@unpublished{EstevesdeCarvalhoMelodeMatosUmbelinoetal.2021, author = {Esteves de Carvalho, Luiza Marina and Melo, Alessandra and de Matos Umbelino, Glauco Jos{\´e} and Mund, Jan-Peter and Gomes dos Santos, Jhonathan and Rosette, Jacqueline and Silveira, Daniel and Gorgens, Eric Bastos}, title = {Charcoal heaps volume estimation based on unmanned aerial vehicles}, series = {agriRxiv}, journal = {agriRxiv}, publisher = {CABI}, issn = {2791-1969}, doi = {10.31220/agriRxiv.2021.00053}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:eb1-opus-5226}, pages = {21}, year = {2021}, abstract = {The charcoal stock in a forest company is controlled based on the theoretical capacity of the masonry ovens (input) and shipped trucks (output). During the year, the company must monitor the stock for the purposes of accountability reports. This study proposes a more efficient and equally precise survey method that overcomes the challenges of the common monitoring system in Brazil. During this study, a new monitoring method based on digital stereoscopy from UAV images was developed, implemented and evaluated. The results were compared with a traditional topographic survey. A masonry oven's complex containing eight charcoal heaps was flown and surveyed using a multi-engine UAV, with an integrated Global Navigation Satellite System (GNSS) and RTK equipment. Two stereoscopic processing methods were applied: (1) very low quality and (2) high quality to image alignment, reconstruction of the dense cloud, face count and in three-dimensional mesh creation. Low quality products showed geometric deformities when compared to high quality, but resulted in similar estimation to the topographic survey. The results indicated that the charcoal heaps' volume estimation using UAV derived orthomosaics can replace the conventional method of GNSS RTK surveys with considerable gains in stockpile volume accuracy, inventory frequency, and safety. In the case of high accuracy parameterization, improvements in geometric precision and accuracy are also produced.}, language = {en} } @article{EstevesdeCarvalhoMelodeMatosUmbelinoetal.2022, author = {Esteves de Carvalho, Luiza Marina and Melo, Alessandra and de Matos Umbelino, Glauco Jos{\´e} and Mund, Jan-Peter and Gomes dos Santos, Jhonathan and Rosette, Jacqueline and Silveira, Daniel and Gorgens, Eric Bastos}, title = {Charcoal heaps volume estimation based on unmanned aerial vehicles}, series = {Southern Forests: a Journal of Forest Science}, volume = {83}, journal = {Southern Forests: a Journal of Forest Science}, number = {4}, publisher = {Taylor \& Francis}, issn = {2070-2620}, doi = {10.2989/20702620.2021.1997067}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:eb1-opus-5181}, pages = {303 -- 309}, year = {2022}, abstract = {The charcoal stock in a forestry business is controlled based on the theoretical capacity of the masonry ovens (input) and shipped trucks (output). During the year, the company must monitor the stock for accountability reports and internal governance. This paper proposes a more efficient and precise survey method that overcomes the challenges of the common monitoring system in Brazil. In this study, a monitoring method based on digital stereoscopy from UAV images was implemented and evaluated. The results were compared with those of the traditional topographic survey based on RTK equipment. A multi-engine UAV, with an integrated global navigation satellite system (GNSS) and real-time kinematic positioning (RTK) equipment was used to fly over and survey a masonry oven complex containing eight charcoal heaps. Two stereoscopic processing methods were applied: (1) very low quality and (2) high quality to image alignment, reconstruction of a dense cloud, facet count and a three-dimensional mesh creation. Low-quality products showed geometric deformities when compared to high quality, but resulted in estimations similar to the topographic survey. Results indicated that the volume estimation of the charcoal heaps using UAV derived orthomosaics can replace the conventional method of GNSS RTK surveys with considerable gains in stockpile volume accuracy, inventory frequency and labour safety. The high quality processing method registered improvements in geometric precision and accuracy.}, language = {en} } @article{GoergensMundCremeretal.2020, author = {G{\"o}rgens, Eric Bastos and Mund, Jan-Peter and Cremer, Tobias and de Conto, Tiago and Krause, Stuart and Valbuena, Ruben and Estraviz Rodriguez, Luiz Carlos}, title = {Automated operational logging plan considering multi-criteria optimization}, series = {Computers and Electronics in Agriculture}, journal = {Computers and Electronics in Agriculture}, number = {170}, publisher = {Elsevier}, issn = {0168-1699}, doi = {10.1016/j.compag.2020.105253}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:eb1-opus-4423}, year = {2020}, abstract = {Multiple goals should be considered while planning and executing forest management. This study proposes a new multidimensional framework for a precision forestry approach assisted by airborne laser scanning data (ALS). Therefore, successful management operations become a key element in the process of promoting protection through sustainable development. Thirteen relevant variables were derived from ALS data, such as: canopy height, terrain topography, relative vegetation density, forest gaps, slope restrictions, skidder restrictions, load truck restrictions, topographic wetness, flow accumulation, horizontal distance to drainage, vertical elevation from drainage, stream and headspring restrictions. Four different scenarios for the management plan optimization were studied: shortest distance, forest conservation, soil conservation and all combined. Results showed that the detailed forest information from ALS point clouds is useful to indicate regions not suitable for forest operations. Failure to properly consider the different factors involved may result in inadequate infrastructures, lower operational performance and constant re-planning requirements.}, language = {en} }