PERENCANAAN JALUR TUR WISATA KAWASAN PUSAT KOTA TUA SEBAGAI SALAH SATU PAKET WISATA DI KOTA BANDUNG

Kawasan Pusat Kota Tua merupakan salah satu kawasan yang terletak di Kota Bandung, Jawa Barat. Kawasan Pusat Kota Tua memiliki potensi sebagai kawasan wisata sejarah di Kota Bandung. Banyak peristiwa sejarah yang terjadi di kawasan ini, bangunan, tempat dan monumen di kawasan ini merupakan saksi bisu juga bukti dari perjalanan Kota Bandung maupun Indonesia. Akan tetapi, banyak orang tidak tahu keistimewaan tempat ini dan juga peristiwa dibalik setiap bagian dari kawasan ini, maka dibuatlah suatu konsep perencanaan jalur tur wisata di kawasan ini.Tujuan perencanaan jalur tur wisata di kawasan ini adalah sebagai alat untuk mempermudah pengenalan kawasan ini, baik dari segi nilai sejarah atupun nilai lainnya sehingga wisatawan akan mengapresiasi setiap bangunan bersejarah di kawasan tersebut. Jalur tur wisata adalah suatu rute yang dibuat untuk mengarahkan wisatawan pada objek daya tarik wisata yang bertujuan untuk memperkenalkan dan memberikan informasi setiap objek pada suatu destinasi. Penelitian ini menggunakan metode kualitatif, sedangkan teknik yang digunakan adalah teknik site analysis untuk memudahkan peneliti dalam merencanakan setiap aspek yang terhubung dengan perencanaan jalur tur wista. Aspek yang diteliti adalah Land Use And Tenure, Land Use Regulation, Public Insfratructure, Building And Neighborhood Character, Historic Resources dan Sensory Perception. Dalam penelitian ini peneliti menggunakan metode wawancara untuk mengumpulkan data sebelum diolah menjadi bentuk deskriptif. Berdasarkan hasil penelitian, peneliti menyimpulkan bahwa terdapat potensi wisata sejarah di kawasan tersebut yang berupa 22 bangunan bersejarah. Bangunan-bangunan tersebut dibagi menjadi 3 kategori sesuai dengan nilai dan peristiwa sejarahnya. Jalur tur wisata yang dibuat melewati 22 bangunan bersejarah di kawasan tersebut. Peta wisata yang telah dibuat berjudul “Treasure Map : The Old Gold Bandoeng”. Diharapkan penelitian ini menjadi referensi bagi pembelajaran sejarah dengan menggunakan wisata sejarah sebagai sarana pendidika

Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra.

BACKGROUND:Reduction of carbon emissions from peatlands is recognized as an important factor in global climate change mitigation. Within the SE Asia region, areas of deeper peat present the greatest carbon stocks, and therefore the greatest potential for future carbon emissions from degradation and fire. They also support most of the remaining lowland swamp forest and its associated biodiversity. Accurate maps of deep peat are central to providing correct estimates of peat carbon stocks and to facilitating appropriate management interventions. We present a rapid and cost-effective approach to peat thickness mapping in raised peat bogs that applies a model of peat bottom elevation based on field measurements subtracted from a surface elevation model created from airborne LiDAR data. RESULTS:In two raised peat bog test areas in Indonesia, we find that field peat thickness measurements correlate well with surface elevation derived from airborne LiDAR based DTMs (R2 0.83-0.88), confirming that the peat bottom is often relatively flat. On this basis, we created a map of extent and depth of deep peat (> 3 m) from a new DTM that covers two-thirds of Sumatran peatlands, applying a flat peat bottom of 0.61 m +MSL determined from the average of 2446 field measurements. A deep peat area coverage of 2.6 Mha or 60.1% of the total peat area in eastern Sumatra is mapped, suggesting that deep peat in this region is more common than shallow peat and its extent was underestimated in earlier maps. The associated deep peat carbon stock range is 9.0-11.5 Pg C in eastern Sumatra alone. CONCLUSION:We discuss how the deep peat map may be used to identify priority areas for peat and forest conservation and thereby help prevent major potential future carbon emissions and support the safeguarding of the remaining forest and biodiversity. We propose rapid application of this method to other coastal raised bog peatland areas in SE Asia in support of improved peatland zoning and management. We demonstrate that the upcoming global ICESat-2 and GEDI satellite LiDAR coverage will likely result in a global DTM that, within a few years, will be sufficiently accurate for this application

Creating a Lowland and Peatland Landscape Digital Terrain Model (DTM) from Interpolated Partial Coverage LiDAR Data for Central Kalimantan and East Sumatra, Indonesia

Coastal lowland areas support much of the world population on only a small part of its terrestrial surface. Yet these areas face rapidly increasing land surface subsidence and flooding, and are most vulnerable to future sea level rise. The accurate and up to date digital terrain models (DTMs) that are required to predict and manage such risks are absent in many of the areas affected, especially in regions where populations are least developed economically and may be least resilient to such changes. Airborne LiDAR is widely seen as the most accurate data type for elevation mapping but can be prohibitively expensive, as are detailed field surveys across a broad geographic scale. We present an economical method that utilizes airborne LiDAR data along parallel flight lines (‘strips’) covering between 10% and 35% of the land depending on terrain characteristics, and manual interpolation. We present results for lowland areas in Central Kalimantan and East Sumatra (Indonesia), for which no accurate DTM currently exists. The study areas are covered with forest, plantations and agricultural land, on mineral soils and peatlands. The method is shown to yield DTM differences within 0.5 m, relative to full coverage LiDAR data, for 87.7–96.4% of the land surface in a range of conditions in 15 validation areas, and within 1.0 m for 99.3% of the area overall. After testing, the method was then applied to the entire eastern coastal zone of Sumatra, yielding a DTM at 100 m spatial resolution covering 7.1 Mha of lowland area from 1.45 Mha of effective LiDAR coverage. The DTM shows that 36.3%, or 2.6 Mha, of this area is below 2 m +MSL and, therefore, at risk of flooding in the near future as sea level rise continues. This DTM product is available for use in flood risk mapping, peatland mapping and other applications