Archive for June, 2010

Master Thesis : Spasial Modeling for Habitat Suitability of Sumatran Tiger (Panthera tigris sumatrae) in Bukit Tigapuluh National Park and Its Surrounding areas)

Astri Meirani Mulyono Putri1), Lilik Budi Presetyo2), Abdul Haris Mustari2

(1) Graduate student of Biodiversity Conservation,Dept.Forest Resources Conservation, Forestry Faculty – IPB, (2) Supervisor & co-supervisor (Dept. Forest Resources & Conservation, Forestry Faculty )

Sumatran tiger is one of eight sub-species tiger in the world.Their distribution is limited in island of Sumatra. Their habitat and population were threatened by land conversion activities and also legal and illegal logging. Bukit Tigapuluh National Park is part of Bukit Tigapuluh landscape. This area designated as a global protection priority area for Sumatran tigers. Therefore, it is an urgent need to study their habitat suitability for management purposed. Geographical Information System and Remote Sensing can be used to achieve the objective. It can be applied for large area scale. This study aims to identify broad areas that are still suitable for tiger habitat. In the same time they can be utilized also to clarify the impact of land use change on sumatran tiger habitats. The logistic regression equation was used for habitat suitability prediction models. Logistic regression utilized absence and presence data. Presence of tiger indicated by location of the camera trap that catched tiger as well as secondary markers, suh as traces, scrape and dirt. Pseudo-absence data was set randomly at a buffer outside the area of presence. One hundred and six pairs of presence and pseudo-absence data used in this study. Environmental data wasobtained from digital maps, ASTER GDEM, and Landsat 5TM. Six predictor variables were used are elevation, slope, distance from river, distance from roads, distance from settlements and NDVI. Research results indicate that altitude, slope, distance from rivers and NDVI have a significant influence on the models. Habitats with low suitability (201.265,56 ha) is greater than medium suitability (52.754,49 ha) and the high suitability is 263.164,95 ha. Extrapolation models on the time sequence image shows the influence of forest land cover changes on the appropriate area for tiger habitat.

Keywods: habitat suitability, logistic regression, Sumatran tiger, Bukit Tigapuluh National Park, GIS and RS

Correspondence Author : Astri Meirany Mulyono Putri (

Master Thesis :Analysis of Changes in Food Biomass of Javan Rhinos Based Land Cover Change in Ujung Kulon National Park

Yudhi Rusbiandi (1), Lilik Budi Prasetyo (2), Burhanuddin Masy’ud (2)

(1) Mahasiswa S2 Magister Profesi Konservasi Keanekaragaman Hayati, Sekolah Pascasarjana IPB, (2) Ketua dan anggota komisi pembimbing


Above ground biomass or standing stock is weight of organic material per unit area in the components of the ecosystem at a particular time. Food is one component of the habitat that is essential for life. It is one limiting factor for growth of wildlife populations including Javan Rhino in Ujung Kulon National Park. Purpose of this study are: 1) estimate the amount of foodplant biomass of Javan Rhino potential to be eaten in the Ujung Kulon Peninsula, 2) determine changes in total foodplant biomass of Javan Rhino based land cover map of the Ujung Kulon Peninsula region in 1992 and 2008 by using remote sensing and GIS (Geographic Information System). Based on analysis of foodplant biomass of Javan Rhino, total biomass in the form of land cover type of forest, bush and mangroves amounted to 16.09 tons/hectare, 23.42 tons/ha and 0.65 tonnes/ha, respectively. Total plant biomass feed Javan Rhino in Ujung Kulon Peninsula region in 1992 amounted to 512,464.86 tons and in 2008 amounted to 497,974.25 tons. Decreasing the total plant biomass diets at 14490.62 tons, or about 905.66 tons/year.
Keywords: biomass, javan rhino, Ujung Kulon National Park, land cover


Lilik B.Prasetyo(1), Agus P. Kartono(1), Haris Syahbuddin(2), Samin Botanri (3), and Agus Jacob(3), Beni Okarda (4)

(1)Bogor Agricultural University, Bogor (2) Ministry of Agriculture, (3) Darusalam University-Ambon, (4) Master Degree Program of Information Technology for Natural Resources Management-IPB

Keywords : Spatial Modelling, Metroxylon spp, Distribution, Sago palm, GIS & Remote Sensing

Area of Sago palms in Indonesia is the largest among Sago starch production countries such as Papua New Guinea, Malaysia and Thailand. It was estimated around 50% of Sago palms of the world is situated in Indonesia, which is distributed in Sumatra, Maluku & Papua. Sago palm area in Maluku is estimated of about 30.1 thousand hectare (Mulyono & Suward,2000), meanwhile Ruhendi (2000) has estimated with higher figure (800 thousand hectare). In other publication Louhenapessy (1992) has annouced lower figure (26 thousand hectare).

Sago palms (Metroxylon spp) is multi-function trees. Its starch have been utilized by rural community at Papua, Maluku and other eastern part of Indonesia as staple food. It can be utilized also for raw material of food industries, plywood and also for bioenergy. Since two decades ago, food habit/preference of community has shifted to rice, which lead to decrease sago starch consumption, and its habitat conversion.

Based on the above situation, it is an urgent need to estimate actual Sago palm distribution and its potential habitat for management purposes. Up to now, estimation of Sago palm distribution was based on terestrial survei & sampling, and therefore its accuracy is questioned. Remote Sensing and Geographical Information System (GIS) can be utilized to enhance the accuracy of invetory purposes. The research objectives are as follows (1) develop distribution map of sago palms in Seram Island based on satellite imagery, (2) develop spatial model of sago palms distribution by GIS. Classification of Landsat TM was conducted by Supervised classification with maximum likelihood technique. Meanwhile, its habitat prediction was modeled by logistic regression.

It was estimated that area of sago in Seram island was about 17 902 hectare.It distributed at low altitude (250 m dpl)(left figure, green colour indicated Sago habitat distribution prediction).

Logistic regression model of its habitat distribution is presented in equation below :

P =1/1 + e -(-3.698+(3.384x[elevation])-( 0.639x[slope])+(0.398*[river distance])+(0.359* [coastline distance)-(0.150* [soil type]))

Based on Hosmer and Lemeshow Test model was valid. However, Nagelkerke R Square of the model was very low ( 35%). It means that there are other factors contributed to the sago distribution. Regarding role of each variable, variable of elevation,slope, distance from river and coastline had significance impact on its habitat distribution. further analysis showed that utilizing sago distribution derived from landsat as validation, accuracy of the model was about 76 %.

Paper was presented in Plant Ecology and Diversity Observation Network and Capacity Building in Indonesia (16 – 17 July 2010, Univ.Udayana- Bali)