East–Southeast Asia is currently one of the fastest urbanizing regions in world, with countries such as China climbing from 20 to 50% urbanized just a few decades. By 2050, these are projected add 1 billion people, 90% that growth occurring cities. This population shift parallels an equally astounding amount built-up land expansion. However, spatially-and temporally-detailed information on regional-scale changes urban or distribution do not exist; previous efforts have been either...

Despite women earning similar numbers of graduate degrees as men in STEM disciplines, they are underrepresented upper level positions both academia and industry. Editorial board memberships an important example such positions; membership is a professional honor recognition achievement opportunity for advancement. We surveyed 10 highly regarded journals environmental biology, natural resource management, plant sciences to quantify the number on their editorial boards leadership (i.e.,...

Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales challenging due to the costs logistics of collection. While advances in remote sensing techniques allow surveys unprecedented extents, there remain technical challenges turning sensor into tangible information. Using deep learning methods, we produced an open-source set crown estimates 100 million...

Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree distributions at increasingly greater spatial scales. Classification requires a dataset field observations matched the image, which will often reflect natural distributions, resulting in an imbalanced with many samples for common and few less species. Despite high prevalence datasets multiclass predictions, effect on prediction accuracy landscape abundance has not yet been...

•In ecosystems maintained by low-intensity surface fires, tree bark thickness is a determinant of fire-survival because it protects underlying tissues from heat damage. However, has been unclear whether relatively thick i S: at all heights or only near the ground where damage most likely.•We studied six Quercus species red and white clades, with three characteristic fire-maintained savannas forests infrequent fire. Inner outer (secondary phloem rhytidome, respectively) thicknesses were...

Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is associate sensor data into individual crowns. While dozens of crown detection algorithms have been proposed, their performance typically not compared based on standard or evaluation metrics. There a need for benchmark dataset minimize differences reported results as well support across broad range types. Combining RGB, LiDAR and hyperspectral from the USA National...

Ecology has reached the point where data science competitions, in which multiple groups solve same problem using by different methods, will be productive for advancing quantitative methods tasks such as species identification from remote sensing images. We ran a competition to help improve three that are central converting images into information on individual trees: (1) crown segmentation, identifying location and size of trees; (2) alignment, match ground truthed trees with sensing; (3)...

Remotely sensed data have revealed ongoing reforestation across many tropical landscapes. However, most studies quantified changes between discrete land cover categories that are difficult to relate the continuous in forest structure underlie reforestation. Here, we demonstrate how generalized linear models (GLMs) can predict tree height and canopy from Landsat satellite reflectance a 109 882 ha agricultural landscape of western Panama. We derived airborne Light Detection Ranging (LiDAR)...

Remote sensing is increasingly needed to meet the critical demand for estimates of forest structure and composition at landscape continental scales. Hyperspectral images can detect tree canopy properties, including species identity, leaf chemistry disease. Tree growth rates are related these measurable properties but whether be directly predicted from hyperspectral data remains unknown. We used a single image light detection ranging-derived elevation predict 20 tropical planted in...

Functional ecology has increasingly focused on describing ecological communities based their traits (measurable features affecting individuals' fitness and performance). Analyzing trait distributions within among forests could significantly improve understanding of community composition ecosystem function. Historically, data are generated by (1) collecting a small number leaves from trees, which suffers limited sampling but produces information at the fundamental unit (the individual), or...

Abstract Measuring forest biodiversity using terrestrial surveys is expensive and can only capture common species abundance in large heterogeneous landscapes. In contrast, combining airborne imagery with computer vision generate individual tree data at the scales of hundreds thousands trees. To train models, ground‐based labels are combined reflectance data. Due to difficulty finding rare a landscape, many classification models include most abundant species, leading biased predictions broad...

Remote sensing data provides unique information about the Earth’s surface that can be used to address ecological questions. Linking high-resolution remote field-based requires methods identify objects of interest directly on georeferenced digital images while in field. Mapping individual trees with a GPS often has location error and is focused position tree stem rather than crown, creating mismatch between field pixel information. We describe mapping process uses consumer-grade tablet...

Ecology has reached the point where data science competitions, in which multiple groups solve same problem using by different methods, will be productive for advancing quantitative methods tasks such as species identification from remote sensing images. We ran a competition to help improve three that are central converting images into information on individual trees: 1) crown segmentation, identifying location and size of trees; 2) alignment, match ground truthed trees with sensing; 3)...

Predicting forest recovery at landscape scales will aid restoration efforts. The first step in successful is tree recruitment. Forecasts of recruit abundance, derived from the landscape-scale distribution seed sources (i.e., adult trees), could assist efforts to identify sites with high potential for natural regeneration. However, previous work revealed wide variation effect on seedling positive no effect. We quantified relationship between and recruits predicted where recruitment would...

The ecology of forest ecosystems depends on the composition trees. Capturing fine-grained information individual trees at broad scales provides a unique perspective ecosystems, restoration, and responses to disturbance. Individual tree data wide extents promises increase scale analysis, biogeographic research, ecosystem monitoring without losing details species abundance. Computer vision using deep neural networks can convert raw sensor into predictions canopy through labeled collected by...

Hyperspectral images can be used to identify savannah tree species at the landscape scale, which is a key step in measuring biomass and carbon, tracking changes distributions, including invasive species, these ecosystems. Before automated mapping performed, image processing atmospheric correction often potentially affect performance of classification algorithms. We determine how three techniques (atmospheric correction, Gaussian filters, shade/green vegetation filters) prediction accuracy...

Abstract Forests provide essential biodiversity, ecosystem and economic services. Information on individual trees is important for understanding the state of forest ecosystems but obtaining individual-level data at broad scales challenging due to costs logistics collection. While advances in remote sensing techniques allow surveys unprecedented extents, there remain significant technical computational challenges turning sensor into tangible information. Using deep learning methods, we...

Abstract Functional ecology has increasingly focused on describing ecological communities based their traits (measurable features affecting individuals fitness and performance). Analyzing trait distributions within among forests could significantly improve understanding of community composition ecosystem function. Historically, data are generated by (1) collecting a small number leaves from trees, which suffers limited sampling but produces information at the fundamental unit (the...

With the greater availability of imaging spectrometer data, vegetation species classification in presence outlier and ambiguous spectra is an increasingly important poorly addressed problem. At large scales, assuming that all test are from one training classes unrealistic. An attractive resolution these problems possibility theory, which axiomatic system, like probability represents uncertain labels outliers ambiguities more flexibly. In this letter, two popular probabilistic algorithms,...

Hyperspectral remote sensing can be a powerful tool for detecting invasive species and their impact across large spatial scales. However, studies of invasives rarely occur multiple seasons, although the properties often change seasonally. This may limit detection using through time. We evaluated ability hyperspectral measurements to quantify coverage plant invader its on senesced canopy equivalent water thickness (EWT) seasons. A portable spectroradiometer was used collect data in field...

Abstract Delineating and classifying individual trees in remote sensing data is challenging. Many tree crown delineation methods have difficulty closed-canopy forests do not leverage multiple datasets. Methods to classify species are often accurate for common species, but perform poorly less when applied new sites. We ran a science competition help identify effective of crowns classification determine identity. This included from sites assess the methods’ ability generalize learning across...

Despite women earning similar numbers of graduate degrees as men in STEM disciplines, they are underrepresented upper level positions both academia and industry. Editorial board memberships an important example such positions; membership is a professional honor recognition achievement opportunity for advancement. We surveyed 10 highly regarded journals environmental biology, natural resource management, plant sciences to quantify the number on their editorial boards leadership (i.e.,...

Despite women earning similar numbers of graduate degrees as men in STEM disciplines, they are underrepresented upper level positions both academia and industry. Editorial board memberships an important example such positions; membership is a professional honor recognition achievement opportunity for advancement. We surveyed 10 highly regarded journals environmental biology, natural resource management, plant sciences to quantify the number on their editorial boards leadership (i.e.,...

Automated individual tree crown (ITC) delineation plays an important role in forest remote sensing. Accurate ITC benefits biomass estimation, allometry and species classification among other related tasks, all of which are used to monitor health make decisions management. In this paper, we introduce Neuro-Symbolic DeepForest, a convolutional neural network (CNN) based algorithm that uses neuro-symbolic framework inject domain knowledge (represented as rules written probabilistic soft logic)...