The Indonesian Ministry of Forestry, where I have been working, and The NZ School of Forestry, University of Canterbury provided supporting letters to conduct the field visit. A research supporting letter is an essential document3 for conducting field research in Indonesia.
This field research was conducted from September – December 2011. For several reasons, there was a delay and slow progress in collecting data for this study.
Visits to the capital city of every selected province were arranged to collect data and information as given in Table III-3. A special arrangement was also made to visit national institutions based in Jakarta, the capital of Indonesia.
3
The letter is required formally by both central and local institutions. The letter should be addressed to, and approval should be sought from the head of the institution or head of department before it is forwarded to the relevant department or unit. The process to get an approval and to get the required data varies depending upon the presence of the personnel is in charge to approve or to handle the data.
No. East Kalimantan* South Kalimantan* SE Sulawesi*
District/City Number of Subdistricts District/City Number of Subdistricts District/City Number of Subdistricts
1 Paser 15 Tapin 12 Wakatobi 8
2 Kutai Barat 21 Tanah Laut 11 Muna 39
3 Kutai Kartanegara 18 Tanah Bumbu 10 Konawe 30
4 Kutai Timur 19 Tabalong 12 Konawe Utara 7
5 Berau 13 Kotabaru 25 Konawe Selatan 22
6 Malinau 12 Hulu Sungai Utara 16 Kolaka 23
7 Bulungan 11 Hulu Sungai Tengah 11 Kolaka Utara 15
8 Nunukan 9 Hulu Sungai Selatan 11 Bombana 22
9 Penajam Paser Utara 4 Barito Kuala 19 Buton 31
10 Tana Tidung 3 Banjar 19 Buton Utara 6
11 Balikpapan (C) 5 Balangan 8 Kendari (C) 10
12 Samarinda (C) 6 Banjarmasin (C) 5 Bau-bau (C) 7
13 Tarakan (C) 4 Banjarbaru (C) 6 - -
14 Bontang (C) 3 - - - -
51 Table III-3 Data collection from field visits
Data/Information Name of
Institution/Organisation
Acronym Type of Data
Land use (Tabular):
forests concessions transmigration areas road network forest infrastrucures agricultural land crop plantation mining sites
- The National Statistics Agency at central and localbranches - The Ministry of Forestry - Provincial Forestry Service
Office BPS MoF FSO - Spatial (Softcopy) - Non-spatial (softcopy and hardcopy)
Maps of forest concessions (natural concessions, industrial plantation concessions, and community-based plantations)
- The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial
Maps of transmigration areas - The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial
Maps of road network - The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial
Maps of forest infrastructures - The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial
Maps of Mining sites - The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial
Maps of potential mining - The Directorate of Planning and Utilisation of Production Forests (Direktorat Bina rencana Pemanfaatan Hutan Produksi), The Ministry of Forestry
BRPHP (MoF) - Spatial
Maps of potential agriculture and crop plantation
- The Indonesian Centre for Agricultural Land Resources Research and Development (Balai Besar Sumber Daya Lahan Pertanian), The Ministry of Agriculture
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Land system maps - The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) -
Land cover (time series 1990, 2000, 2003, 2006, 2009 and 2011)
- The Directorate of Inventory and Monitoring of Forest Resources (Direktorat
Inventarisasi dan Pemantauan Sumber Daya Hutan)
DIPSDH (MoF) - Spatial - Non-spatial
Forest utilisation regulations - The Ministry of Forestry - The Ministry of Energy &
Mineral Resources
- The Ministry of Agriculture - Provincial Forestry Service
Office MoF MoEMR MoA FSO - Spatial - Non-spatial
Demographic data (Number of population)
- The National Statistics Agency at central and localbranches
BPS - Non Spatial
Demographic data (Number of poverty people)
- The National Agency for Population and Family Planning Programmes (Badan
Kependudukan dan Keluarga Berencana Nasional)
BKKBN - Non Spatial
Districts and sub-districts data (administrative boundaries, geographic condition etc)
- The National Statistics Agency at central and local branches - The Ministry of Forestry
BPS MoF
- Spatial - Non-spatial
Other data and information related to forestry issues
- The National Statistics Agency
at central and local branches
- The Ministry of Forestry - The Ministry of Energy &
Mineral Resources
- The Ministry of Agriculture - Provincial Forestry Service
Office BPS MoF MoEMR MoA FSO - Non Spatial
Visits to the nearest forest areas from the capital city of every chosen province were arranged to observe land use changes. This observation was made in order to see how much deforestation and forest degradation have altered the existence of forest in the study site areas. A global positioning system (GPS) which included official forest area (forest estate) maps was used to locate forest estate boundaries and non-forest areas. No formal interviews were undertaken with the locals. Figure III-2 shows the field photographs of study sites.
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The locations of forest areas in which to observe land use change were sought from the Provincial Forestry Service Office (Kantor Dinas Kehutanan Provinsi). Meetings with relevant officers to discuss options for field visits were arranged in Kendari (the capital of SE Sulawesi), Banjarmasin (the capital of South Kalimantan) and Banjarbaru, where most South Kalimantan provincial offices are located, and Samarinda (the capital of East Kalimantan). The officers, however, were reluctant to provide information on where illegal activities occur. Criteria applied were:
Field photographs of East Kalimantan (a – c), SE Sulawesi (d – g) and South Kalimantan (h – k): (a) Dipterocarp. Spp Log at Wood Museum in
Tenggarong, Kutai Kartanegara District; (b) Coal Mining within Production Forests, Kutai Kartanegara District; (c) Production Forests at Bukit Bangkirai, Balikpapan Municipality; (d) Land clearing in Conservation Forests, Kendari Municipality; (e) Clove Plantation within Conservation Forests, Kendari; (f) Local people’s activities within Conservation Forests, Kendari; (g) Production Forests, Konawe Selatan District; (h) Rubber Plantation, Barito Kuala District; (i) Logging and mining road infrastructure within Production Forests; (j) Paddy Field, Banjar District; (k) Peat land, Banjar District.
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The nearest forest areas from the capitals;
Forest areas that had been converted into agricultural land, crop plantation areas, transmigration villages, forest concessions, mining sites and other land uses; Good accessibility;
Free of conflicts. This is to minimise risk during field visits.
Vector data of land cover for the years 1990, 2000, 2003, 2006, 2009 and 2011 were obtained from MoF. This study, however, only focused on land cover in 2000 and 2009 as the major resources, although land cover data for 1990 was also used to help understand the trend of forest degradation and deforestation of the study sites.
In dealing with spatial data, there are two types of data to represent the geographical
information of the real world: vector data and raster data. The former provides a vector view, which allocates coordinates (x, y) in the form of point, line or area (polygon) to form a map (O'Sullivan & Unwin, 2010). The latter defines objects on the ground using a grid of small units, called pixels (O’Sullivan & Unwin, 2010). Polygons represent areas that have boundaries
(countries, lakes and forest areas), lines represent linear objects (roads, rivers and pipelines), and points represent subjects with limited spatial extent (this depends on map scale, but can include cities, schools and individual trees) (Ormsby, Napoleon, Burke, Groessl, & Bowden, 2010). Polygons, lines and points are called vector data (Ormsby et al., 2004). Figure III-3 describes vector and raster data.
55