Judul: 3D model reconstruction using aerial photo to measure object height
Abstrak: 3D reconstruction, especially for height extraction, using digital aerial photos taken from a non-metric camera and Unmanned Aerial Vehicle (UAV) is a challenging study. The purposes of the study are to determine the factors affect the accuracy of an object’s height reveal from a 3D model and establish procedures to deliver the optimal result. Two or more overlapping aerial photos can be constructed into the 3D model by applying the principles of collinearity and epipolar geometry using 3D reconstruction algorithm. Due to the instability of non-metric digital camera, the camera must be calibrated before 3D reconstruction is processed, in that way the quality of spatial extraction can be then measured. The study is conducted using 24 megapixels resolution Sony NEX7 digital camera and Hexacopter UAV. UAV was flown to a height of 50 m, 60 m and 70 m and placed at a certain position in order to get some height variations of camera. Camera Calibration Toolbox is utilized to calculate intrinsik parameters of the camera and a specific program is developed using MATLAB in order to build the 3D model and to obtain the object’s height. The result validation is done by comparing the height from 3D model with that one measured using Electronic Total Station. The accuracy of the object’s height up to 1 mm successfully achieved, with the largest height prediction error reaches 15.2 cm at 70 m flying height above ground level and average percentage error 4.07 for 20 objects.
Keyword: 3D reconstruction, collinearity, epipolar geometry, UAV

Judul: Height, Diameter and Tree Canopy Cover Estimation Based on Unmanned Aerial Vehicle (UAV) Imagery With Various Acquisition Height
Abstrak: Penerapan penginderaan jauh di bidang kehutanan telah menjadi perkembangan teknologi untuk kegiatan inventarisasi hutan. Citra UAV (Unmanned Aerial Vehicle) adalah salah atu produk penginderaan jauh yang efisien untuk mendapatkan informasi biofisik yang mendekati data lapangan melalui resolusi spasialnya yang tinggi. Oleh karena itu, citra UAV dapat digunakan untuk menginventarisasi kawasan hutan yang luas dan terpencil secara efektif dibandingkan dengan pengukuran konvensional. Sebagian besar hutan tanaman di Indonesia, seperti hutan jati, dikelola oleh Perhutani. Pemantauan individu pohon di wilayah Perhutani yang luas akan efisien dengan menggunakan sensor UAV RGB. Penelitian ini bertujuan untuk mengevaluasi pengaruh variabel tinggi terbang UAV terhadap akurasi pengukuran pohon. Estimasi tinggi tegakan dan tajuk pada aplikasi UAV dihitung dengan Digital Surface Model (DSM), Digital Terrain Model(DTM) dan orthophoto. Kemudian, hasil studi dievaluasi berdasarkan R2 dan RMSE dalam analisis statistik. Hasil penelitian berdasarkan analisis statistik dari R2dan RMSE menunjukkan tinggi observasi pohon dengan tinggi estimasi pohon pada tinggi terbang 100 m memiliki hubungan kombinasi yang baik daripada tinggi terbang 80 m dan 120 m. Konstanta “a” menunjukkan konsistensi antara diameter pohon hasil observasi dan estimasi tinggi pohon yang memiliki nilai pengaruh rata-rata di atas 80%. Selain itu, estimasi tajuk pohon menggunakan ARCI memiliki perbedaan maksimum 9,8% dan bila umur jati semakin tua, maka persentase selisih antara area semak atau rerumputan dengan tutupan tajuk akan semakin tinggi., Application of remote sensing in forestry has become a technological development for forest inventory activities. UAV (Unmanned Aerial Vehicle) imagery is a powerful remote sensing tool to achieve biophysical information close to field data through its high spatial resolution. Therefore, UAV images can be utilized for inventorying the vast and remote forest area effectively compare to conventional measurement. Most of plantation forests in Indonesia, such as teak forest, are managed by Perhutani. Monitoring individual trees covering vast area of Perhutani would be efficient by using UAV RGB sensors. This study aims to evaluate the effect of UAV’s flight height variables to tree measurements accuracy. Stand height and canopy estimation in UAV application were calculated by Digital Surface Model (DSM), Digital Terrain Model (DTM) and orthophoto. Then, the study results were evaluated based on R2 and RMSE in statistical analysis. Based on the results, statistical analysis of R2 and RMSE indicate high tree observations with tree height estimation at high altitude of 100 m (100 ft) have a good combination of combination rather than of 80 m and 120 m. The “a” constant showed the consistency between tree diameter from observation and tree height estimation which has an average effect value in above 80%. In addition, tree crown estimation using ARCI has a maximum difference of 9.8% and when the age of teak being older, so that, the difference percentage between bush or grass area and canopy cover would be higher.
Keyword: forest inventory, tree crown estimation, orthophoto, UAV imagery, UAV RGB sensors

Judul: Theileriosis pada Sapi Akibat Infeksi Theileria Mutans
Abstrak: Theleria mutans pertama kali ditemukan oleh Theiler pada tahun 1906. Theileria mutans pernah dimasukkan dalam genus Nuttalia, Gondoria, dan Babesia, sehingga penyakit yang disebabkan oleh parasit ini mempunyai banyak nama diantaranya adalah Benign bovine theilariosis, Benign bovine gonderiosis, Tzaneen disease, marico calf disease dan Mild gall sickness (Saidu, 1982).
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