Estimating Primary Forest Attributes and Rare Community Characteristics Using Unmanned Aerial Systems (UAS): An Enrichment of Conventional Forest Inventories
نویسندگان
چکیده
The techniques for conducting forest inventories have been established over centuries of land management and conservation. In recent decades, however, compelling new tools methodologies in remote sensing, computer vision, data science offered innovative pathways enhancing the effectiveness comprehension these sampling designs. Now with aid Unmanned Aerial Systems (UAS) advanced image processing techniques, we never closer to mapping forests at field-based inventory scales. Our research, conducted New Hampshire on complex mixed-species forests, used natural color UAS imagery estimating individual tree diameters (diameter breast height (dbh)) as well stand level estimates Basal Area per Hectare (BA/ha), Quadratic Mean Diameter (QMD), Trees (TPH), a Stand Density Index (SDI) using digital photogrammetry. To strengthen our understanding also assessed proficiency map presence large trees (i.e., >40 cm diameter). We photogrammetry identifying two ways: (1) estimated dbh 40 size threshold (2) random supervised classification combination spectral, textural, geometric features. UAS-based diameter reported an average error 19.7% 33.7%. At level, BA/ha QMD were overestimated by 42.18% 62.09%, respectively, while TPH SDI underestimated 45.58% 3.34%. When considering only stands larger than 9 ha overestimation dropped 14.629%. overall trees, achieved accuracy 85%. efficiency methods offer local managers opportunity better understand their forested ecosystems. Future research into crown detection delineation, especially co-dominant or suppressed will further support efforts.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13152971