Manokwari Regency has high environmental risks due to the high rate of population growth and increased migration. This condition could affect the biocapacity of forest and land resources as well as the ecological footprint that could fulfill the needs of the community in the Manokwari Regency. This study aimed to assess the bioecological carrying capacity of forest and land, changes in forest cover, and projecting the bioecological carrying capacity for the next 50 years in the Manokwari Regency. A quantitative descriptive approach based on secondary time series data analysis and land cover dynamics analysis was used. The ecological footprint approach was carried out by calculating the ecological footprint, biocapacity, and bioecological carrying capacity. The results showed that the bioecological carrying capacity in 2017 in Manokwari District decreased compared to 2012. Forest degradation tended to decrease at a rate of 372 ha/year. However, deforestation increased at a rate of 1,298 ha/year. The results indicated that the policy of converting forests to permanent non-forest lands in the last five years was very massive. The projected bioecological carrying capacity in the next 50 years showed that forest and land in Manokwari District tend to be overshoot.Keywords: bioecological carrying capacity, change in land use, forests, land, Manokwari
Tree height is an important piece of information in forest management. Cost, time, and effort are some of the limiting factors in extracting tree height values on a large scale. The canopy height model approach through aerial photography using UAV can be used to quickly estimate the height of large-scale trees combined with field measurements. CHM analysis was carried out using spatial statistics to get the maximum tree height value based on the tree canopy. Evaluation of accuracy in the form of statistical tests is used to assess the level of accuracy of the estimation. Photogrammetry results show that the obtained CHM has a resolution of 11.8 cm/pixel with the results of the evaluation of tree height accuracy having an RMSE of 2.4 m, MAE 2.0 m, SDE 3.8 m. The chi-square statistical test shows that the results of the tree height estimation accept H0 and there is a strong relationship between the observed tree height and the estimation through linear regression with an R2 value of 0.67. The broad estimation of height shows that Mansinam Island has a tree height in the range of 7 – 66 m. The dominant tree height is in the 19-30 m class with the number of individuals reaching 1,877 trees. This study shows that CHM obtained from aerial photography using low-cost UAVs is still able to estimate tree height well. For future studies, it is necessary to use a ground control point (GCP) to increase the accuracy of the elevation model and orthophoto.
Unmanned aerial vehicles (UAV) have often been used for various purposes, not only for photography but also have been used for science in various scientific fields, including forestry. UAV has the ability to move freely in the air and record objects on the ground with high spatial resolution and wide area coverage. This study aimed to estimate the diameter at breast height (DBH) based on the image generated from the UAV. UAV was used to obtain aerial photographs taken at an altitude of 150 m above the land surface in four sample areas of 27 ha at the study site. Aerial photos were processed using agisoft photoscan software to produce a Digital Elevation Model (DEM) and orthophoto. Tree crowns were delineated from orthophoto and analyzed to obtain crown area and diameter. DBH measurements in the field were carried out on 206 sample trees used to build a DBH estimator model. The correlation test results showed that the crown diameter has a high correlation with DBH so that this variable was used as an independent variable. The best DBH estimator model was the polynomial model with the equation y = 0.0118744 x² + 1.08835 x + 22.8125, where y is DBH and x is the canopy diameter of the aerial photo interpretation results. Estimating DBH using UAV has several benefits, such as reducing time, cost and labour. Abstrak Unmanned aerial vehicle (UAV) sudah sering digunakan untuk berbagai tujuan, bukan hanya untuk fotografi, namun telah dimanfaatkan untuk sains di berbagai bidang keilmuan, termasuk bidang kehutanan. UAV memiliki kemampuan bergerak dengan bebas di udara dan merekam objek di darat dengan resolusi spasial tinggi, dan cakupan areal yang luas. Penelitian ini bertujuan untuk melakukan pendugaan diameter setinggi dada (DBH) berdasarkan citra yang dihasilkan dari UAV. UAV digunakan untuk memperoleh foto udara yang diambil pada ketinggian 150 m di atas permukaan darat pada empat areal sampel seluas 27 ha di lokasi penelitian. Foto udara diproses dengan menggunakan perangkat lunak agisoft photoscan untuk menghasilkan Digital Elevation Model (DEM) dan ortofoto. Tajuk pohon dideliniasi dari ortofoto dan dianalisis untuk memperoleh luas dan diameter tajuk. Pengukuran DBH di lapangan dilakukan terhadap 206 pohon sampel yang selanjutnya digunakan untuk membangun model penduga DBH. Hasil uji korelasi menunjukkan bahwa diameter tajuk mempunyai korelasi yang tinggi dengan DBH sehingga variable ini digunakan sebagai variable bebas. Model terbaik penduga DBH adalah model polinomial dengan persamaan y = 0,0118744 x² + 1,08835 x + 22,8125, dengan y adalah DBH dan x adalah diameter tajuk hasil interpretasi foto udara. Pendugaan DBH menggunakan UAV memiliki beberapa manfaat seperti mampu mengurangi waktu, biaya dan tenaga kerja.
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