One of the problems in the development of human resource professionalism so far is related to land issues (boundaries). The purpose of this activity is to provide training on the use of GPS and processing data using Autodesk map software. The training was attended by the village and sub-district staff of Samarinda City, as many as 50 people. The method used is 1) giving theoretical and practical knowledge about data collection and processing 2) assignment of making land boundaries per area, 3) presentation of results in the field and 4) output (boundary map). The results of this activity were: First, all participants of this training activity were very enthusiastic, enthusiastic, and had high motivation to take part in the implementation of the second boundary land making training activity, the participants who succeeded in making a land boundary map of 25 people or 50% of 50 participants. Third, the quality of the maps is quite good. They found differences in boundary map shape between version Samarinda City Bappeda and field data collection. Based on field data from the Bugis Kelurahan staff, the shape of the land boundary map in the Bugis sub-district in Samarinda almost resembles the land boundary map of Samarinda City of 2.5 ha, because Samarinda City Bappeda does not include the Segiri GOR Stadium as an area of Bugis sub-district that should be included as a map of the border. The map results from Samarinda Kota sub-district staff were recombined by sub-district and sub-district lurah to be determined as a map of sub-district Kota Samarinda and displayed in the A0 printout in each of the kelurahan offices located in sub-district Samarinda Kota.

Penyebaran pohon pada hutan produksi yang mengandalkan proses alam maupun penangan manusia. Pemudaan pohon di suatu kawasan hutan bergantung pada tempat tumbuh. Penelitian ini bertujuan untuk mengetahui penyebaran pohon pada 3 kelas kelerengan di Kelurahan Sungai Siring, Kecamatan Samarinda Utara. Metode pengumpulan data menggunakan Sistem Informasi Geografi (GIS), pada tiga kelas kelerengan yaitu datar (0-8%), landai (8-15%) dan agak curam (15-25%). Hasil penelitian menunjukkan bagian timur dengan kelas lereng landai (0-8%) diperoleh 10 jenis dari 9 famili dengan jumlah 34 pohon, kelas lereng datar (8-15%) diperoleh 8 jenis dari 7 famili dengan jumlah 24 pohon, dan kelas lereng agak curam (15-25%) diperoleh 8 jenis dari 7 famili dengan jumlah 20 pohon. Bagian barat dengan kelas lereng datar (0-8%) diperoleh 9 jenis dari 9 famili dengan jumlah 31 pohon, kelas lereng landai (8-15%) diperoleh 10 jenis dari 9 famili dengan jumlah 25 pohon, dan kelas lereng agak curam (15-25%) diperoleh 8 jenis dari 8 famili dengan jumlah 19 pohon.

The advent of unmanned aerial vehicles has improved aerial photography, which is now aided by computer software for data acquisition and processing. These developments allow for accurate aerial photographs of Kebun Raya Universitas Mulamarwan Samarinda (KRUS) for managerial purposes. This study aims to compare the accuracy of horizontal and vertical geometry with Agisoft Photoscan (AP) and Pix4D Mapper (PM) software. The materials consisted of 150 aerial photographs of KRUS with eight ground control points (GCP) and one internal control point (ICP). Data were obtained from nine flight paths with AP and PM software linked to GCP and ICP. These data were processed and compared to manual measurements using linear error (LE) 90 and circular error (CE) 90 criteria. The commission omission equation was used for the object accuracy test on orthophoto. The vertical geometry accuracy test was carried out using the criteria of root mean square error (RMSE) and LE90 values on the digital elevation model. In comparison, the horizontal geometry accuracy test was performed by using the obtained orthophoto based on RMSE and CE90 criteria. The result demonstrated that the horizontal geometry accuracy for AP was higher than PM, indicated by lower RMSE and CE90 values, which were 0.091 versus 0.148 and 0.139 versus 0.224 for AP and PM, respectively. The vertical geometry accuracy was similar, with lower RMSE and LE90 values of 0.169 versus 0.309 and LE90 0.279 versus 0.224 for AP and PM, respectively. Furthermore, AP is a potential tool for KRUS spatial mapping.

Mendapatkan data tanaman yang akurat sesuai dengan kondisi real di lapangan perlu dilakukan kegiatan sensus pokok secara teliti. Pada umumnya hasil kegiatan sensus pokok dituang ke dalam form blangko sensus (staple card). Data yang dihasilkan sering kali tidak akurat. Sebagai upaya untuk menghasilkan data sensus pokok yang lebih akurat, digunakanlah GPS (Global Positioning System) sebagai alat sensus. Kajian ini dilakukan untuk menentukan metode sensus pokok yang efektif dan efisien antara menggunakan staple card dan menggunakan GPS. Metode yang digunakan dalam pelaksanaan kajian ini, yaitu dengan melakukan pengamatan dan observasi di lapangan mengenai kedua metode sensus pokok yang dikaji. Parameter yang diamati yaitu biaya, waktu dan tenaga yang dibutuhkan, serta akurasi data yang dihasilkan masing–masing metode. Hasil kajian menunjukkan bahwa sensus pokok menggunakan GPS akan lebih efisien dan efektif, serta dapat menghasilkan profit yang lebih besar bagi perusahaan yaitu Rp.204.674/ha/tahun.