Replanting trees helps with avoiding desertification, reducing the chances of soil erosion and flooding, minimizing the risks of zoonotic disease outbreaks, and providing ecosystem services and livelihood to the indigenous people, in addition to sequestering carbon dioxide for mitigating climate change. Consequently, it is important to explore new methods and technologies that are aiming to upscale and fast-track afforestation and reforestation (A/R) endeavors, given that many of the current tree planting strategies are not cost effective over large landscapes, and suffer from constraints associated with time, energy, manpower, and nursery-based seedling production. UAV (unmanned aerial vehicle)-supported seed sowing (UAVsSS) can promote rapid A/R in a safe, cost-effective, fast and environmentally friendly manner, if performed correctly, even in otherwise unsafe and/or inaccessible terrains, supplementing the overall manual planting efforts globally. In this study, we reviewed the recent literature on UAVsSS, to analyze the current status of the technology. Primary UAVsSS applications were found to be in areas of post-wildfire reforestation, mangrove restoration, forest restoration after degradation, weed eradication, and desert greening. Nonetheless, low survival rates of the seeds, future forest diversity, weather limitations, financial constraints, and seed-firing accuracy concerns were determined as major challenges to operationalization. Based on our literature survey and qualitative analysis, twelve recommendations—ranging from the need for publishing germination results to linking UAVsSS operations with carbon offset markets—are provided for the advancement of UAVsSS applications.
Papua New Guinea is a country in Oceania that hosts unique rain forests and forest ecosystems which are crucial for sequestering atmospheric carbon, conserving biodiversity, supporting the livelihood of indigenous people, and underpinning the timber market of the country. As a result of urban sprawl, agricultural expansion, and illegal logging, there has been a tremendous increase in land-use land cover (LULC) change happening in the country in the past few decades and this has triggered massive deforestation and forest degradation. However, only a few studies have ventured into quantifying the long-term trends and their associated spatial patterns—and have often presented contrasting responses. Herein, we intended to assess the extent of deforestation and the rate of urbanization that happened in the past 33 years (1987–2020) in the Bumbu river basin in Papua New Guinea using satellite imagery—for the years 1987, 2002, 2010, and 2020—and Geographic Information System (GIS) tools. On performing image classification, land use maps were developed and later compared with Google Earth’s high-resolution satellite images for accuracy assessment purposes. For probing into the spatial aspects of the land-use change issues, the study area was divided into four urban zones and four forest zones according to the four main cardinal directions centered in the urban and forest area centers of the 1987 image; subsequently, the rate of urban area expansion in each urban zone was separately calculated. From our preliminary analysis and literature survey, we observed several hurdles regarding the classification of regenerative forests and mixed pixels and gaps in LULC studies that have happened in Papua New Guinea to date. Through this communication paper, we aim to disseminate our preliminary results, which highlight a rapid increase in urban extent from 14.39 km2 in 1987 to 23.06 km2 in 2020 accompanied by a considerable decrease in forest extent from 76.29 km2 in 1987 to 59.43 km2 in 2020; this observation favors the presumption that urban and agricultural land expansion is happening at the cost of forest cover. Moreover, strategies for addressing technical issues and for integrating land-use change with various socioeconomic and environmental variables are presented soliciting feedback.
Applications of unmanned aerial vehicles (UAVs) have proliferated in the last decade due to the technological advancements on various fronts such as structure-from-motion (SfM), machine learning, and robotics. An important preliminary step with regard to forest inventory and management is individual tree detection (ITD), which is required to calculate forest attributes such as stem volume, forest uniformity, and biomass estimation. However, users may find adopting the UAVs and algorithms for their specific projects challenging due to the plethora of information available. Herein, we provide a step-by-step tutorial for performing ITD using (i) low-cost UAV-derived imagery and (ii) UAV-based high-density lidar (light detection and ranging). Functions from open-source R packages were implemented to develop a canopy height model (CHM) and perform ITD utilizing the local maxima (LM) algorithm. ITD accuracy assessment statistics and validation were derived through manual visual interpretation from high-resolution imagery and field-data-based accuracy assessment. As the intended audience are beginners in remote sensing, we have adopted a very simple methodology and chosen study plots that have relatively open canopies to demonstrate our proposed approach; the respective R codes and sample plot data are available as supplementary materials.
The wellbeing, socio-economic viability and the associated health of the inhabitant species of any ecosystem are largely dependent on the quality of its water resources. In this regard, we developed a protocol to measure the potential impact of various environmental and anthropogenic factors on runoff quality at 22 water sampling sites across the Bumbu Watershed in Papua New Guinea. For this purpose, we utilized Digital Elevation Models and several GIS techniques for delineation of stream drainage patterns, classification of the watershed based on Land Use/Land Cover, spatial interpolation of rainfall patterns and computation of the corresponding factor runoff. Our study concludes that a variety of potential challenges to surface water quality are possible such as natural geologic and geochemical inputs, runoff accumulation of precipitation and organic matter pollutants. The developed protocol can also accommodate socio-economic factors such as community and household health, sanitation and hygiene practices, pollution and waste disposal. This research lays the foundation for further development of an all-inclusive correlational analysis between the relative importance values of the factors influencing runoff and spatially distributed water quality measurements in the Bumbu basin.
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