Application of Forest Canopy Density (FCD) Model for the Hotspot Monitoring of Crown Fire in Tebo, Jambi Province

<p><em>Indonesia is one of the owners of the 9th largest forest area in the world. Forest area in Indonesia reaches 884,950 km². Tebo Regency is a regency in Jambi Province which has a wide forest area of 628,003 Ha. However, this forest area has been reduced due to the conversion of functions of Industrial Plantation Forests (HTI), oil palm plantations, and forest clearing activities for both settlements and plantations which led to the phenomenon of forest and land fires (karhutla). This study aims to get a better knowledge of crowns of fire potential locations in forest areas using remote sensing technology. Remote sensing data used in this study is from the satellite imagery </em><em>of </em><em>Landsat 8 OLI - TIRS in 2019. Remote sensing data is used to produce a Forest Canopy Density (FCD) model that can be overlap</em><em>ped with</em><em> a hotspot location, so the crown fire potential locations will be explored in the forest area of Tebo Regency, Jambi Province. Identification of hotspot patterns in Forest Areas was analyzed using spatial analysis. The results of this study are useful for the government as the information of the hotspot area as the cause of fires in the Forest Region of Tebo Regency Jambi Province.</em></p><strong><em>Keywords</em></strong><em>: Spatial Analysis, Forest Cover Density (FCD), Hotspots, Forest Areas, Remote Sensing</em>

Spatial Distribution Patterns Analysis of Hotspot in Central Kalimantan using FIMRS MODIS Data

<p><em>One of the ways to observe the </em><em>hotspot created by </em><em>forest fires in Indonesia </em><em>is </em><em>through </em><em>Remote sensing imagery, such as MODIS, NOAA AVHRR, etc</em><em>. </em><em>Central Kalimantan is one of the areas in Indonesia with the highest hotspot data. In this research, MODIS FIRMS hotspot data in Central Kalimantan collected from 2017 – 2019, covering 13 districts: South Barito, East Barito, North Barito, Mount Mas, Kapuas, Katingan, Palangkaraya City, West Kotawaringin, East Kotawaringin, Lamandau, Murung Raya, Pulang Pisau, Seruyan, and Sukamara. That is four aspects that this research evaluated: 1) evaluating the spatial pattern using the Nearest Neighbor Analysis (NNA); 2) evaluate the hotspot density appearance using Kernel Density; and 3) correlation analysis between rainfall data and MODIS FIRMS. As a result, the hotspot in Central Kalimantan shows a clustered pattern. While the natural breaks KDE algorithm shows the most relevant result to represent the hotspot distribution. Finally, the hotspot is low correlated with rainfall; however, is see that most of the hotspot (~90%) appeared in low rainfall month (less than 3000 mm/month).</em></p><p><strong><em>Keywords</em></strong><em>: Forest fire, Hotspot, NNA, Kernel density, Central Kalimantan</em></p>

Designing the special pilot economic zone on peatlands

<p><em>Peatland restoration projects in tropical countries could prevent environmental disasters such as peat fires. In Indonesia, one of peatland restoration activities is the revitalization of the livelihoods of communities around peatlands. Nevertheless, this activity is still lacking in reducing the environmental pressures from the communities on peatland. We aim to find a comprehensive strategy to design a sustainable bioeconomy on peatlands. This study draws on spatial, qualitative, and quantitative data from the literature, project and policy documents, open-source web application, observations from the field and meetings; and interviews with key stakeholders at national level and three Indonesian provinces. We found that an ecosystem-based special pilot economic zone (SPEZ) is a potential proposal that can provide a framework for a sustainable peatland bioeconomy. We suggests seven phases for planning and implementation of the SPEZ; 1. Preparing its spatial planning to support its legal aspects; 2. Field observation to derive biophysical information of the location and determining peatland suitability; 3. Identifying target group, paludiculture commodities and alternative livelihoods; 4. Analyzing the value chain, market demand and conducting a cost-benefit analysis; 5. Natural capital accounting; 6. Designing social innovation to trigger investment and market chain; and 7. Community engagement. From our study in Riau, South Sumatra, and Central Kalimantan, each of the phase present different challenges and opportunities especially in terms of regulation for land permit, institutional arrangement, market chain for peat products, remuneration of external benefits, and perception and capacity of community for cultivation on peat.</em></p><p><strong><em>Keywords</em></strong><em>: </em><em>L</em><em>ivelihood, peatland, paludiculture, special pilot economic zone, Indonesia. </em></p>

Characteristics of Transit Oriented Development Area (Case Study: Jakarta MRT)

<p class="Abstract"><em>The city of Jakarta is famous because the traffic jams, so the transportation sector needs special attention. Based on data from the Jakarta Transportation Management Agency, of the 47.5 million trips in Jakarta City, only 24% used public transportation. The Jakarta City Government has provided public transportation modes, namely the MRT. This mode of transportation offers a basic concept of TOD, area around the 400 meter buffer from the station can be accessed by walking. This concept has been developed in various cities on the Continent of Europe and America. The space conditions in a TOD based area can be assessed using the TOD Index measurement. Each TOD Index criterion has its own indicators. This study uses 8 criteria and 18 indicators that can measure the value of the TOD Index at each MRT station. Processing data is using spatial processing so that each indicator can be analyzed holistically from a spatial perspective. The TOD area of Bendungan Hilir Station is a station with the highest TOD value, amounting to 0.71. TOD Station in Lebak Bulus Station takes the lowest TOD Index value of 0.31. The TOD Index’s value at each station can be influenced by the weight of each indicator and criteria. Through this research, it is hoped that each policyholder can pay attention to every indicator on the station that is deemed necessary to be improved if needed for a TOD-based area that is in accordance with the concept of a smart city.</em></p><p class="Abstract"><strong><em>Keywords:</em></strong><em> TOD, space, TOD Index, smart city, 6Ds</em></p>

GIS-Based Spatial Model for Habitat Suitability of Babirusa (Babyrousa celebensis), in Gorontalo Province

<p>Babirusa (<em>Babyrousa celebensis</em>) is an endemic animal from Gorontalo Province whose population is declining day by day due to poaching, land clearing, and selling babirusa meat in traditional markets in Gorontalo Province. Since 1931 this species has begun to be protected in Indonesia, and since 2008, <em>International Union for Conservation of Nature (</em>IUCN) named the babirusa species as a vulnerable category. This study aims to determine the suitability of babirusa habitat areas (<em>Babyrousa celebensis)</em> in Gorontalo Province with a Geographic Information System (GIS) approach and to determine the relationship of physical characteristics for the habitat of the babirusa habitat in Gorontalo Province. The variables are land use, slope, and elevation. The method used is GIS spatial modeling with overlay analysis. From the results of the analysis, it has concluded that a suitable area as a babirusa habitat is only about 33% of the total area of Gorontalo Province and there are types of land use in the wilderness and swamps at an elevation of 0-500 msl with sloping 0-8%. The validation test shows that Coefficient kappa is 0.16 and overall accuracy is 58%. Therefore, further research is needed by adding other variables to delineate the spatial distribution of babirusa.<em></em></p><p><strong><em>Keywords</em></strong><em>: babirusa, habitat, GIS, suitability area</em></p>