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Indonesian Journal of Geography
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325
Articles
Current achievements to reduce deforestation in Kalimantan

Wegscheider, Stephanie, Purwanto, Judin, Margono, Belinda Arunarwati, Nugroho, Sigit, Budiharto, Budiharto, Buchholz, Georg, Sudirman, Ruandha Agung

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

Indonesia has developed its forest reference emission level (FREL), using a historical reference period of 1990-2012. Based on official Ministry of Environment and Forestry (MoEF) data, this paper analyses gross deforestation rates and emissions from deforestation in the five provinces of the island of Kalimantan which occurred in the time after 2012, i.e. 2013 until 2015, and puts them in relation to the average annual deforestation and emission rates of each province in the reference period. Even though the overall linear trend of deforestation and emission rates in Kalimantan from 1990 until 2015 goes down, this trend is not reflected in all of the five provinces equally. West and North Kalimantan’s rates even seem to be on the rise. The potentials to achieve emission reduction targets thus remain unequal for each province in Kalimantan Island.

Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan

Arjasakusuma, Sanjiwana, Pribadi, Uji Astrono, Seta, Gilang Aria

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

The accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simple manner. We measured the accuracy by constructing area-proportion error matrix from 388 random sample points and assessed the consistency analysis by looking at the spatial pattern of deforestation and regrowth from built-up area, roads, and rivers from 2010 – 2015 in Katingan district, Central Kalimantan. Accuracy assessment showed that those 3 datasets indicate low to medium accuracy level in which the highest accuracy was achieved by Claslite who produced 71 % ± 5 % of overall accuracy. The consistency analysis provides a similar spatial pattern of deforestation and regrowth measured from the road, river, and built-up area though their distance sensitivity are different one to another. 

Implementing Landslide Susceptibility Map at Watershed Scale of Lompobattang Mountain South Sulawesi, Indonesia

Rasyid, Abdul Rachman, Bhandary, Netra Prakash, Yatabe, Ryuichi

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

This study attempts to predict future landslide occurrence at watershed scale and calculate the potency of landslide for each sub-watershed at Lompobatang Mountain. In order to produce landslide susceptibility map (LSM) using the statistical model on the watershed scale, we identified the landslide with landslide inventories that occurred in the past, and predict the prospective future landslide occurrence by correlating it with landslide causal factors. In this study, six parameters were used namely, distance from fault, slope, aspect, curvature, distance from river and land use. This research proposed the weight of evidence (WoE) model to produce a landslide susceptibility map. Success and predictive rate were also used to evaluate the accuracy by using Area under curve (AUC) of Receiver operating characteristic (ROC). The result is useful for land use planner and decision makers, in order to devise a strategy for disaster mitigation.

Sea Level Rise of Sumatera Waters based on Multi-Satellite Altimetry Data

Khasanah, Isna Uswatun

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

The information of sea level rise was needed in the Indonesia as archipelago country to management risk and development coastal area. This research study took in West Sumatra waters, because the majority people have lived in coastal area and some areas is located below 100 m above Mean Sea Level (MSL). The sea level data was taken from multi-satellite altimetry, they are Topex/Poseidon, Jason-1, and Jason-2. The period of data started from 1993 until 2015.Preliminary data processing of satellite altimetry was done by global test and post-processing of satellite altimetry data. The sea level rise analysis done by linear regression methods. Linear regression formula of sea level rise in West Sumatra Waters during the period was  y = 1.586 + 0.0000113x. The change of sea level during period 1993 until 2015 was 3.394 cm with mean sea level rise value was 1.35 mm/year

Applying GIS in Analysing Black Spot Areas in Penang, Malaysia

Wan Hussin, Wan Muhammad Taufiq, Masron, Tarmiji, Nordin, Mohd Norarshad

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

This study aims to analyze fatal accident rate involving all vehicle types in the North East District of Penang. It covers fatal accident data within the duration of three years from 2011 till 2013. The primary objective is to analyze the spatial pattern and fatal accident black spot areas using Geographic Information System (GIS) application. Average Nearest Neighbor (ANN) tool is used to analyze fatal accident spatial pattern, while Kernel Density Estimation (KDE) method is utilized for fatal accident analysis. The Fatal Accident rates in 2011, 2012 and 2013 were the highest with each accounted up to 90, 88 and 91 cases. The result of ANN shows that the fatal accident pattern for 2011, 2012 and 2013 is clustered with null hypothesis rejected. The KDE analysis result shows that most fatal accident black spot areas happened at main road areas or segments.

An Overview of Indonesia’s Maritime Strategy

suseto, buddy, Othman, Zarina, Mohd Razalli, Farizal Bin

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

As one of the consent maritime on earth, Indonesia has no maritime strategy. Maritime strategy is important not only to protect state’s maritime pathway, but also as part of a national strategy. This article is designed to provide an understanding way for the Indonesian readers to urgently prepare and design a maritime strategy. It is argued that a maritime strategy for Indonesia is needed because of the changing landscape of the international threat such maritime security nontraditional issues. It affects the international trade through the Malacca Strait, Sunda Strait, and Lombok Strait. Data for the articles have been collected from secondary reliable sources. The Early finding of the study suggests that Indonesia needs to shape a maritime strategy to reduce threats at sea and guarantee the security most importantly in the archipelagic sea-lanes (ASL) as an international route. In conclusion, a brief overview of the study indicates that Indonesia urgency needs to establish a maritime strategy.

Assessing the Potential of LAPAN-A3 Data for Landuse/landcover Mapping

Zylshal, Zylshal, Wirawan, Rachmad, Kushardono, Dony

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

LAPAN-A3 / LAPAN-IPB is the third generation of micro-satellite developed by Indonesian National Institute of Aeronautics and Space (LAPAN). The satellite carries a multispectral push-broom sensor that can record the earth's surface at the visible and near-infrared spectrum. Being launched in June 2016, there has no been many publications related to the use of LAPAN-A3 multispectral data for landuse/landcover (LULC) mapping. This paper aims to provide information regarding the use of LAPAN-A3 data for the LULC extraction maximum likelihood algorithm as well as neural network and then evaluate the results. The LAPAN-A3 image was geometrically corrected by using Landsat-8 OLI image as reference data. Three test areas with a size of 1200x945 pixels are then selected for pixel-based classification with the two aforementioned algorithms. For comparison, both LAPAN-A3 and Landsat-8 data were classified for 3 test areas. Accuracy assessment was performed on both datasets using manually interpreted SPOT-6 Pansharpened image as reference data. Preliminary results showed that LAPAN-A3 were able to extract  10 different LULC classes, comprises of built-up area, forest, rivers, fishponds, shrubs, wetland forests, rice fields, sea, agricultural land, and bare soil. The overall accuracy of LAPAN-A3 data is generally lower than Landsat-8, which ranges from 49.76% to 71.74%. These results illustrate the potential of LAPAN-A3 data to derive LULC information. The lack of necessary parameters to perform radiometric correction and blurring effect are several issues that need to be solved to improve the accuracy LULC. 

Well Water Site Selection at Local Scale Using Geographical Information System for Flood Victim in Malaysia

See, Koh Liew, Nasir, Nayan, Yazid, Saleh, Mohmadisa, Hashim, Hanifah, Mahat, Zullyadini, A. Rahaman

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

Clean water supply is a major problem among flood victims during flood events. This article aims to determine the sites of well water sources that can be utilised during floods in the District of Kuala Krai, Kelantan. Field methods and Geographic Information Systems (GIS) were applied in the process of selecting flood victim evacuation centres and wells. The data used were spatial data obtained primarily, namely the well data, evacuation centre data and flood area data. The well and evacuation centre data were obtained by field methods conducted to determine the position of wells using global positioning system tools, and the same for the location of the evacuation centres. Information related to evacuation centres was obtained secondarily from multiple agencies and gathered into GIS as an evacuation centre attribute. The flood area data was also obtained via secondary data and was digitised using the ArcGIS software. The data processing was divided into two stages, namely the first stage of determining the flood victim evacuation centres to be used in this research in a structural manner based on two main criteria which were the extent to which an evacuation centre was affected by the flood and the highest capacity of victims for each district with the greatest impact to the flood affected population. The second stage was to determine the location of wells based on three criteria, namely i) not affected by flood, ii) the closest distance to the selected flood victim evacuation centre and iii) located at different locations. Among the main GIS analyses used were locational analysis, overlay analysis, and proximity analysis. The results showed that four (4) flood evacuation centres had been chosen and matched the criteria set, namely SMK Sultan Yahya Petra 2, SMK Manek Urai Lama, SMK Laloh and SK Kuala Gris. While six (6) wells had been selected as water sources that could be consumed by the flood victims at 4 evacuation centres in helping to provide clean water supply, namely Kg. Keroh 16 (T1), Kg. Batu Mengkebang 10 (T2), Lepan Meranti (T3), Kg. Budi (T4), Kg. Jelawang Tengah 2 (T5) and Kg. Durian Hijau 1 (T6). With the presence of the well water sources that can be used during flood events, clean water supply can be distributed to flood victims at the evacuation centres. Indirectly, this research can reduce the impact of floods in the future, especially in terms of clean water supply even during the hit of a major flood.

Digital Interpretability of Annual Tile-based Mosaic of Landsat-8 OLI for Time-series Land Cover Analysis in the Central Part of Sumatra

Dimyati, Ratih Dewanti, Danoedoro, Projo, Hartono, Hartono, Kustiyo, Kustiyo, Dimyati, Muhammad

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

This paper presents an interoperability of annual tile-based mosaic (MTB) images, as well as a verification of the validity of the model for the time series land cover analysis purposes. The primary data used are MTB image of Landsat-8 of the central part of Sumatra, acquired from January 2015 to June 2017. The method used for the interoperability validation is the digital analysis of three-years time series land cover. The classification was performed with four band spectral groups. Training samples are taken from the image of 2016. The results are then reclassified to improve the overall accuracy score based on Jefferies Matusita (JM) distance. The interoperability can be measured by the average of overall accuracy (AOA) score, namely Good (scores > 80%), Fair (70.0% -79.9%), and Bad (< 70%). The results show that the use of the groups Bands 6-5-4-3-2 performs the consistent accuracy level of Good with an AOA score of 86% for six classes object. Whereas the use of the groups Bands 6-5-4-3-2, Bands 6-5-4, and Bands 6-5 shows the consistent accuracy level of Good up to four classes object with an AOA score of 89%, 82%, and 81%, respectively. It means that the annual mosaic image of MTB model is accepted for the image interoperability with an AOA score of > 80% for six and four classes object. Thus the most efficient for interoperability is the use of Bands 6-5 to analyze four class object of land cover. 

Percent of Building Density (PBD) of Urban Environment: A multi-index Approach Based Study in DKI Jakarta Province

Ardiansyah, Ardiansyah, Hernina, Revi, Suseno, Weling, Zulkarnain, Faris, Yanidar, Ramadhani, Rokhmatuloh, Rokhmatuloh

Indonesian Journal of Geography Vol 50, No 2 (2018): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

This study developed a model to identify the percent of building density (PBD) of DKI Jakarta Province in each pixel of Landsat 8 imageries through a multi-index approach. DKI Jakarta province was selected as the location of the study because of its urban environment characteristics.  The model was constructed using several predictor variables i.e.  Normalized Difference Built-up Index (NDBI), Soil-adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI), and surface temperature from thermal infrared sensor (TIRS). The calculation of training sample data was generated from high-resolution imagery and was correlated to the predictor variables using multiple linear regression (MLR) analysis. The R values of predictor variables are significantly correlated. The result of MLR analysis shows that the predictor variables simultaneously have correlation and similar pattern to the PBD based on high-resolution imageries. The Adjusted R Square value is 0,734, indicates that all four variables influences predicting the PBD by 73%.

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