Scholarly article on topic 'Identification and Seasonal Analysis of Degraded Tropical Peatland by Using ALOS AVNIR-2 Data'

Identification and Seasonal Analysis of Degraded Tropical Peatland by Using ALOS AVNIR-2 Data Academic research paper on "Agriculture, forestry, and fisheries"

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{"tropical peatlands" / McFeeters-NDWI / "ALOS AVNIR-2" / "remote sensing"}

Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — Dandy Aditya Novresiandi, Ryota Nagasawa

Abstract Tropical peatlands are being subjected to the consequences of rapid economic development without any consideration of the importance of sustainable management practices. Sustainable management of tropical peatlands is an important element in controlling carbon emission. However, the available information of tropical peatlands lacks of accuracy and is outdated, especially in terms of medium to high resolution. Thus, development of reliable monitoring techniques is a significant step towards the sustainable management of tropical peatlands. The remote sensing (RS) application is suitable as a tool to monitor tropical peatlands, whereas direct measurements are generally labor-intensive, time-consuming and limited to accessibility. In this study, methodology to identify degraded tropical peatland was developed by using the McFeeters Normalized Difference Water Index (McFeeters-NDWI), which was derived by Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) data. Additionally, a seasonal analysis was carried out to examine the characteristics of degraded tropical peatland during the rainy and dry seasons from the viewpoint of the medium to high resolution of optical RS. Overall, a relationship was discovered such that the wet shrub class was considered as the degraded tropical peatland area, and was identified as being in between -0.43 to -0.11 of the McFeeters-NDWI value. The wet-shrub class yielded a producer's accuracy of 80.6% and a user's accuracy of 91.8%. Afterwards, the seasonal change was discovered to slightly shift the threshold values (TrVs) in the identification of degraded tropical peatland by as much as -0.05. However, the interval of the TrVs for the wet shrub class was stable and remained unchanged.

Academic research paper on topic "Identification and Seasonal Analysis of Degraded Tropical Peatland by Using ALOS AVNIR-2 Data"

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Agriculture and Agricultural Science Procedia 11 (2016) 90 - 94

International Conference on Inventions & Innovations for Sustainable Agriculture 2016, ICIISA

Identification and Seasonal Analysis of Degraded Tropical Peatland

by Using ALOS AVNIR-2 Data

Dandy Aditya Novresiandi a b* Ryota Nagasawa c

aUnited Graduate School of Agricultural Sciences, Tottori University, 4-101 Koyama-cho Minami, Tottori 680-8550, Japan bCenter for Remote Sensing, Bandung Institute of Technology, Jalan Ganesha 10, Bandung 40132, Indonesia c Faculty of Agriculture, Tottori University, 4-101 Koyama-cho Minami, Tottori 680-8550, Japan

Abstract

Tropical peatlands are being subjected to the consequences of rapid economic development without any consideration of the importance of sustainable management practices. Sustainable management of tropical peatlands is an important element in controlling carbon emission. However, the available information of tropical peatlands lacks of accuracy and is outdated, especially in terms of medium to high resolution. Thus, development of reliable monitoring techniques is a significant step towards the sustainable management of tropical peatlands. The remote sensing (RS) application is suitable as a tool to monitor tropical peatlands, whereas direct measurements are generally labor-intensive, time-consuming and limited to accessibility. In this study, methodology to identify degraded tropical peatland was developed by using the McFeeters Normalized Difference Water Index (McFeeters-NDWI), which was derived by Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) data. Additionally, a seasonal analysis was carried out to examine the characteristics of degraded tropical peatland during the rainy and dry seasons from the viewpoint of the medium to high resolution of optical RS. Overall, a relationship was discovered such that the wet shrub class was considered as the degraded tropical peatland area, and was identified as being in between -0.43 to -0.11 of the McFeeters-NDWI value. The wet-shrub class yielded a producer's accuracy of 80.6% and a user's accuracy of 91.8%. Afterwards, the seasonal change was discovered to slightly shift the threshold values (TrVs) in the identification of degraded tropical peatland by as much as -0.05. However, the interval of the TrVs for the wet shrub class was stable and remained unchanged.

© 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 Faculty of Animal Sciences and Agricultural Technology, Silpakorn University Keywords: tropical peatlands; McFeeters-NDWI; ALOS AVNIR-2; remote sensing

* Corresponding author. Tel.: +81-9057871656. E-mail address: dandyaditya@gmail.com

2210-7843 © 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 Faculty of Animal Sciences and Agricultural Technology, Silpakorn University doi:10.1016/j.aaspro.2016.12.015

1. Introduction

Tropical peatlands play an important role in the global carbon balance, while being recognized as one of the largest terrestrial carbon stores (Jauhiainen et al., 2005). Therefore, tropical peatlands have a direct relationship with the process of global climate change (Jaenicke et al., 2008). Unfortunately, tropical peatlands are being subjected to the consequences of rapid economic development without any consideration of the importance of sustainable management practices (Rieley et al., 2008). Excessive land conversions to commercial plantations, drainage and illegal logging have led to fires, as well as large increases in carbon emissions to the atmosphere (Rydin and Jeglum, 2006). Sustainable management of tropical peatlands is an important element in controlling carbon emission. However, the available information on tropical peatlands lacks accuracy and is outdated (Page et al., 2007), especially in terms of medium to high resolution. Thus, the development of reliable monitoring techniques is a significant step towards the sustainable management of tropical peatlands. The remote sensing (RS) application is suitable as a tool to monitor tropical peatlands, whereas direct measurements are generally labor-intensive, time-consuming and limited to accessibility. The use of the RS application to the monitoring of tropical peatlands has been increasing expeditiously in recent years, along with the availability of RS data sets (e.g., Page et al., 2002; Wijaya et al., 2010; Wahyunto et al., 2012). The data from the Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) are a particular concern, as they provide a medium to high spatial resolution of 10 meters for optical RS data (JAXA, 2008). The present study was carried out to develop methodology for identifying degraded tropical peatland using ALOS AVNIR-2 data. The McFeeters Normalized Difference Water Index (McFeeters-NDWI) was evaluated to measure the amount of wetness in shrub areas, as well as examine the characteristics of degraded tropical peatland from the perspective of the medium to high resolution of optical RS. In addition, a seasonal analysis was carried out to examine the characteristics of degraded tropical peatland during the rainy and dry seasons from the perspective of the medium to high resolution of optical RS.

2. Materials and Methods

2.1 Description of the study area and dataset

The study area was taken from the catchment area of the Kahayan River in Central Kalimantan, Indonesia (Fig. 1). In general, the condition of tropical peatland in this area is mostly in a severely degraded condition (Jaenicke, 2010). A sparse to medium vegetation layer in the form of shrubs covers the degraded tropical peatland in this area. This condition was considered as a key parameter in order to identify the degraded tropical peatland. In this study, ALOS AVNIR-2 data, acquired on 11 January 2009 (rainy season) and 17 October 2010 (dry season), were used as the primary data. An existing land use/cover map, published by the Indonesian Geospatial Information Agency, which was updated by using visual interpretation, was used as a reference map. In addition, data collected from a ground truth survey conducted between 23 and 28 August 2013 was used to provide basic information about the study area.

Fig. 1. Map of Indonesia showing the location of the study area (hatched rectangle).

2.2 Remote sensing techniques and methodology

Geometric and radiometric corrections were made to the data processing for both sets of data (Oo and Takagi, 2010). Thus, eight classes of land use/cover—waterbody light, waterbody mix, waterbody dark, artificial, forest, bare land, shrub and mixed plantation—were extracted by performing a supervised classification using the Maximum Likelihood method. From these classes, the shrub class was used as an approach to identify degraded tropical peatland. Rainy season data were used to develop the methodology for the identification of degraded tropical peatland due to less cloud contamination compared to dry season data. Therefore, McFeeters-NDWI was derived using the combination of green and near-infrared bands of the ALOS AVNIR-2 data.

The McFeeters-NDWI has been proposed as a parameter for discriminating and improving the existence of open water features among soil and other terrestrial vegetation features from the perspective of optical RS data. The McFeeters-NDWI was derived by the following equation (McFeeters, 1996):

McFeeters-NDWI = (REEN ~ NIR\ (1)

(green+nir\

Where, GREEN and NIR are the green and the near-infrared bands of optical RS data in the reflectance unit, respectively. Generally, the open water features yield positive values, while soil and other terrestrial vegetation features generate zero or negative values.

Subsequently, threshold values (TrVs) were derived by means of spatial analysis for discriminating shrub class into wet shrub and dry shrub classes. The McFeeters-NDWI image was then overlaid with the reference map for spatial analysis. Thus, regions that exhibited similar patterns of degraded tropical peatland areas were combined as a "wet shrub", while its McFeeters-NDWI values were considered as the TrVs for the wet shrub class. Accuracy assessment, using a confusion matrix, was carried out in order to assess the accuracy of the TrVs. Hence, a total of 388 points was generated on the shrub areas of the reference map, with each point situated within a 1 x 1 km mesh. In additional, validation using the spectral signature of ALOS AVNIR-2 was carried out in order to examine associations between the derived wet shrub class and the degraded tropical peatland area. A particular value of spectral signature for bands 2, 3, and 4 was found to be represented by the thickness of peatland (Wahyunto et al., 2012). Furthermore, in order to conduct seasonal analysis, dry season data were processed by the same procedures as the rainy season data. Thus, McFeeters-NDWI images derived by both sets of data were then overlaid for seasonal analysis purposes. The difference between the TrVs, in relation to rainy season and dry season data, was examined, as well as their intervals, in order to understand the effect of seasonal change upon the identification.

3. Results and Discussions

As shown in Fig. 2 (a), the McFeeters-NDWI image of the shrub class area was generated by the rainy season data. This image was then overlaid with the reference map for spatial analysis. Thus, a relationship was discovered between the McFeeters-NDWI and the shrub area, such that the McFeeters-NDWI was found to produce a higher value for the wet shrub area than for the dry shrub area. The higher wetness level of the wet shrub compared with the dry shrub was clearly distinguished by the McFeeters-NDWI. Hence, TrVs were derived in order to separate the shrub class into wet and dry classes. The wet shrub was identified as being in between -0.43 and -0.11 of the McFeeters-NDWI value. Subsequently, accuracy assessment using a confusion matrix was carried out to assess the accuracy of the TrVs, which yielded a Producer's Accuracy (PA) of 80.6% and a User's Accuracy (UA) of 91.8% for the wet shrub class, whereas the dry shrub class achieved a PA of 87.4% and a UA of 86.6%. Overall, the TrVs yielded an Overall Accuracy (OA) of 84.2% and a Kappa Coefficient of 0.69.

Concurrently, additional validation using a spectral signature of ALOS AVNIR-2 was performed to examine the association between the derived wet shrub class and the tropical peatland area. The spectral signatures for bands 2, 3 and 4 of ALOS AVNIR-2 were found to represent the thickness of peatland, whereby a lower spectral signature meant a thicker tropical peatland (Wahyunto et al., 2012). A shallow (less than 100 cm of thickness) tropical peatland ought to have spectral signatures of less than, or equal to, 51.2% of band 2, 43.6% of band 3, and 77.6% of

113' 55"ifE I H* ffC'E EU" ': 'j r. :' j" 55'0'E 114" 00 E 114" :;0 \

Fig. 2. McFeeters-NDWI images of (a) rainy season and (b) dry season data.

band 4. These values were used as a boundary to determine the association between the wet shrub class and the presence of tropical peatland. Thus, a spectral signature less than, or equal to, the boundary value ought to be recognized as tropical peatland and vice versa. As a result, a relationship was discovered between the wet shrub class and the tropical peatland area. The spectral signature for the derived wet shrub class was situated below the boundary of the spectral signature for peatland (Table 1). Therefore, the wet shrub class was considered as the degraded tropical peatland area.

Table 1. The spectral signature comparison between shallow tropical peatland and the wet shrub class.

Spectral signature

Class Name Band 2 Band 3 Band 4

% Digital Number % Digital Number % Digital Number

Shallow peat (less than 100 cm) 51.2 130.6 43.6 111.2 77.6 197.9

wet shrub 42.35 108 31.76 81 42.35 108

Furthermore, to conduct a seasonal analysis, dry season data were processed by the same procedures as the rainy season data. As shown in Fig. 2 (b), the McFeeters-NDWI image of the shrub class area was generated by the dry season data. This image was then overlaid with the McFeeters-NDWI image of the rainy season data for seasonal analysis. Thus, the seasonal analysis found that there was a shift of -0.05 in the TrVs between both sets of data

(Table 2). Therefore, the seasonal change was discovered to moderately shift the TrVs in the identification of degraded tropical peatland. Nevertheless, the interval of the TrVs for the wet shrub class was stable and remained unchanged by as much as 0.32.

The rainy season data TrVs were found to be closer to positive values, which indicate that the degraded tropical peatland was slightly wetter during the rainy season and vice versa. However, this condition did not extremely affect the TrVs, since they only moderately shifted, while the interval of the TrVs for the wet shrub class was stable and remained unchanged. Consequently, in the present study, the McFeeters-NDWI provided better analysis for identifying degraded tropical peatland without being severely influenced by the seasonal effects.

Table 2. TrVs comparison between rainy season and wet season data.

Data Threshold Values (TrVs)

dry shrub class wet shrub class open water class

rainy season -0.44 < dry shrub -0.43 < wet shrub < -0.11 open water ^ -0.10

dry season -0.49 < dry shrub -0.48 < wet shrub < -0.16 open water ^ -0.15

4. Conclusions

The study shows that optical RS application could be advantageous as an approach to identify degraded tropical peatland in relation to the sustainable management of tropical peatland. In this study, the methodology to identify degraded tropical peatland was developed by using the McFeeters-NDWI, which was derived by ALOS AVNIR-2 data. The degraded tropical peatland was identified to be associated with the wet shrub class generated by the developed methodology. Additionally, the developed methodology was useful in understanding the seasonal effects of degraded tropical peatland, whereby the McFeeters-NDWI provided better analysis for identifying degraded tropical peatland without being severely influenced by the seasonal effects. Finally, this study should aid to improve the state of knowledge about tropical peatland monitoring, especially involving the use of medium to high resolution optical RS. In terms of future research, findings obtained from this study ought to be used as considerations for further analysis and developing methodology, along with the use of Synthetic Aperture Radar (SAR) data to improve the reliability of tropical peatland identification by using an RS application.

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