Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

Garrity, S. R.; Allen, Craig D.; Brumby, Steven P.; Gangodagamage, C.; McDowell, Nate G.; Cai, D. Michael

doi:10.1016/j.rse.2012.10.029

Cited by 60 publications

(38 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If different levels of damage or mortality are not distinguished, overall accuracies are usually higher. For example, [17] identified living and dead tree pixels of pinyon-juniper woodlands based on Quickbird and WV-2 images with 98% overall accuracies. Hyperspectral imagery was used by [16], which obtained high overall accuracies between 84 and 96% for detecting dead spruce, and separation between the healthy trees and the dead trees with a 94%-97% accuracy.…”

Section: Classification Accuraciesmentioning

confidence: 99%

“…Besides coastal, GNDVI, the additional RSIs GR, and RR (red ratio) are also useful for identifying tree species. The benefits of applying RSIs have been shown in several studies to detect tree stress and mortality, where most used NDVI or derivations of it, and ratios of red and green bands (e.g., [7,17,57,82]). Thus, also in this study, NIR, NDVI, RedEdge, and the green-related ratios and variables were the most important predictors for distinguishing between different damage levels.…”

Section: Extraction Of Explanatory Variablesmentioning

confidence: 99%

“…To minimize the large numbers of explanatory variables of the three sets, reducing the variable space dimension by using a LDA was successfully tested. Other tree species and tree mortality classification studies (e.g., [17,25]) have also shown that a reduction of variables by LDA facilitates the straightforward interpretation of the classification model output, tuning and performance.…”

Section: Extraction Of Explanatory Variablesmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

et al. 2014

View full text Add to dashboard Cite

Forest disturbances in central Europe caused by fungal pests may result in widespread tree mortality. To assess the state of health and to detect disturbances of entire forest ecosystems, up-to-date knowledge of the tree species diversity is essential. The German state Mecklenburg-Vorpommern is severely affected by ash (Fraxinus excelsior) dieback caused by the fungal pathogen Hymenoscyphus pseudoalbidus. In this study, species diversity and the magnitude of ash mortality was assessed by classifying seven different tree species and multiple levels of damaged ash. The study is based on a multispectral WorldView-2 (WV-2) scene and uses object-based supervised classification methods based on multinomial logistic regressions. Besides the original multispectral image, a set of remote sensing indices (RSI) was derived, which significantly improved the accuracies of classifying different levels of damaged ash but only slightly improved tree species classification. The large number of features was reduced by three approaches, of which the linear discriminant analysis (LDA) clearly outperformed the more commonly used principal component analysis (PCA) and a stepwise selection method. Promising overall accuracies (83%) for classifying seven tree species and (73%) for classifying four different levels of damaged ash were obtained. Detailed tree damage and tree species maps were visually inspected using aerial images. The results are of high relevance for forest OPEN ACCESSRemote Sens. 2014, 6 4516 managers to plan appropriate cutting and reforestation measures to decrease ash dieback over entire regions.

show abstract

Section: Classification Accuraciesmentioning

confidence: 99%

Section: Extraction Of Explanatory Variablesmentioning

confidence: 99%

Section: Extraction Of Explanatory Variablesmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Over the last 17 years, piñon-juniper woodlands have experienced dry conditions, punctuated by two extreme drought years (1996 and 2002) that resulted in high piñon mortality across the southwestern United States (Mueller et al 2005;Breshears et al 2008;Garrity et al 2013). Most importantly, drought was an evolutionary event where differential mortality of moth susceptible (21 % mortality) versus resistant trees (68 % mortality) has altered the genetic structure and function of this ecosystem (Sthultz et al 2009a;Gehring et al unpublished data).…”

Section: Drought-tree Interactions and Piñon-juniper Woodlandsmentioning

confidence: 99%

Plant genetic effects on soils under climate change

et al. 2013

View full text Add to dashboard Cite

Background In the face of climate change, shifts in genetic structure and composition of terrestrial plant species are occurring worldwide. Because different genotypes of these plant species support different soil biota and soil processes, shifts in genetics are likely to have cascading effects on ecosystems. Scope We explore plant genetic effects on soil function in the context of climate change, and selection by soils, soil biota and plant-soil feedbacks. We propose categories of genetically-based plant traits that should be prioritized in research on genetic-based effects on soil processes including plant productivity and C allocation, tissue quality, plant water-use, and rhizosphere mutualisms. Additionally, we posit that soil community responses to climate change should be considered in concert with plant genotype because of sensitivity of soil communities to climate. We use two case studies to highlight these points. Conclusions We argue that the effects of climate change as an agent of selection on plants may cascade to affect soils, and ultimately the structure, composition and function of ecosystems. Understanding the ecological and evolutionary potential of plant-soil linkages may help us understand and mitigate the extended consequences of global change for ecosystems worldwide. Accordingly, we conclude with experimental approaches for examining genetically-based plant-soil interactions across climate change gradients.Plant Soil (2014) 379:1-19 DOI 10.1007/s11104-013-1972-x Responsible Editor

show abstract

“…This breakthrough for small-scale mapping with satellite images was followed by the launch of other satellites such as QuickBird, GeoEye-1, WorldView-1, and WorldView-2 (Jacobsen 2012). DigitalGlobe's World-View-2 satellite has been operational since 2010 and provides stereo imagery with a panchromatic ground sampling distance of 0.5 m. Some of the first studies based on WorldView-2 used the images to map urban tree species in Tampa (Florida, USA) (Pu and Landry 2012) and to quantify tree mortality in mixed-species woodlands (Garrity et al 2013). An accuracy study conducted in the lowlands of Switzerland revealed the benefit of stereo WorldView-2 images for the 3D modeling of forest canopies (Hobi and Ginzler 2012), which allows for the analysis of vertical forest structure and holds potential for canopy gap detection.…”

Section: Introductionmentioning

confidence: 99%

Gap pattern of the largest primeval beech forest of Europe revealed by remote sensing

et al. 2015

View full text Add to dashboard Cite

Abstract. Little is known about the gap pattern of primeval beech forests, since large-scale studies with continuous coverage are lacking. Analyses of forest structural patterns have benefitted from advances in remote sensing, especially with the launch of satellites providing data of submetric ground resolution. These developments can strongly advance our knowledge of natural forest dynamics and disturbance regimes. The Uholka-Shyrokyi Luh forest in the Ukrainian Carpathians, the largest remnant of primeval European beech (Fagus sylvatica L.) covering 102.8 km 2 , is an outstanding object to analyze the frequency distribution of gap sizes and to infer processes of forest dynamics. A stereo pair of very high-resolution WorldView-2 satellite images was used to characterize the forest's gap pattern. Canopy gaps were first digitized stereoscopically based on the image pair. In a second step, spectral properties in the red and yellow frequency bands were used to distinguish the stereoscopically mapped gap areas from non-gap areas, which enabled gap mapping over the entire study area. To validate the spectral gap mapping 338 randomly distributed samples were assigned manually to gap and non-gap areas based on the orthoimages. We found excellent agreement except for an overestimation of gaps close to clouds due to diffuse image areas. The frequency distribution of gap size revealed the forest to be structured by a small-scale mosaic of gaps mainly ,200 m 2 (98% of the gaps). Only a few large, stand-replacing events were detected, most probably caused by a wind storm in March 2007 and a heavy wet snow fall in October 2009. The small canopy gaps reflect fine-scale processes shaping forest structure, i.e., the death of single trees or groups of a few trees and is in line with the findings of the terrestrial forest inventory. We conclude that remote sensing approaches based on very high-resolution satellite images are highly useful to characterize even small-scale forest disturbance regimes and to study long-term gap dynamics. Stereo satellite images provide two viewing angles of the study area, thus allowing for a highly accurate mapping of canopy gaps in forests with a complex topography.

show abstract

Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery

Cited by 60 publications

References 62 publications

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

Plant genetic effects on soils under climate change

Gap pattern of the largest primeval beech forest of Europe revealed by remote sensing

Contact Info

Product

Resources

About