland forest, mangrove, sea grass beds, coral reefs and other critical lands.

The importance of tropical peat lands (tropical peat swamp lands) on the global carbon cycle and ecosystems has been studied by many researchers, such as changes in its ecological function [5], estimation of CO2 emissions released by forest fire [6], declining in biodiversity through land conversion [7] and sustainable management in tropical peat land [8]. Furthermore, Wösten et al. [9] explained that peat land in inundated condition is recommended as a regional ecosystem conservation program and reducing CO2 emissions from this lands.

Advances in remote sensing technology enable land scientists to characterize a terrestrial ecosystem, including its change using high temporal resolution satellite data [10]. Monitoring of land surface on such ecosystem continuously in space and time allows a characterization of the ecosystem in Sumatra [11], and, consequently, it would be possible to consider the actual subtle nature of inter-annual change [12].

1.2. Objectives

• To identify the characteristics of peat swamp area in Sumatra, as a sensitive/vulnerable ecosystem, based on spatial-temporal monitoring on vegetation dynamic patterns continuously.

• To detect the changes occurred in the peat swamp ecosystem systematically.

2. Methodology

2.1. Satellite images

The MODIS product used in this study is the Vegetation Indices (VI) Composite 16-day Global 250 m SIN Grid V005 or MOD13Q1 product, which provided the needed vegetation phenology data. In addition, the product had already been systematically corrected for the effects of gaseous and aerosol scattering. The MODIS EVI is embedded in the MOD13Q1 product. The MODIS LAND Discipline Group (MODLAND) developed the EVI for use with MODIS data following this equation:

EVI = G—-~fred ,-(1 + L) (1)

Pnir + ClPred CiPblue + ^

where, p*nir, p*red and p*blue are the remote sensing reflectance in the NIR, red and blue, respectively, L is a soil adjustment factor, and C1 and C2 describe the use of the blue band in correction of the red band for atmospheric aerosol scattering. The coefficients, C1, C2, and L, are empirically determined as 6.0, 7.5, and 1.0, respectively. G is a gain factor set to 2.5 [13].

The EVI data was developed in the above form in order to optimize the vegetation signal with improved sensitivity in high biomass regions. The EVI also minimizes atmospheric influences with the "aeroso l resistance" term which uses the blue band to correct aerosols influence in red band [13]. In this study we used the MODIS EVI datasets

which were acquired from January 2001 to December 2013. The data were obtained through open access publicly from USGS Land Processes Distributed Active Archive Center (USGS LP DAAC). The study area is covered by four MODIS tiles: h27v08, h27v09, h28v08 and h28v09. The images were then clipped to cover the Sumatran peat swamp area and sequentially stacked to produce the EVI time-series datasets. Accordingly, peat swamp area of Sumatra can be characterized by regular EVI sequence at 299 time series with the time interval 16 days.

2.2. Maps datasets

Land cover map 2013 provided by the Ministry of Forestry was used to describe the characteristics of land cover type in the peat swamp ecosystem. This land cover map was generated based on interpretation of Landsat 5 TM/7 ETM+, and performed by visual interpretation. This classification was performed by digitizing polygons based on image-interpretation with minimum mapping unit (MMU) defined by means of the smallest polygon identified. The 23 land cover types by the Ministry of Forestry are as follows: 1) Primary dry land forest (Hp); 2) Secondary dry land forest (Hs); 3) Primary swamp forest (Hrp); 4) Secondary swamp forest (Hrs); 5) Primary mangrove forest (Hmp); 6) Secondary mangrove forest (Hms); 7). Bush/slash (B); 8) Swamp (Rw); 9) Swamp bush (Br); 10) Savannah (S), 11) Industrial forest plantation (Ht), 12). Plantation (Pk), 13). Dry land agriculture (Pt); 14) Mixed dry land agriculture (Pc); 15) Rice field (Sw); 16) Fishpond (Tm); 17) Bare land (T); 18) Transmigration (Tr); 19) Mining (Tb); 20) Airport area (Bdr); 21) Built-up area/Housing (Pm); 22) Water body (A); and 23) Cloud cover.

Moreover, map of peat depth distribution in Sumatra was provided by the Global Forest Watch [14]. The depth was classified into 6 classes: 1) less than 50cm; 2) 50-100cm; 3) 100-200cm; 4) 200-300cm; 5) 300-400cm; and 6) more than 400cm.

2.3. Image processing

In this study, a clustering method is used to group the EVI temporal patterns into meaningful clusters, even if, the clusters may be of arbitrary shapes due to the huge amount and diverse characteristics of the datasets. Another important issue in the use of time-series EVI to provide basic information of vegetation phenology is the handling of residual noise in the EVI composited datasets [14]. This noise object refers to the atmospheric disturbance which cannot be removed effectively by the MVC algorithm. Such noise degrades the data quality and confusing the analysis of temporal image sequences by introducing significant variations in the EVI time-series data.

Extending the themes mentioned above, we consider the spatial time-series EVI data as multidimensional signals and apply signal-processing technique to convert the spatial data into the frequency domain [16]. We applied wavelet transform to reduce inevitable disturbance in the EVI profiles. The wavelet transform could be useful to remove high frequency noise in vegetation phenology data as well as to preserve hierarchical information while allowing for pattern decomposition [12, 17, 18]. In order to analyze the fluctuation of the EVI values, we used the level 3 of Coiflet wavelet transform since this wavelet shape gives remarkably good results in determining phenological. More details about the wavelet transform can be found in Mallat's paper [19].

Meanwhile, distinguishing among temporal patterns into meaningful information was accomplished using the K-means clustering method based on Euclidean distance in an EVI-space, in which each EVI images provides one dimension of feature space, analogous to spectral clustering. The clustering method yields sets of clusters, which each cluster represents a significant different EVI pattern of detailed information of characteristics/type of peat swamp area (Fig. 1). The similar method was applied in a previous study [18], which a specific class of land use was determined based on seasonal land cover dynamics in a long-term analysis.

The model generating the data is of the following from: X(i)=/(i)+£(i), and more precisely, for k clusters [16]:

T : (/>) + *' = x!.1 note: k = /,...« (2)

where X is a cluster, which describes the matrix of Euclidean distances between objects by hierarchical clustering algorithm,/is a signal, is a centered Gaussian white noise of variance a2 independent of k and i and where T is a slight deformation transforming a given function g as follows:

where b(i) is around 0, and a(i), d(i) around 1.

Fig. 1. Clustering the EVI temporal pattern in multidimensional feature space.

In this study, the complexity and enormous amount of time-series EVI datasets may lead to the difficulty of obtaining the actual number of clusters. Therefore, to provide maximum effectiveness of the clustering algorithm, we first consider the number of clusters of 25 which was then evaluated based on a statistical measurement of how separate that pattern is to patterns in its own cluster compared to patterns in other clusters. The separability analysis was applied to discriminate among high detailed significant patterns that were theoretically defined to portray the specific characteristics of each peat swamp area in the study site.

3. Results and Discussion

3.1. Distinguishing typical patterns in peat swamp area

As mentioned earlier, we defined typical EVI patterns in Sumatran peat swamp area, which indicates different type of ecosystem and/or different response of ecosystems to the changing environment in a given land area. The EVI pattern is used to measure reliable spatial and temporal characteristics of vegetation dynamics of land cover, as a means for better understanding of land characterization [18, 20].

The initial segmentation of the 13-years EVI composites into typical pattern of peat-ecosystem types was performed using clustering method (unsupervised). In this study, these typical patterns were differentiated into 25 clusters as can be seen in Fig. 3. The distribution of each typical pattern in study area is shown in Fig. 2.

Fig. 2. Distribution of each typical pattern in peat area.

In order to achieve the significant patterns, the number of clusters was evaluated based on the statistical separability analysis. Firstly, the 25 clusters of dynamics pattern in peat swamp area were near the maximum number of typical patterns that could be discriminated effectively. However, the result showed the need to evaluate such 25 cluster number because some clusters were so difficult to be separated from each other, which indicated by a high correlation (as shown in Table 1). For instance, class pattern-6 shows a high correlation with class pattern-8; class pattern-24 and class pattern-25. Consequently, we combined such clusters as needed. Finally, the typical patterns of Sumatran peat swamp were discriminated into 23 class patterns. The 23 typical patterns seem sufficient to represent various patterns of vegetation dynamics in Sumatran peat swamp ecosystems. Each class pattern represents the specific peat swamp ecosystem type; in turn inferred to have relatively homogeneous environmental characteristics such as peat depth, land cover type, elevation, etc.

Fig. 3. The 25 class of dynamics vegetation patterns in Sumatran peat swamp.

Fig. 3. The 25 class of dynamics vegetation patterns in Sumatran peat swamp (Continue).

Table 1. Separability matrix of the 25 class-patterns in this study.

peat_cls1 91.56 0.21 2.27 0.5 0.35 0.04 0.91 2.01 0 0 0.16 0 0.04 0 0 0.17 0 0 0.13 0 0 0.19 0.3 0

peat_cls2 0.56 994.98 0.75 0.5 0.03 0.04 0.75 0 0 0.13 0.22 0 0.04 0.08 0.06 0.06 0 0 0.13 0.11 0 0.19 0 0

peat_cls3 2.41 1.1 85.25 2.97 0.21 0.56 2.81 0 0 0.13 1.27 0.12 0.64 0.12 0 0.29 0 0.06 0.51 0 0.09 0.98 0.65 0

peat_cls4 0.18 0.09 0.74 92.56 0 0

peat_cls5 0.11 0.09 0.21 0.07 97.58 0

peat_cls6 0.05 0.21 0.36 0.09 0 98.22

peat_cls7 0.74 0.44 0.72 0.34 0.14 0.04

peat_cls8 0.14 0.37 0.32 0.18 0.14 0

0.22 0.28 0.68

0.96 0.2

9/25 0

99.91 0

3.2. Characteristics of typical patterns in peat swamp area

Some previous studies [21, 22] determined the global ecosystem characteristics based on their seasonal land cover, floristic properties, climate, and physiognomy. In this study, to understand the environmental characteristics of each typical pattern, the 23 patterns were characterized by land cover type and peat depth. According to the land cover map, most of class patterns in the peat swamp were associated mainly with six land cover types; namely: secondary swamp forest, swamp bush, timber forest, plantation, paddy field and bare lands. Consequently, more than one typical pattern might be characterized by one land cover type, which represents different environmental characteristics of a specific ecosystem.

As shown by Fig. 4, most of peat area with a depth more than 4 meter is covered by pattern-12 (12.27%), pattern-13 (15.07%), pattern-14 (22.06%) and pattern-15 (14.71%), which is widely distributed in the central raised part of the peat swamp area. The pattern-12 and pattern-14 are highly characterized by timber forest plantation; 21.88% and 20.34%, respectively. A decreasing EVI pattern periodically on both patterns indicated that the area was a part of land use management. Consequently, good water availability and management is an important issue of such areas.

Meanwhile, the pattern-13 and pattern-15 are covered by secondary swamp forest (42.46%) and swamp bush (19.75%), respectively. The pattern-13 has relatively steady during 13 years (Fig. 3). Then, as overlaid with hotspot data (https://firms.modaps.eosdis.nasa.gov/), it indicated that the areas had never been burned from 2000 to 2013. This peat lands support a natural tree cover and important ecosystem to be preserved. Moreover, the swamp bush area which characterized by pattern-15 indicates a decreasing EVI pattern in 2013. It might be caused by land conversion as well as peat-fires.

Fig. 4. Relationships between class patterns of peat swamp and peat depth.

Visual analysis on the 23 typical patterns indicated that several patterns changed significantly (detail in Table 2). In industrial forest plantation, such change pattern was caused by a change in land cover, as a part of land management; for instance: planting, managing and harvesting of trees. The dynamics change was represented by pattern-6/8, pattern-9, pattern-12, pattern-14, and pattern-16. These different change pattern types represent different land characteristics at temporal scale. Moreover, land management activities might also affect the change patterns in plantation areas; such as weeding and replanting. These change patterns were represented by pattern-

18 and pattern-19.

Moreover, the abrupt changes in the secondary swamp forest and swamp bush, which represented by pattern 5 and pattern 15, respectively, occurred mostly at a peat depth of more than 400 cm. These typical conditions have numerous consequences relevant to the environment as well as changes in carbon storage, land degradation and loss of biodiversity.

Table 2. Summary of typical pattern characteristics in Sumatran peat swamp.

No Class pattern Land cover type Peat depth (cm)

1 Pattern 1 Water features including lakes and reservoirs < 50

2 Pattern 2 Water features including lakes and reservoirs; mixed vegetated areas < 50

3 Pattern 3 Swamp bush 100-200

4 Pattern 4 Swamp bush, paddy field/intensive agricultural lands 50-100

5 Pattern 5 Swamp bush > 400

6 Pattern 6/8 Industrial forest plantation, swamp bush 50-100; 100-200,

7 Pattern 7 Swamp bush 50-100

8 Pattern 9 Industrial forest plantation > 400

9 Pattern 10 Bare land, swamp bush 300-400

10 Pattern 11 Secondary swamp forest 300-400, > 400

11 Pattern 12 Industrial forest plantation > 400

12 Pattern 13 Secondary swamp forest > 400

13 Pattern 14 Industrial forest plantation > 400

14 Pattern 15 Secondary swamp forest > 400

15 Pattern 16 Industrial forest plantation, swamp bush 50-100

16 Pattern 17 Plantation, secondary swamp forest, swamp bush 100-200

17 Pattern 18 Plantation 100-200

18 Pattern 19 Plantation, swamp bush 100-200

19 Pattern 20 Plantation, swamp bush 50-100

20 Pattern 21 Plantation 50-100

21 Pattern 22 Plantation 50-100

22 Pattern 23 Plantation 50-100

23 Pattern 24 and 25 Plantation 50-100

Ecosystem characteristics*1

Change pattern significantly in 2002_q1q2

Change pattern significantly in 2002_q2q3

Change pattern significantly in 2006_q2q4

Change pattern significantly in 2005_q2q3

Change pattern significantly in 2013_q2q3

Change pattern significantly in 2002_q3q4, 2008_q1q2, 2013_q2q3 Change pattern significantly in 2011_q2q3, 2013_q2q3 Not significantly changed Change pattern significantly in 2006_q3q4, 2011_q2q3 Not significantly changed Change pattern significantly in 2002_q3q4, 2009_q3q4 Change pattern significantly in 2013_q2q3

Change pattern significantly in 2002_q3q4, 2006_q2q4 Change pattern significantly in 2002_q3q4

Not significantly changed Change pattern significantly in 2005_q3q4

Change pattern significantly in 2006_q3q4

Not significantly changed Not significantly changed Not significantly changed Not significantly changed

Characterization of typical peat ecosystem based on temporal pattern analysis would provide useful information regarding the change dynamics in the peat land ecosystems; consequently it should be possible to consider the actual, subtle nature of inter-annual ecosystem change in Sumatran peat swamp.

Fig. 5. Relationships between land cover/use types and their main typical patterns.

4. Conclusion

Monitoring land surfaces continuously based on temporal vegetation dynamics allows characterization of the typical ecosystem in peat swamp area. This study is based on the approach that each pattern of vegetation dynamics represents the specific peat swamp ecosystem type; in turn inferred to have relatively homogeneous environmental conditions such as land cover type and peat depth.

On Sumatran peat swamp, the temporal pattern of EVI profiles was differentiated into 23 patterns. Each pattern indicates different type of ecosystem and/or different response of ecosystems to the changing environment in the areas. Considering the results, the peat swamp ecosystems can be categorized into two types as follows: (1) developed land as the industrial forest plantation and other plantations, and 2) secondary swamp forest and swamp bush. Different typical pattern of these ecosystems represented different environmental characteristics such as peat depth.

In forest plantation areas, the dynamic change pattern was caused mostly by land management activities, for instance: planting, managing and harvesting of trees. Moreover, the abrupt changes in the secondary swamp forest and swamp bush, either by peat-fire or human factors, especially located at very deep peat soil (more than 400 cm), have numerous consequences relevant to the environmental changes.

Acknowledgements

We would like to thank the Center for Environmental Research, Bogor Agricultural University (PPLH-IPB) for giving us opportunity to get the research funding. This research was funded by Indonesian Directorate General of Higher Education (DIKTI) for fiscal year 2015.

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