INDONESIAN PEATLAND MAP: METHOD, CERTAINTY, AND...

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INDONESIAN PEATLAND MAP: METHOD, CERTAINTY, AND USES

PETA LAHAN GAMBUT INDONESIA: METODE PEMBUATAN, TINGKAT KEYAKINAN, DAN PENGGUNAAN

Wahyunto, Kusumo Nugroho, Sofyan Ritung, Yiyi Sulaeman

Indonesian Center for Agricultural Land Resources Research and Development, Jalan Tentara

Pelajar No.12, Cimanggu, Bogor 16114.

Abstract. Peatland map has a strategic significance in agricultural

development planning, land conservation and calculating green house gas

(GHG) emissions. This study aims to improve the accuracy of the

Indonesian peatland map at scale 1:250.000 through an overlay of old

version peatland map (Wahyunto et al. (2003, 2004, 2006) with legacy soil

data and current soilsurveys data. Approximately 2,409 site observations

equipped with recording of geographical positioning System (GPS)

including peat thickness and peat maturity observations used in this study.

The main land cover types on peatland (such as: forest, oil palm, shrubs-

bush, annual agricultural crops, horticulture crops, tree crops/fruits and

paddy fields) were also mapped. The results showed that the latest

Indonesian peatlands based on legacy soil data resulted from soil survey

up to the year of 2011 was approximately 14.9 Mha, mainly distributed into

3 islands namely Sumatra, Kalimantan and Papua. A lot of decreasing

areas from the original estimate total of 20.6 Mha previous peatland area

during 9-year period (2002's to 2011), peatlands of Sumatra and

Kalimantan islands successively reduced approximately 0.7Mha and 1

Mha. While in Papua island peatland estimated was reduced about 4.4

million ha from the old estimate of 8 million ha, because the previous

estimate mostly based on analysis of satellite images with limited ground

truth data. By the support of 2,409 observation points the level of

confidence is much higher compared to the previous version. From the total

peatland area, a 2011 landsat TM imagery analysis showed that 7.8 M ha

(50.1%) is covered by forests, 1.56 M ha (10.5%) oil palm plantation, 0.79

M ha (5.7%) annual agricultural crops and 0.3 M ha (2.3%) paddy field.

Keywords: Peatland, updating, spatial distribution, accuracy, ground truth

Abstrak. Peta lahan gambut mempunyai arti sangat strategis dalam

perencanaan pembangunan pertanian, konservasi lahan dan perhitungan

emisi gas rumah kaca (GRK). Penelitian ini bertujuan untuk meningkatkan

keakuratan peta lahan gambut nasional Indonesia melalui overlay peta

lahan gambut Wahyunto et al., (2003, 2004, 2006) dengan data survei

terkini. Sekitar 2.409 titik pengamatan yang dilengkapi dengan posisi

geografis (GPS) dengan jenis pengamatan ketebalan dan kematangan

5

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gambut digunakan dalam penelitian ini. Tipe penutupan lahan utama

(hutan, kelapa sawit, semak belukar, pertanian tanaman semusim,

hortikultura/ kebun campuran dan sawah) juga dipetakan. Hasil penelitian

menunjukkan bahwa luas lahan gambut Indonesia berdasarkan hasil

kombinasi analisis landsat TM dan data survei tanah sampai dengan tahun

2011 adalah sekitar 14,9 juta ha, tersebar di Sumatera, Kalimantan dan

Papua. Luas ini turun drastis dari perkiraan semula seluas 20,6 juta ha.

Lahan gambut di Pulau Sumatera dan Kalimantan berkurang sekitar 700

ribu sampai 1 juta ha. Sedangkan di Papua luasnya berkurang sekitar 4,4

juta ha dari 8 juta ha karena estimasi luasan yang terdahulu hanya

didasarkan hasil analisis citra satelit dan sedikit data verifikasi lapang

(ground truth). Peta yang terbaru ini mempunyai tingkat keyakinan yang

jauh lebih tinggi dibandingkan dengan peta versi sebelumnya karena

ditunjang oleh 2.409 titik pengamatan. Dari luas total lahan gambut ini,

analisis citra Landsat tahun 2011 menunjukkan bahwa sekitar 7,8 juta ha

(50,1%) lahan ditutupi oleh hutan, 1,56 juta ha (10,5%) kelapa sawit , 0,79

juta ha (5,7%) pertanian tanaman semusim dan 0,3 juta ha (2,3%) sawah.

Kata kunci: Lahan gambut, pemutakhiran, sebaran, akurasi, titik observasi

I. INTRODUCTION

Peatland has a multifunctionality including water retention function, a niche for

peatland-specific biodiversity, and production of agricultural and forest commodities. Peat

stores carbon between 30 to 70 kg C/m3 or equivalent to 300 – 700 t C /ha per one meter

depth (Agus et al., 2009). Peatland in Indonesia stocks an average of about 30-40 Giga

ton C/ha (Wahyunto et al., 2005). Under natural forest, peat sequesters carbon and grows

between 0.5 to 1.0 mm per year, while drained peat emits carbon and subsides at the rate

of 1.5 – 3.0 cm per year. About 50% of the subsidence is attributable to oxidation (Wosten

et al., 1997). Since the subsidence rate is 15-30 times the rate of growth under the drained,

deforested and drained peats become a major source of green house gas emissions (Agus

and Subiksa, 2008).

Reducing emissions from peatland has been one of the main focus of Indonesian

Reducing Emissions from Deforestation and Degradation Program (REDD+). The closest

estimate of peatland area to the existing and real condition is essential as it avoids „hot air‟

of greenhouse gas (GHG) emissions from peat. Spatial distribution of peatland area

estimate has varied from 14 to 26 million ha since 1952 until present (Subagjo H, 2002

and Wahyunto et al., 2005). The estimate of 20.8 million ha (Mha) is one of the most

widely referred wide since it provide a digital shapefile data (Shp) that can be used for the

analysis of land use change trajectories. This peatland map was generated mostly based on

satellite data analysis up until 2002 acquisition dates, with limited ground verification

and input data is known to vary in quality. Since then updated by a number of field

Indonesian Peatland Map: Method, Certainty, and Uses

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validation (ground truth) have been conducted and the number of observation points of

what was considered as peatland as of 2.409 site. These have increased our confidence in

the estimate of peatland area and our current best estimate is 14.9 Million ha with overall

accuracy 87,9% followed by Kappa coeficient 0,68. The main reduction, reaching 28,3%

from the earlier Indonesia Peatland of 20,8 Mha to the current as amount of 14,9 Mha.The

eirlier estimates for Papua was 7,8 Mha, to the current estimate as amount of 3,7 Mha,

where past soil survey was hindered by location remoteness. We still lack ground truth

data in the remote peatland areas and thus further refinement will be made as more soil

survey data are accumulated. This current estimate implies that past GHG analyses have

been inflated and using this current more robust estimate will form a more logical basis

for GHG emission reduction as well as sustainable peatland management plans.

II. MATERIALS AND METHOD

2.1. Soil survey and peatland mapping in Indonesia

In Indonesia, soil resources inventories have been conducted since 1905 by

ICALRD for various purposes (e.g agricultural planning, erosion hazard assessment, and

soil fertility monitoring). This has resulted in numerous soil survey reports and soil maps.

Soil survey reports commonly store soil profile descriptions, i.e soil morfology, and

selected basic physico-chemical properties (Yiyi Sulaeman et al., 2012).The entire

Indonesian land has been covered by a Exploration Soil Map at scale of 1:000.000

(CSAR, 2000). This maps has about 180 soil mapping units with 44 great groups from 8

orders of US Soil Taxonomy (Soil Survey Staff, 1975). As of 2014, all of Indonesian soil

is covered by a 1:250.000 map (ICALRD Personal communication, 2014).

Henceforth, Indonesia has voluminous legacy soil data in form of legacy soil

observations ( in the form of soil profile, soil minipit, and/or soil laboratory analysis data)

and poligon data including legacy soil map with legends. Legacy soil data based, soil

map and field observations data resulted from soil surveys up to now have been used to

assess and update peatland distribution for the whole country. Old estimate spatial data of

peatland (Wahyunto et al., 2003, 2004 and 2005) were mostly based on satellite images

interpretation supported with land unit and soil maps (Center for Soil and Agroclimate

Research and Developmnet, 1999), including Land system maps (RePPPRoT, 1999) with

very limited ground data/field observations. Especially for Papua, where past soil survey

still lack ground truth data, because lack of accessibility. Therefore, field assessments are

required to identify and reclassify any sites that may have been misclassified during the

desktop analysis. A large number representative soil sampling and ground truth can

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provide better estimates of any tipe of peatland, however, collecting field data can be time

consuming and costly .

Newer estimate of peatland areas was validation of peatland old map based on

ground truth (soil survey data) including legacy soil data. Gap still exist on areas with low

accessibility, and these areas are subject to further verification. Updating ICALRD

peatland map (Ritung et al., 2011), conducted by using the combination the result of

more recent soil surveys, legacy soil data and auxiliary information (e.g digital elevation

model, geology map, agroclimate map). Overlaying among“existing soil observation

maps the result of soil surveys” with “old version of peatmap” and “latest satellite images

acquisitions dates” may help in priotizing next soil observations and soil samplings

strategy. The next soil (peat) observations can be directed to the site/area that low

reliability and no soil observations yet. If planned soil observations cannot be observed

due to several reasons, then soil observations may be selected based on priority level. The

high priority is site with low or lack information on peat characteristics. Spatial and

atribute data were used to generate and upadte peatland maps is presented in Figure 1 and

formula to evaluate accuracy assessment peatland mapping are as follows.

Figure 1. Flow chart for generating and updating peatland maps


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Formula for accuracy assessment of updating peatland map

Overall Accuracy = Xii/N

Where: Xii = total true classes of site sampel at diagonal of confussion matrix table

= total number of site samples in confusion matric

I I

Kappa Coef = N ∑ Xii - ∑ X i + Xi+i

i=1 i=1

____________________ ................................................................... (1)

I

N2- ∑ X i + Xi+i

I=1

Kappa Coefficient = 0,68

Where:

N = Total number of site samples in confusion matrix

Xii = Total true classes of site sample at diagonal of confussion matrix table

Xi+ = Total site sample in the row for all column

X+i = Total site sample in the column for all row

2.2. Updating peatland spatial distribution

Updated peatland mapping conducted by means a GIS methodology approach that

integrates: legacy soil data, satellite images data and field validation (ground truth)to

reach more accurately mapping of peatland. This task consisted of four activities: (1) desk

study on legacy soil data base and soil mapping (2) search and explore the information

from satellite images data, that having relation with spatial distribution of peatland; (3)

data integration of selected legacy soil data, existing peatland map, spatial based

information of satellite data (4) field validation/ground truth including field data

collection and (4) generate updating peatland map.

For practical application of the legacy soil profile observations could also be used

as a benchmark for soil properties monitoring and assessment purposes. Armed with

global positioning system (GPS) receiver, map and assisted by Google Map that informs

direction to location from a given landmark. Soil profile observations and soil samples

may re-taken at same location. Then, measured soil properties data can be compared with

previous one. As a result, the extent of existing peatland, soil properties change (peat

thickness, peat maturity etc) can be determined. This technique can be exercised for others

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legacy soil profiles data. Hence, existing peatland and soil properties change can be

mapped easily by interpolation techniques.

III. RESULTS AND DISCUSSION

3.1. Current soil surveys and mappings and future directions

Up to now,conventionally soil surveys and mapping, including peatlands mapping,

conducted by exploring and observing of soil properties and the surrounding environment

is done with reference to the existing accessibility, where the observations were made

through the road that have been there, either by car, boat, bike or on foot. When necessary,

making transect along forested and/or bushed land to reach the representitive sampling

site for soil observations. Thus surveying and mapping peatlands, for areas that are

relatively close to the road assess or river, soil profile information (including peat

thickness and its peat maturity) will be available in more detail and a higher level of

reliability. In areas away from roads and rivers more over still a natural forest or bushe

shrub and there is no access, will be very limited information and low reliability, and

mostly based on the results of satellite image analysis and synthesis of ancilary data/maps

(ie. soil maps, geology maps, topographic maps, etc).

Firstly,soil survey and mapping including peatland inventory, conducted by ground

base method with grid system, which make observations of soil properties at each the

same distance in a point/particular site, it is called transect line. Mapping peatlands by

means ground base methods will take a long time, difficult and costly. However, until now

there is no an existing accurate technology yet, for inventory and verify distribution and

peatland area. Field observation data (resulted from ground observation) or data derived

from the soil profile and accumulated on legacy soil data is absolutely needed. More

intensive field observations (ground truth) will be more detailed/accurate information for

mapping. Field observation data (ground truth), although costly/expensive and exhausting,

do not have a replacement. Without soil observation and ground truth,will produce un-

certainly of peatland map with low accuracy.

The benefit of new and advances on remote sensing and GIS including geo-spatial

technologies by means physiographic approach, the intensity of the field observations

(ground truth) can be reduced, limited to representative areas, but it is still absolutely

necessary. Thus, the combination of digital technology, geo-spatial and land surveying

"ground-based method" is the way forward to be implemented for land resource inventory

includes peatland mapping. Center for Agricultural Land Resources Research and

Dvelopment (ICALRD) conducted peatland maps of Sumatra, Kalimantan and Papua


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islands by means of updating peatland maps issue by Wetland International Program

(Wahyunto et al., 2003, 2004 and 2005) by means of Remote sensing and GIS approaches

supported with ancillary spatial data. Spatial data were used to update spatial information

of peatland these are legacy soil data, soil maps results of previous survey and mapping

up to 2011. Proposed geo-information based for peatland mapping presented in Figure 2.

The results of the extent of peatland, including soil properties development is

presenting in the figure 3 and 4.

Figure 2. Flow chart on Peatland mapping In Indonesia.

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Figure 3. Peatland change estimation in 2002-2011 resulted form updating peatland

mapping for Sumatera Island

Figure 4. Peatland change estimation in 2002-2011 resulted form updating peatland

mapping for Kalimantan Islands


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3.2. The Latest Spatial Data of Peatland in Indonesia

The latest spatial data of peatland in Indonesia was about of 14.9 M ha. The most

extensive peatland found in 3 islands, namely Sumatra, follo wed by Kalimantan, and

Papua (Irian Jaya). Spatial distribution of peatland is presented in Table 1 and Figure 5.

In Sumatra, the widest peat are developedalong east coast including Riau, South Sumatra,

Jambi and Aceh provinces. In the west coast of Sumatra peatland are situated in West

Sumatra province (Pesisir Selatan district) and Bengkulu province (Muko-muko district).

In Kalimantan wide spread peat situated along west coast West Kalimantan

province, especially in Pontianak/Kubu raya, Ketapang and Sambas District. Inland peat,

are found in a swampy area at the upper Kapuas River basin (Kapuas Hulu District). At

the south coastal area, peatland situated in the South Kalimantan and Central Kalimantan

provinces, there are a vast peat among Sebangau, Kahayan, Kapuas and Barito rivers. In

the East Kalimantan province, a quite wide peatland is situated in the backswamp of

upper Mahakam river basin, northwest of Samarinda). Most of the coastal plain in the

form of peat, spread over the coastal plain west of Tarakan, Bulungan/Nunukan district.

In Papua, peatland are widely found along the south coastal plain of Agats, Mappi,

Mimika and a part of Fak-fak districts and peatland also found at swampy areas of Nabire

and Paniai districts, coastal marshes and plains east of the city of Nabire, Paniai district.

Fresh water peatland are found at backswamp of the middle Mamberamo river basin with

altitude of about 100 m above sea level.

Table 1. The latest spatial data of peatland in Indonesia

Province/ Island Agreage

Hectares Percentage

Aceh 215,704 3.35

North Sumatera 261,234 4.06

West Sumatera 100,687 1.56

Riau 3,867,413 60.08

Riau islands 8,186 0.13

Jambi 621,089 9.65

Bengkulu 8,052 0.13

South Sumatera 1,262,385 19.61

Bangka Belitung 42,568 0.66

Lampung 49,331 0.77

SUMATERA 6,436,649 100.00

West Kalimantan 1,680,135 35.16

Central Kalimantan 2,659,234 55.66

South Kalimantan 106,271 2.22

East kalimantan 332,265 6.96

KALIMANTAN 4,777,905 100.00

Papua 2,644,438 71,65

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Province/ Island Agreage

Hectares Percentage

West Papua 1,046,483 28,35

PAPUA 3,690,921 100,00

TOTAL 14,905,475 100,00

Source: Ritung et al., 2011 (Modified)

Figure 5. Peatland map of Indonesia (modified from Ritung et al., 2011)

3.3. Existing landuse/land cover on peatland

To explore the existing and present landuse/land cover on peatland was conducted

by overlaying both map at 1:250.000 scale of latest peatland map (Ritung et al., 2011)

and land use (also called land cover map) (Ministry of Forestry, 2011). Landuse map was

generated based on satellite images analysis of 2010-2011 acquistion dates. Landuse/on

peatland is presented in Table 2.

Peatland in three large islands of Indonesia which still covered by: (i) forested

areas (mangrove, swamp forest, and plantation forest ) as amounts of 7,7 Mha or 52% of

Indonesia peatland, (ii) amounts of 3,23 Mha (21.7%) covered by bushes,(iii) other

peatland has been used for agriculture and settlements. In Sumatra, which is still

dominated by peatland forest areas and bushes as amounts of 2,352,342 ha (32.6%) and

1,526,825 ha (23.7%) respectively. Peatland was used for plantation, annual crops and

vegetables farming, and paddy field are:as amounts of 1,26 Mha (19.6%); 0,499 Mha

(7.4%) and 0,212 Mha (3.3%). The other peatland was used for settlements as amounts of

40 199 ha (0.6%).

In Kalimantan, peatland which is still dominated forest areas (mangrove, peat

forest, forest plantation and bushes as amounts of 2,402,362 ha (49.9%) and 1,373,563 ha


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(28.6%) repectively. Mangrove forests, peat swamps are generally found on the west

coast, the south coast and the east coast (down stream of Mahakam and Sesayap rivers)

East Kalimantan. Peatland was used for agriculture these are: plantation, farmland (food

and horticulture crops) and paddy field are as amounts of 298 156ha (6.2%), 255 835 ha

(5.3%) and 127 781ha (2.7%) respectively. Peatland has been used for settlement as

amounts of 20,966 ha (0.6%).

In Papua peatlands are still dominated forest (mangrove and swampy forest) and

bushes as amounts of 2,98 Mha (81.5%) and 0,33 Mha (9.2%). Papua peatlands,

especially on the south coast of Papua and surrounding Mamberamo river basin been

used for farming, farmland (food and horticulture) and paddy field both mostly as

amounts of 26 933 ha (0.7%).

Tabel 2. Landuse/land cover on peatland for Sumatra, Kalimantan and Papua Islands, Indonesia

Landuse/ Sumatera Kalimantan Papua Grand Total

Land cover ha % ha % ha % ha %

Primary mangrove

Forest 1,147 0.0 1,801 0.0 229,206 6.3 232,154 1.6

Secondary mangrove

forest 29,909 0.5 10,024 0.2 48,868 1.3 88,802 0.6

Primary swamp forest 255,051 4.0 53,254 1.1 2,228,114 60.8 2,536,424 17.0

Secondary swamp forest 1,324,743 20.6 2,182,402 48.6 481,091 13.1 4,143,044 27.8

Forest plantation 741,499 11.5 148 0.0 453 0.0 742,113 5.0

Shurbs and bushes 233,282 3.6 80,566 1.7 88,496 2.4 402,349 2.7

Bushes 1,293,543 20.1 1,293,097 26.9 249,533 6.8 2,836,221 19.0

Plantation 1,262,530 19.6 298,156 6.2 1,723 0.0 1,562,436 10.5

Settlements 40,199 0.6 20,966 0.4 3,586 0.1 64,752 0.4

Bare lands 378,551 5.9 187,447 3.9 13,905 0.4 579,913 3.9

Mining - 0.0 2,065 0.0 495 0.0 2,560 0.0

Cloud cover 1,275 0.0 - - 2,882 0.1 4,157 0.0

Savana 89,143 1.4 2 - 66,921 1.8 156,068 1.0

Water body 5,043 0.1 5,466 0.1 73,205 2.0 83,714 0.6

Swampy areas 50.457 0.8 128,972 2.7 150,793 4.1 330,225 2.2

Annual Agric. Crops 237,937 3.7 81,045 1.7 4,481 0.1 323,469 2.2

Mixed graden (tree crops) 261,882 4.1 174,790 3.6 20,185 0.6 456,864 3.1

Paddy field 212,690 3.3 127,781 2.7 644 0.0 341,122 2.3

Fish pond 14,529 0.2 133 0.0 139 0.0 14,801 0.1

Air port/sea port 106 0.0 - - 94 0.0 201 0.0

Transmigration 147,920 2,3 2,253 0.0 2,129 0.1 4,383 0.0

GRAND TOTAL 6,551,557 100.0 4,687,075 100.0 3,666,946 100.0 14,905,872 100.0

Sources: Peatland map (Ritung et al., 2011); landusemap (Ministry of Forestry, 2011)

3.4. Accuracy assessment of peatland map and its landuse/land cover

Accuracy assessment of peatland map at scale of 1: 250,000 were evaluated to test

the accuracy of peatland spatial distribution and its existing land use/landcover. In

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conjuction with it, test the accuracy of peatland map was s based on class type of

landuse/land cover on peatland. Focus accuracy testing performed on peatland areas with

class landuse/land cover these are: forested, shurbs and bushes, plantations, annual

agricultural crops, mixed garden/tree crops, and paddy fields.

The accuracy or uncertainties include some errors known and unknown, variation

or ambiguity in the database and decision-making rules. Dempster-Shaffer Theory (DST)

is designed to cope with varying degrees of accuracy in determining the information that

there are built using various assumptions. DST also take into account about the

"uncertainty" of the system to respond to the information that is less clear. Each source

(such as imagery, maps and field data/ground truth) is considered a proof (evidence) the

existence of a fact. Confusion matrix was made to compare the class that is considered

correct/right with the class the results super-imposed multiple layers of data and analysis

are automatically processed in a computer (digital analysis) (Also calculated by the

method of approach "discrete multivariate technique called "Kappa analysis" used in the

Kappa statistic to measure the suitability/accuracy (agreement) with the reference data are

considered true (Cohen, 1960; Curran 1986; Skidmore, 1999). If Kappa coefficient value

is 1orclose to 1it is assumed that the level of precision/accuracy is also high between

classes of data analysis results with benchmark/reference data (De Wit and Clever, 2004).

The data used for reference are considered true in this assessment is the result of field

observation data (ground truth).

Accuracy assessment of agricultural landuse/land cover detection was performed

using ground control points (GCP) of ground truth as a results of Global Positioning

System (GPS) measurements during field validations at the site of field validation for

each class of landuse/land cover on peatland. Two thousands four hundred and nine

(2.409) site observation (ground truth) well scattered validation GCP‟s were randomly

selected for validating the accuracy spatial distribution of any tipe landuse/land cover

classification on peatland.

Determination of overall accuracy using equation1, where the results of the

classification results of spatial data processing with the approach of GIS for each class

divided into two groups: the producer's accuracy and user‟s accuracy. Producer's accuracy

indicate show the training site of a classis classified. While user's accuracy indicates the

probability of a training site is classified into a particular class representing the existing

class in the field, in other words, is the difference between class results of GIS

classification and existing or actual class in the field (Lillesand et al., 2004). Besides the

producer's accuracy and user's accuracy, accuracy digital spatial data classification results

are also determined and declared by the Kappa Coefficient, whichit presented inequations


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1 and 2 (Jensen, 1966; Richard and Jia, 2006). Error Matrix showing percentage

correspondence of validation points with Geographic Information System (GIS) analysis

classified of 2011 peatland map and ground validation during 2012-2014 presented in

Table 3. Table 3 shows that estimated overall accuracy for peatland map (Ritung et al.,

2011) is 87,96% with Kappa Coefficient 0,68.

Table 3. Error Matrix showing percentage correspondence of validation points with Geographic

Information System (GIS) analysis classified of 2011 peatland map and ground validation during

2012-2013

Landuse/land cover field verification through Landuse/land cover on peat land Total total Overall Agree-

No. on peatland based 1 2 3 4 5 6 7 8 9 10 11 12 13 site Omission Accura- ment -1

on GIS analysis Rubber an.crop paddy f pineap Tree cr Oilplm Bush Setlm cconut Horti Frspltn Forest shurbs Site cy (%) (%)

1 Rubber 581 31 22 2 8 644 63 90,2

2 Annual crops 2 215 11 9 3 3 243 28 88,5

3 Paddy field 7 52 4 2 1 66 14 78,8

4 Pineapple 41 3 8 52 3 94,2

5 Bushes 11 3 1 363 42 2 2 424 61 85,6

6 Oilpalm 11 4 2 344 12 3 376 29 92,3

7 Tree crops (Fruits) 25 3 6 21 223 1 279 31 88,9

8 Settlements 2 10 86 1 99 13 86,9

9 Coconut 5 45 50 0 100,0

10 Horticulture 7 65 72 0 100,0

11 Forest plantation 8 8 0 100,0

12 Forested areas 42 42 0 100,0

13 Shurbs (Fen) 54 54 0 100,0

Total site 630 241 64 49 446 366 238 136 47 68 8 42 74 2409 242 87,9618

Total Comission (site) 24 19 12 8 78 22 15 50 2 3 0 0 0 233

Agreement-2 (%) 96,2 92,1 81,3 83,7 82,5 94,0 93,7 63,2 95,7 95,6 100,0 100,0 100,0

Note : Agreement-1 (%) = producer‟s accuracy:indicates how the training site of a classis

Classified :

Agreement-2 (%) = User‟s accuracy: indicates the probability of a training site is

classified into a particular class representing the actual class in the field

Overall Accuracy (%) = 581+215+52+41+363+344+223+86+45+65+8+42+54x 100% (1)

2409

= 87,96%

Kappa Coefficient =0,68

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IV. CONCLUSIONS

By applying of remote sensing, GIS technogies and soil survey data up to the year

2011 as well as legacy data, we have updated the peatland map. The latest and most

reliable estimate of Indonesian peatland area is about of 14.85 Mha, mainly distributed in

Sumatra, Kalimantan and Papua. This is a dynamic the data, especially for the remote

areas of Papua where ground truth data are scanty. This newly produced maps have been

used for nationally/locally appropriate mitigation actions (RAN/RAD-GRK).

This research has shown the benefits of combining soil survey and remote sensing

satellite images in the GIS technique for generating and updating peatland maps.

Field verification (ground truthing) has no substitute in data accuracy while the

remote sensing technique increase the speed of mapping. The estimated overall accuracy

of our peatland map is about 88% with Kappa coeffisient of 0,68. Ground survey for areas

in Papua will increase the map accuracy.

REFERENCES

Agus F., I G.M. Subiksa. 2008. Lahan Gambut: Potensi untuk Pertanian dan Aspek

Lingkungan. Balai Penelitian Tanah. Bogor.

Agus, F., E.Runtunuwu, T. June, E.Susanti, H. Komara, H. Syahabudin, I. Las and M.van

Noorwijk. 2009. Carbon budget in landuse transitions plantation. Indonesian

Agricultural Research and Development Development Journal. 29(4):119-126.

Center for Soil and Agroclimate Research. 2000. Indonesian Soil Exploration Maps at

scale 1:1.000.000 Maps. Center For Soil and Agroclimate Research. , AARD.

Bogor.

Cohen,J.1960. A Coefficient of Agreement nominal scales.Educational and psychological

measurement, 20 (1), 37-46.

Jensen, J.R.1966. Introductory to Digital Image Processing: An Introductory Perspective

(second edition). Prentice-Hall, Inc., Upper Saddle River. New Yersey.

Kementerian Kehutanan. 2011. Penutupan Lahan di Indonesia. Kementerian Kehutanan.

Jakarta.

Lillesand T.M. and R.W.Keifer and J. W. Chipman.2004. Remote Sensing and Image

Interpretation (Fifth Edition). John Willey and Sons. New York.

Center for Soil and Agroclimate Research and Development (CSARD). 2000. Atlas

Sumberdaya Tanah Eksplorasi Indonesia, skala 1:1.000.000. Puslitbangtanak,

Badan Litbang Pertanian. Bogor.

Richard, J.A. and Jia, X. 2006.Remote Sensing Digital Image Analysis: An Introduction

(Fourth Edition). Springer-Verleg.Berlin.


95

Kementerian Kehutanan. 2011. Penutupan Lahan di Indonesia. Kementerian Kehutanan.

Jakarta.

LREP-I (Land Resources Evaluation and Planning Project). 1987-1991. Maps and

Explanatory Booklet of the Land Unit and Soil map. All Sheet of Sumatra.

Center For Soil Research, AARD. Bogor.

Regional Physical Planning Project for Transmigration (RePPPRoT). 1989. Land Unit and

Land Status Maps at Scale of 1:250.000. All Sheet of Indonesia. Direktorat Bina

Program Departemen Transmigrasi. Jakarta.

Ritung, S., Wahyunto, Nugroho, K., Sukarman, Hikmatullah, Suparto, Tafakresnanto, C.

2011. Peta Lahan Gambut Indonesia Skala 1:250.000 (Indonesian peatland map

at the scale 1:250,000). Indonesian Center for Agricultural Land Resources

Research and Development, Bogor, Indonesia.

Skidmore,A.K. 1999. Accuracy Assessment of Spatial Information. In : A.Stein F., van

der Meer and B. Gorte (editors), Spatial Statistics for Remote sensing. Kluwer

Academic Publisher, Netherlands, 197-209.

Soil Survey Staff.1975. Key to Soil Taxonomy. United States Development of

Agriculture. Cornel University, USA.

Subagyo H..2002.Penyebaran dan potensi tanah gambut di Indonesia untuk

pengembangan pertanian. Prosiding Lokakarya : Kajian dan sebaran gambut di

Indonesia. Di Bogor 25 Oktober 2002. Wetland International Program. Bogor-

Indonesia hal 197 -227.

Wahyunto, Suparto, B. Heryanto, ad H. Bekti. 2006. Sebaran lahan gambut, luas dan

cadangan C bawah permukaan di Papua (Peatland distribution, area extent, and C

stock of peat in Papua). Wetland Int‟l – Indonesia Programme. Bogor, Indonesia.

Wahyunto, Sofyan Ritung, Suparto dan H. Subagjo. 2005. Sebaran Gambut dan

Kandungan karbon di Sumatera dan Kalimantan. Wetland International

Indonesian Programme. Jalan Ahmad Yani 53. Bogor.

Wahyunto, S. Ritung, Suparto, and H. Subagjo.2004. Map of peatland distribution and its

C content in Kalimantan. Wetland Int‟l – Indonesia Programme and Wildlife

Habitat Canada. Bogor, Indonesia.

Wahyunto, S. Ritung, Suparto, and H. Subagjo.2003. Map of peatland distribution and its

C content in Sumatera. Wetland Int‟l – Indonesia Programme and Wildlife

Habitat Canada. Bogor, Indonesia.

Wosten, J.H.M., Ismail, A.B., and van Wijk, A.L.M.1997. Peat subsidence and its

prcatical implications: a case study in Malaysia. Geoderma 78:25-36.

Yiyi Sulaeman, Any Mulyani, Wahyunto and Muhrizal Sarwani. 2012. Mapping Soil

Depth Characteristic Using Digital Soil mapping Technique to Monitor land

Degradation. Presented on the Scientific Workshop on Sustainable Management

to Enchance Food Production of APEC Members, Chiang mai, Taliand, 28-30

November 2012.

Wahyunto et al.

96

Curran, P.J. and Williamson, H.D. 1986. Sample size for ground and remotely sensed

data. Remote Sensing Environment, 20 :31-41.

De wit a.j. and Clevers JGPW. 2004. Efficiency and accuracy of per field classification

for operational crop mapping. International Journal of Remote Sensing 68 (11):

1155-1161.

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