Applications of Individual Tree Detection (ITD)

Dear Colleagues,

Recent advancements in the data processing sphere and introduction of low-cost Unmanned Aerial Vehicles (UAV) have resulted in proliferation of Individual Tree Algorithm (ITD) applications in areas of forestry and conservation in the past decade. Even though, origins of few of the most prominent underlying principles – such as local maxima and watershed algorithm – supporting ITD techniques can be traced back to 1980s, novel, modified and combined versions of these  algorithms are still being developed, tested widely and expected to extend further in terms of applicability. Ongoing ITD initiatives within the forest science sector include monitoring, mapping and/or modeling forest growth, deforestation, disturbance, recovery, degradation, species diversity, forest health, aboveground biomass, canopy cover, biodiversity conservation, land use land change, climate change impacts, natural resource assessment, pest detection, among others. Even then, there exists a vast void of unexplored opportunities, unaddressed issues and unfilled gaps – such as constraints arising from dense forest canopy structures, time intensive data analysis paradigms, lack of standardization of UAV remote sensing development platforms, species-specific ITD optimization models and long-term large scale forest inventory databases – that solicit urgent attention.

We, hereby invite authors from the broad forest remote sensing domain to consider this SI as a medium to publish their original and/or review articles that explore the applications of ITD algorithms – which can be based on satellite imagery, drone data, discrete return and full waveform LiDAR (Light Detection and Ranging), hyperspectral data and/or sensor fusion. A few of the potential topics, other than the ones mentioned previously, include:

• Tree-level attributes estimation and three-dimensional (3D) canopy structure analysis
• Development of novel ITD algorithms and/or comparison and evaluation of existing ones
• Compare and contrast performance of various remote sensing techniques in terms of ITD abilities
• Data fusion approach for improving tree detection accuracy and characterization
• ITD models transferable from one species to another as well as between disparate spatial scales and locations

Dr. Ana Paula Dalla Corte
Mr. Midhun (Mikey) Mohan
Dr. Mikko Vastaranta
Ms. Shruthi Srinivasan
Dr. Weijia Li
Guest Editors

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