DEVELOPMENT OF METHODOLOGY FOR PLANT PHENOLOGY MONITORING BY GROUND-BASED OBSERVATION USING DIGITAL CAMERA

When monitoring phenology at ground level, it would be more important to continue observations in long terms and to detect the timing of various phenological events such as leafing, flowering and autumn senescence. In this study, to develop the methodology for plant phenology monitoring by using digital camera, we examined how multiple image indices, which are derived from multi-temporal visible images, respond to the changes of colors of leaves and flowers for several target species of plants, and tried to detect various phenology events by tracing time series changes of the coordinate in the feature spaces of two indices. As a result, we found out that it was possible to understand the characteristics of the phenological events for different species from each image index. Also, it was identified that the utility of combination with two indices would be effective to detect the timing of phenology events in the feature space of two indices. In the actual phenology monitoring, it would be effective to use a single index for understanding the seasonal characteristics and to use the combination of two indices for detection of the timing of phenology events by tracing the time series changes in the feature space

Automated Processing of Webcam Images for Phenological Classification

Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels’ time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the statistical software package R and publicly available in the R package phenofun. Executable example code is provided as supplementary material

Assessing spring phenology of a temperate woodland : a multiscale comparison of ground, unmanned aerial vehicle and Landsat satellite observations

PhD ThesisVegetation phenology is the study of plant natural life cycle stages. Plant phenological events are related to carbon, energy and water cycles within terrestrial ecosystems, operating from local to global scales. As plant phenology events are highly sensitive to climate fluctuations, the timing of these events has been used as an independent indicator of climate change. The monitoring of forest phenology in a cost-effective manner, at a fine spatial scale and over relatively large areas remains a significant challenge. To address this issue, unmanned aerial vehicles (UAVs) appear to be a potential new platform for forest phenology monitoring. The aim of this research is to assess the potential of UAV data to track the temporal dynamics of spring phenology, from the individual tree to woodland scale, and to cross-compare UAV results against ground and satellite observations, in order to better understand characteristics of UAV data and assess potential for use in validation of satellite-derived phenology. A time series of UAV data were acquired in tandem with an intensive ground campaign during the spring season of 2015, over Hanging Leaves Wood, Northumberland, UK. The radiometric quality of the UAV imagery acquired by two consumer-grade cameras was assessed, in terms of the ability to retrieve reflectance and Normalised Difference Vegetation Index (NDVI), and successfully validated against ground (0.84≤R2≥0.96) and Landsat (0.73≤R2≥0.89) measurements, but only NDVI resulted in stable time series. The start (SOS), middle (MOS) and end (EOS) of spring season dates were estimated at an individual tree-level using UAV time series of NDVI and Green Chromatic Coordinate (GCC), with GCC resulting in a clearer and stronger seasonal signal at a tree crown scale. UAV-derived SOS could be predicted more accurately than MOS and EOS, with an accuracy of less than 1 week for deciduous woodland and within 2 weeks for evergreen. The UAV data were used to map phenological events for individual trees across the whole woodland, demonstrating that contrasting canopy phenological events can occur within the extent of a single Landsat pixel. This accounted for the poor relationships found between UAV- and Landsat-derived phenometrics (R2<0.45) in this study. An opportunity is now available to track very fine scale land surface changes over contiguous vegetation communities, information which could improve characterization of vegetation phenology at multiple scales.The Science without Borders program, managed by CAPES-Brazil (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior)

Using digital repeat photography for monitoring the regrowth of a clear-cut area

Sammanfattning Digitala övervakningskameror har tidigare använts inom fenologisk forskning för att kunna mäta grönskan i trädkronor. Man har under en längre tid kunnat koppla lövträdets årscykel till klimatförändringar och på så sätt haft ett starkt incitament att studera sambandet. I denna uppsats utforskas möjligheten att applicera metoden med digitalkameror på ett nyligen kalhugget område för att se om man kan mäta återväxten under tre års tid (2011-2013). Genom att extrahera pixelvärden och beräkna grönskan kan man under de tre växtsäsongerna studera en signifikant ökning i markvegetation. Under arbetet har digitalkamerorna jämförts med sensordata, så kallad NDVI, för att studera huruvida metoden kan mäta sig med mer precis och konventionell teknik. Detta har den visat sig kunna där de digitala kamerorna, i vissa fall, visat sig vara mer känsliga för hastiga variationer i grönska än de parallella sensormätningarna. Forskning har bevisat att det största läckaget av markbundet kol sker under de inledande åren efter skogsfällning. Detta kol har skogens jordar tidigare förvarat och konserverat, men efter fällning läcker det ut i atmosfären som koldioxid. Läckaget har också visat sig ha ett starkt samband med den initiala återväxten av markvegetation på kalhygget. Digitalkamerorna skulle således kunna användas för att studera relationen. I denna uppsats diskuteras därför vidare användning av metoden inom skogsforskning och industri. En annan applicering, i form av vegetationsövervakning, undersöks också i denna uppsats där digitalkamerorna skulle kunna vara till stor hjälp inom skogsindustri och skogsvård. Målet med denna uppsats har alltså varit att utforska användningen av digitala kameror för att studera möjligheten att övervaka återväxten av ett kalhygge.Abstract The use of inexpensive digital cameras in phenological research has been acclaimed since results in previous research have shown that they are reliable and precise in measuring greenness of vegetation. The work of this thesis aims to broaden the applicability by studying how well the method performs when measuring the regrowth of a clear-cut area. This is needed to complement existing research that primarily uses the technique to study phenology. Data acquisition from the digital images was carried out with the use of chromatic coordinates in comparison to parallel measurements of sensor-based NDVI. These time series were analyzed through correlations, measuring the linear dependency and covariance. The results show significant similarities between the two measured time series and the increase in vegetation denseness during the studied period (2011-2013). It is also shown that the chromatic coordinates are more sensitive to variations in chlorophyll greenness than NDVI. These results, together with previous research, show that the digital camera is a valuable tool that is possible to apply to forest research and industry. Studies of clear-cut areas have shown that soil carbon release is strongly dependent on initial vegetation, a relationship that is possible to study following the results of this thesis. However, more research is needed to calibrate the method for measurements in different forest types and climate zones, before this is reality. The use of ground-level reference panels are also analyzed but fails to provide the reliable information needed. Too many sources of error are detected where the brightness calibration does more harm than good. Instead, chromatic coordinates and smoothing of the time series are used for suppressing the diurnal and seasonal variations in scene illumination

Patterns of plant phenology in Amazonian seasonally flooded and unflooded forests

Few studies have successfully monitored community-wide phenological patterns in seasonally flooded Amazonian várzea forests, where a prolonged annual flood pulse arguably generates the greatest degree of seasonality of any low-latitude ecosystem on Earth. We monitored the vegetative and reproductive plant phenology of várzea (VZ) floodplain and adjacent terra firme (TF) forests within two contiguous protected areas in western Brazilian Amazonia, using three complementary methods: monthly canopy observations of 1056 individuals (TF: 556, VZ: 500), twice monthly collections from 0.5-m2 litterfall traps within two 100-ha plots (1 TF, 1 VZ; 96 traps per plot), and monthly ground surveys of residual fruit-fall along transect-grids within each 100-ha plot (12 km per plot). Surveys encompassed the entire annual flood cycle and employed a floating trap design to cope with fluctuating water levels. Phenology patterns were generally similar in both forest types. Leaffall peaked during the aquatic phase in várzea forest and the dry season in terra firme. Flowering typically followed leaffall and leaf flush, extending into the onset of the terrestrial phase and rainy season in várzea and terra firme, respectively. Abiotic seed dispersal modes were relatively more prevalent in várzea than terra firme; the main contrast in fruiting seasonality was more likely a result of differences in community composition and relative abundance of seed dispersal modes than differences within individual genera. We emphasize the difficulty in distinguishing the role of the flood pulse from other seasonal environmental variables without multiannual data or spatially replicated studies across the spectrum of Amazonian forest types

A System for Acquisition, Processing and Visualization of Image Time Series from Multiple Camera Networks

201

Applications of Time-lapse Imagery for Monitoring and Illustrating Ecological Dynamics in a Water-stressed System

Understanding and perceiving the natural world is a key part of management, policy, conservation, and inevitably for our future. Increased demand on natural resources has heightened the importance of documenting ecosystem changes, and knowledge-sharing to foster awareness. The advancement of digital technologies has improved the efficiency of passive monitoring, connectivity among systems, and expanded the potential for innovative and communicative approaches. From technological progression, time-lapse imagery has emerged a valuable tool to capture and depict natural systems. I sought to enhance our understanding of a water-stressed system by analyzing imagery, in addition to integrating images with data visualization to illustrate the complexity of a river basin in central Nebraska. Image analysis was used to quantify wetland water inundation and vegetation phenology. These measurements from visible changes were combined with less visible data from additional passive monitoring to examine the relationship between vegetation phenology and bat activity, as well as wetland inundation and water quality. Moreover, time-lapse data sequences were constructed by integrating time-lapse imagery with data visualization in an interactive digital framework to examine the applications for communicating social-ecological dynamics. Findings suggest vegetation phenology was differentially associated with seasonal bat activity, possibly related to migratory versus resident life history strategies. In regards to examining wetland hydrology, water inundation was found to be correlated with nitrate, dissolved oxygen, and DEA, and negatively correlated with water temperature, indicating the importance of understanding water levels. AEM-RDA analysis identified several significant temporal patterns occurring with the wetland as well as the river site. Similarities between river and wetland patterns were suggestive of regional conditions driving fluctuations, while discrepancies were indicative of structural, biological, and local differences within individual sites. In examining communicative applications, time-lapse data sequences depicted a range of ecological dynamics while linking visible and invisible occurrences. The framework shows potential to offer a tangible context with explanatory content to aid in understanding environmental changes that are often too subtle to see or beyond the temporal scale of unaided human observation. Overall, cumulative findings suggest time-lapse imagery is of dual utility and has high potential for collecting data and illustrating ecological dynamics. Advisor: Craig R. Alle

Applications of Time-lapse Imagery for Monitoring and Illustrating Ecological Dynamics in a Water-stressed System

Understanding and perceiving the natural world is a key part of management, policy, conservation, and inevitably for our future. Increased demand on natural resources has heightened the importance of documenting ecosystem changes, and knowledge-sharing to foster awareness. The advancement of digital technologies has improved the efficiency of passive monitoring, connectivity among systems, and expanded the potential for innovative and communicative approaches. From technological progression, time-lapse imagery has emerged a valuable tool to capture and depict natural systems. I sought to enhance our understanding of a water-stressed system by analyzing imagery, in addition to integrating images with data visualization to illustrate the complexity of a river basin in central Nebraska. Image analysis was used to quantify wetland water inundation and vegetation phenology. These measurements from visible changes were combined with less visible data from additional passive monitoring to examine the relationship between vegetation phenology and bat activity, as well as wetland inundation and water quality. Moreover, time-lapse data sequences were constructed by integrating time-lapse imagery with data visualization in an interactive digital framework to examine the applications for communicating social-ecological dynamics. Findings suggest vegetation phenology was differentially associated with seasonal bat activity, possibly related to migratory versus resident life history strategies. In regards to examining wetland hydrology, water inundation was found to be correlated with nitrate, dissolved oxygen, and DEA, and negatively correlated with water temperature, indicating the importance of understanding water levels. AEM-RDA analysis identified several significant temporal patterns occurring with the wetland as well as the river site. Similarities between river and wetland patterns were suggestive of regional conditions driving fluctuations, while discrepancies were indicative of structural, biological, and local differences within individual sites. In examining communicative applications, time-lapse data sequences depicted a range of ecological dynamics while linking visible and invisible occurrences. The framework shows potential to offer a tangible context with explanatory content to aid in understanding environmental changes that are often too subtle to see or beyond the temporal scale of unaided human observation. Overall, cumulative findings suggest time-lapse imagery is of dual utility and has high potential for collecting data and illustrating ecological dynamics. Advisor: Craig R. Alle

A scheme for the uniform mapping and monitoring of earth resources and environmental complexes: An assessment of natural vegetation, environmental, and crop analogs

The author has identified the following significant results. A study was performed to develop and test a procedure for the uniform mapping and monitoring of natural ecosystems in the semi-arid and wood regions of the Sierra-Lahontan and Colorado Plateau areas, and for the estimating of rice crop production in the Northern Great Valley (Ca.) and the Louisiana Coastal Plain. ERTS-1 and high flight and low flight aerial photos were used in a visual photointerpretation scheme to identify vegetation complexes, map acreages, and evaluate crop vigor and stress. Results indicated that the vegetation analog concept is valid; that depending on the kind of vegetation and its density, analogs are interpretable at different levels in the hierarchical classification from second to the fourth level. The second level uses physiognomic growth form-structural criteria, and the fourth level uses floristic or taxonomic criteria, usually at generic level. It is recommended that analog comparisons should be made in relatively small test areas where large homogeneous examples can be found of each analog