Open AccessEstimating mangrove biomass using drone in Karimunjawa Islands
Author(s) -
Hadiwijaya Lesmana Salim,
Novi Susetyo Adi,
Terry Louise Kepel,
Restu Nur Afi Ati
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/561/1/012054
Subject(s) - mangrove , aerial photography , biomass (ecology) , environmental science , drone , forestry , vegetation (pathology) , geography , remote sensing , shore , global positioning system , fishery , ecology , computer science , biology , medicine , telecommunications , genetics , pathology
Research on mangrove forest biomass using drones was conducted in Karimun Jawa Islands in August 2018. Karimunjawa Islands is a conservation area under the management authority of the Ministry of Environment and Forestry (KLHK). However potential environmental stress due to increasing numbers of tourists and aquaculture activityis concerned to degrade mangrove ecosystem in the area. The method used in this study includes aerial photography work using drones and field data collection of forest ecosystems. Aerial photography work consists of stages of preparation, aerial photography and aerial photo processing in the form of photos mosaicking and DSM generating. The mangrove field data obtained were tree diameter (DBH), tree height and mangrove genus. To find out the mangrove biomass, the equation Saenger & Snedaker (1993) is used. The results show that the number of branches of mangrove trees are 853 branches with heights varying between 1 to 15.5 meters and an average height of 4.4 meter. The estimated mangrove biomass in the study site is 82,154 tons/hectare. This study successfully demonstrated that by using relatively low operational cost consumer-grade drone and can help map the characteristics of mangrove vegetation. However, drone technology still has some limitations, including the need to use GPS Geodetic for accurate positioning. Using this supporting technology, it is expected that the position and height of the tree can be measured more accurately.