Mediterranean Forest Species Mapping Using Hyperspectral Imagery

2011/2012Advances in hyperspectral technology provides scientists the opportunity to investigate problems that were difficult if not impossible to approach using multispectral data; among those, species composition which is a very important and dynamic forest parameter, linked with many environmental qualities that we want to map and monitor. This study addresses the problem of Mediterranean forest species mapping using satellite EO-1 Hyperion imagery (30m, 196 bands). Two pixel based techniques were evaluated, namely Spectral Angle Mapper (SAM) and Support Vector Machines (SVM), as well as an object oriented approach (GEOBIA). These techniques were applied in two study areas with different species composition and pattern complexity, namely Thasos and Taksiarchis. Extensive field work provided reference data for the accuracy assessment of the produced maps. Image preprocessing included several steps of data corrections and the Minimum Noise Fraction transformation, as means for data dimensionality reduction. In the case of Thasos, where two conifer species are present, SAM technique resulted in an overall accuracy (OA) of 3.9%, SVM technique yielded OA of 89.0% and GEOBIA achieved an OA of 85.3%. In the case of Taksiarchis, where more species are present – both conifers and broadleaved- the respective OA was 80.0%, 82.6% and 74.1%. All three methodologies implemented to investigate the value of hyperspectral imagery in Mediterranean forest species mapping, achieved very accurate results; in some cases equivalent to forest inventory maps. SAM was the straightest forward to implement, only depending on the training samples. Implementation SVM involved the specification of several parameters as well as the use of custom software and was more successful in the challenging landscape of Taksiarchis. GEOBIA adapted to scale through segmentation and extended the exercise of classification, allowing for knowledge based refinement. Lower accuracies could be attributed to the assessment method, as research on alternative assessment methods better adapted to the nature of object space is ongoing. Two typical Mediterranean forests were studied. In Thasos, two conifer species of the same genus, namely Pinus brutia and Pinus nigra, dominate a big part of the island. Both of them were accurately mapped by all methodologies. In Taksiarchis primarily stands of Quercus frainetto mix with stands of Fagus sylvatica and the aforementioned pines. The two pines were again mapped with high accuracy. However, there was a notable confusion between the two broadleaved species, indicating the need for further research, possibly taking advantage of species phenology. The outcome of the proposed methodologies could confidently meet the current needs for vegetation geographical data in regional to national scale, and demonstrate the value of hyperspectral imagery in Mediterranean forest species mapping.XXIII Ciclo198

Χαρτογράφηση μεσογειακών δασικών ειδών με χρήση υπερφασματικών δεδομένων

Mediterranean forests, although a small fraction of the world's forest cover, need to be understood, described and monitored in order to be preserved. Spatial information about their location, their extent, their structure and their biodiversity, among others, is necessary and traditionally gathered in every available way. In particular, forest species mapping is an objective and a prerequisite in various applications that span in the fields of ecology, biology, forestry and agriculture, such as resource inventories, biodiversity assessment, fire hazard assessment, conservation planning, assessment of per-species carbon sequestration etc. Adding to that, forest species information is also essential for the national reporting obligations towards national and international policies, such as the UN Framework Convention on Climate Change (UNFCCC) and its Kyoto Protocol, the UN Convention on Biological Diversity (UNCBD), the UN Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD), the Ministerial Conference on the Protection of Forests in Europe (MCPFE), and the Streamlining European 2010 Biodiversity Indicators (SEBI2010). Advances in hyperspectral technology provide researchers with an opportunity to explore challenges that were either difficult or impossible to approach using multispectral data, including forest species mapping. This study examines the mapping of Mediterranean forest species, based on EO-1 Hyperion satellite spectral imagery (30m, 196 channels). Two pixel-level analysis methodologies were evaluated, based on Spectral Angle Mapper (SAM) and Support Vector Machines (SVM), as well as an object-based analysis methodology (GEOBIA). These were applied in two study areas with different species composition spatial patterns, namely the island of Thasos and Taxiarchis in Chalkidiki. Extensive fieldwork provided the reference data for estimating the accuracy of the maps. The preprocessing phase included correction steps and reduction of the hyperspectral dimension. In the case of Thasos, where there were two species of pine, the methodologies with SAM, SVM and GEOBIA, achieved overall accuracy of 94%, 89% and 85.3% respectively. In the case of Taxiarchis, where more species were present, the overall accuracy achieved was 80%, 82.6% and 74.1%. All three developed methodologies achieved very accurate results, in some cases comparable to forest inventory maps. The first (SAM) was the simplest to implement while the second required both a series of configurations and custom software. The lowest accuracy of the latest methodology (GEOBIA) can be attributed to the way accuracy is estimated, since in the case of object-based analysis, alternative methods of accurate accuracy estimation are still being investigated. The result of the proposed methodologies can meet the current needs for spatial vegetation data, both regionally and nationally. They also demonstrate the value of satellite hyperspectral imagery in mapping Mediterranean forest species.Τα Μεσογειακά δάση, παρότι είναι ένα μικρό κλάσμα της παγκόσμιας δασικής κάλυψης, χρειάζεται να γίνουν κατανοητά και να παρακολουθούνται ώστε να είναι δυνατή η διατήρησή τους. Χωρική πληροφορία, σχετικά με τη θέση τους, την έκτασή τους, τη δομή τους και τη βιοποικιλότητά τους, μεταξύ άλλων, είναι απαραίτητη και παραδοσιακά συγκεντρώνεται με κάθε διαθέσιμο τρόπο. Συγκεκριμένα, η χαρτογράφηση δασικών ειδών είναι απαιτούμενο και προϋπόθεση για ένα εύρος εφαρμογών στους τομείς της οικολογίας, βιολογίας, δασοκομίας και γεωργίας, όπως απογραφές, εκτίμηση βιοποικιλότητας, εκτίμηση κινδύνου πυρκαϊάς, σχεδιασμός πολιτικών προστασίας, διαχείριση φυσικών κινδύνων, παρακολούθηση αλλαγών και εκτίμηση δέσμευσης άνθρακα. Επιπρόσθετα, πληροφορίες για τα δασικά είδη είναι απαραίτητες για τις εθνικές υποχρεώσεις υποβολής εκθέσεων βάσει εθνικών και διεθνών πολιτικών, όπως η Σύμβαση Πλαίσιο των Ηνωμένων Εθνών για την Κλιματική Αλλαγή (UNFCCC) και το Πρωτόκολλο του Κιότο, η Σύμβαση του ΟΗΕ για τη Βιοποικιλότητα (UNCBD), το Συνεργατικό Πρόγραμμα για τη Μείωση των Εκπομπών από την Αποδάσωση και την Υποβάθμιση των Δασών στις Αναπτυσσόμενες χώρες του ΟΗΕ (UN-REDD), η Υπουργική Διάσκεψη για την Προστασία των Δασών στην Ευρώπη (MCPFE) και ο Εξορθολογισμός των ευρωπαϊκών δεικτών βιοποικιλότητας 2010 (SEBI2010). Η πρόοδος της υπερφασματικής τεχνολογίας παρέχει στους ερευνητές την ευκαιρία να διερευνήσουν προβλήματα που ήταν είτε δύσκολο είτε αδύνατο να προσεγγίσουν με χρήση πολυφασματικών δεδομένων, μεταξύ των οποίων και η χαρτογράφηση δασικών ειδών. Η παρούσα μελέτη εξετάζει τη χαρτογράφηση Μεσογειακών δασικών ειδών με βάση δορυφορική υπερφασματική εικόνα EO-1 Hyperion (30μ, 196δίαυλοι). Αξιολογήθηκαν δυο μεθοδολογίες ανάλυσης σε επίπεδο εικονοστοιχείου, συγκεκριμένα με βάση το Χαρτογράφο Φασματικής Γωνίας (Spectral Angle Mapper - SAM) και τις Μηχανές Διανυσμάτων Υποστήριξης (Support Vector Machines - SVM), όπως επίσης και μία μεθοδολογία αντικειμενοστρεφούς ανάλυσης (GEOBIA). Αυτές εφαρμόστηκαν σε δύο περιοχές μελέτης με διαφορετική σύνθεση και χωρικό μοτίβο ειδών, τη νήσο Θάσο και τον Ταξιάρχη Χαλκιδικής. Εκτενής εργασία πεδίου παρείχε τα δεδομένα αναφοράς για την εκτίμηση ακρίβειας των χαρτών. Το στάδιο της προεπεξεργασίας περιελάμβανε βήματα διορθώσεων και μείωση υπερφασματικής διάστασης. Στην περίπτωση της Θάσου, όπου υπήρχαν δύο είδη πεύκης, οι μεθοδολογίες με SAM, SVM και GEOBIA, πέτυχαν ολική ακρίβεια 94%, 89% και 85,3% αντίστοιχα. Στην περίπτωση του Ταξιάρχη, όπου υπήρχαν περισσότερα είδη, οι αντίστοιχες ολικές ακρίβειες που επιτεύχθηκαν ήταν 80%, 82,6% και 74,1%. Και οι τρεις μεθοδολογίες που αναπτύχθηκαν πέτυχαν πολύ ακριβή αποτελέσματα, σε μερικές περιπτώσεις εφάμιλλα χαρτών δασικής απογραφής. Η πρώτη (SAM) ήταν η πιο απλή στην εφαρμογή ενώ για τη δεύτερη χρειάστηκαν τόσο μια σειρά από παραμετροποιήσεις όσο και προσαρμοσμένο λογισμικό. Οι χαμηλότερες ακρίβειες της τελευταίας μεθοδολογίας (GEOBIA) μπορούν να αποδοθούν στον τρόπο εκτίμησής της, αφού στην περίπτωση της αντικειμενοστρεφούς ανάλυσης ερευνώνται ακόμα εναλλακτικές μέθοδοι εκτίμησης ακρίβειας, καλύτερα προσαρμοσμένες στη φύση του χώρου των αντικειμένων. Το αποτέλεσμα των προτεινόμενων μεθοδολογιών είναι δυνατό να καλύψουν τις τρέχουσες ανάγκες για γεωγραφικά δεδομένα βλάστησης, τόσο σε περιφερειακή όσο και σε εθνική κλίμακα. Επίσης, καταδεικνύουν την αξία των δορυφορικών υπερφασματικών εικόνων στη χαρτογράφηση δασικών ειδών της Μεσογείου

Use of UAV-borne multispectral data and vegetation indices for discriminating and mapping three indigenous vine varieties of the Greek Vineyard

In line with precision viticulture, in recent years new methods of vineyard management have been introduced, so as to optimize vine cultivation and production of wine of the highest quality. Following on the methodologies developed for mapping other crop parameters, there is currently a growing research effort for the discrimination and mapping of vine varieties, as this information is useful for vineyard-scale management, local and regional inventory and planning purposes, application of EU Directives, and support of certification and production of high quality wines. This research focuses on developing a methodology, based on UAV-borne multispectral data, for discriminating and mapping three vine varieties in Attica, Greece, employing three non-parametric classifiers, namely Random Forest (RF), Support Vector Machines (SVM) and Spectral Angle Mapper (SAM), and selected vegetation indices (VIs). The suggested methodology uses easy to obtain and process, cost-effective images and relies mostly on free open-source software. Study conclusions suggest that although the multispectral images used did not result in the accurate discrimination of the vine varieties at pixel level, expressed by highest overall accuracy (OA) 61.6%, they nevertheless proved useful in mapping varieties at the plot level. Therefore, it is considered effective for applications that require such level mapping

A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape

Forest fires constitute a natural disturbance factor and an agent of environmental change with local to global impacts on Earth’s processes and functions. Accurate knowledge of forest fuel extent and properties can be an effective component for assessing the impacts of possible future wildfires on ecosystem services. Our study aims to evaluate and compare the spectral and spatial information inherent in the EO-1 Hyperion, Quickbird and Landsat TM imagery. The analysis was based on a support vector machine classification approach in order to discriminate and map Mediterranean fuel types. The fuel classification scheme followed a site-specific fuel model within the study area, which is suitable for fire behavior prediction and spatial simulation. The overall accuracy of the Quickbird-based fuel type mapping was higher than 74% with a quantity disagreement of 9% and an allocation disagreement of 17%. Both classifications from the Hyperion and Landsat TM fuel type maps presented approximately 70% overall accuracy and 16% allocation disagreement. The McNemar’s test indicated that the overall accuracy differences between the three produced fuel type maps were not significant (p < 0.05). Based on both overall and individual higher accuracies obtained with the use of the Quickbird image, this study suggests that the high spatial resolution might be more decisive than the high spectral resolution in Mediterranean fuel type mapping

Landscape Pattern Changes in Response to Transhumance Abandonment on Mountain Vermio (North Greece)

Transhumance, the seasonal movement of herds between highlands and lowlands following precise, repeated routes, is a common practice in many Mediterranean regions. This livestock movement exploits natural vegetation in both winter and summer pastures. In Greece transhumant herders, drawn by relatively abundant vegetation, usually relocate to mountainous areas between April and October. Mount Vermio was an ideal summer pasture for the nomadic, ethnic group Sarakatsanoi of Thessaly, who used to own big herds. Socio-economic conditions of the 20th century led to the gradual decline of transhumance, resulting in reduction in grazing pressure and changes in vegetation dynamics. The purpose of this study was to monitor changes in landscape patterns in response to transhumance abandonment. Landscape metrics were employed to estimate land use/cover in two altitudinal zones. Results reveal that due to the abandonment of transhumance in the highlands landscape fragmentation increased. Meanwhile, in the lowlands, due to the uninterrupted presence of animals, landscape structure is more stable and diversified. Grasslands and agroforestry systems became smaller and more isolated. In conclusion, the abandonment of transhumance led to the overall deterioration of the rural landscape in the highlands