thesis submitted in partial fulfillment of the requirements of the degree doctor rer nat

CLASSIFICATION OF NATURAL BROAD-LEAVED EVERGREEN FORESTS BASED ON MULTI-DATA FOR FOREST INVENTORY IN THE CENTRAL HIGHLANDS OF VIETNAM Thesis submitted in partial fulfillment of the requirements of the degree Doctor rer. nat. of the Faculty of Forest and Environmental Sciences, Albert-Ludwigs-Universität Freiburg im Breisgau, Germany by Nguyen Thi Thanh Huong Freiburg im Breisgau, Germany 2009 Name of Dean: Prof. Dr. Heinz Rennenberg Name of Supervisor: Prof Dr. Barbara Koch Name of 2 nd Reviewer: Prof. Dr. Dr. h. c. Dieter R. Pelz Date of thesis defence: 2 nd December 2009 i Abstract Proper technical solutions of forest classification and forest mapping are essential to meet the requirements for sustainable forest management planning with reasonable costs and in a rational time period. The main focus of this study is to combine remotely-sensed data and terrestrial data in classifying and mapping tropical forest. The current study also seeks to describe which forest parameters are in closed relation with spectral data. Moreover, it also addresses estimates of stand volume. The study was conducted at a site on the Central Highland of Vietnam where much natural forest remains. The research used SPOT 5 satellite imagery captured during February 2006. Geomatic and topographic corrections were carried out using ground control points (GCPs) and Digital Terrain Model (DTM) which were obtained from Global Positioning System (GPS) and contour lines, respectively. Three algorithms were tested for topographical normalization, which are cosine, minnaert and C-correction. Satellite image corrected using C-correction algorithm was used as input data for further analysis. Both unsupervised and supervised methods have been integrated in the classification process. A set of sample plots and sample points were collected for the classification and validation during ground survey. The study recognized four major distinguished natural forest classes and four non-forest land cover classes. A total of one hundred and twenty one sample plots were collected from four forest classes for analysis. Diameter breast height (DBH), tree height, crown diameter and distance to the nearest neighbor tree were measured by forest inventory tools, while the others such as canopy cover and vegetation cover were estimated visually. The regression method was employed to simulate the relationship amongst forest variables, and between forest variables and spectral data. Tree density, mean diameter and density of the trees having DBH ≥ 35cm were the important variables having a closed relation with spectral values. Inverse J-shaped distribution Meyer N-DBH was selected as the basis to calculate mean characteristics of individual forest class. Finally, an improved classification system of natural wooden forest was defined based on the result of image classification and mean value of forest conditions of quantitative criteria along with qualitative characteristics. Four band SPOT5, three Principle Component (PCs), and a Normalized Difference Vegetation Index (NDVI) image, and the methods of regression, kNN and geostatistics were used to predict the forest stand volume. The best result was obtained by applying regression kriging method on SPOT5 image. In order to predict potential risk for the forest at the study area, the factors which related to accessibility in forest utilization were also analyzed. These factors were divided into four different impact ii levels for the two relevant classes for better forest management. A thematic map showing the potentially vulnerable sites was developed for forest management and planning. For the monitoring purposes as well as for sustainable forest management of the Vietnamese forests, a combination of remote sensing data and field inventory to produce suitable classified forest maps is a prerequisite. In combination with the appraisal of potential risks to forest stands, this information is of extreme importance for forest planning activities. iii Zusammenfassung Für die nachhaltige Bewirtschaftung von Wäldern sind forstliche Karten mit einer zweckmäßigen Waldeinteilung von großer praktischer Bedeutung. Um diese wichtige Datengrundlage zu erstellen und fortzuführen müssen geeignete technische Lösungen gefunden werden, welche Kosten und zeitlichen Aufwand in vernünftigen Grenzen zu halten. In dieser Arbeit wird nach einer optimierten Verknüpfung von Fernerkundungsdaten und terrestrisch erhobenen Daten für die flächige Klassifizierung von tropischen, naturnahen Wäldern gesucht. Dabei wird auch der Frage nachgegangen, welche forstlichen Parameter eine enge Beziehung zu den spektralen Werten in den Satellitendaten haben. Des Weiteren wurden Untersuchungen zur Schätzung der Holzvorräte durchgeführt. Das Untersuchungsgebiet liegt im zentralen Hochland von Vietnam. Dort kommen noch verbreitet natürliche tropische Wälder vor. Als Fernerkundungsmittel wurde eine SPOT 5 Szene vom 5. Februar 2006 verwendet. Für die geometrischen und topographischen Korrekturen des Satellitenbildes wurden Passpunkte (Ground Control Points) aus GPS Messungen sowie ein Geländemodell aus digitalisierten Höhenschichtlinien eingesetzt. Für die topographische Normalisierung wurden drei verschiedene Algorithmen getestet und zwar Cosine, Minnaert und C-correction. Die besten Ergebnisse lieferte die C-correction, weshalb diese Ergebnisse in die weiteren Verarbeitungsschritte einflossen. Die vorbearbeiteten Satellitendaten wurden sowohl mit unüberwachter Klassifizierung, als auch mit überwachten Klassifizierungsverfahren ausgewertet. Für letzteres und auch für die Genauigkeitsüberprüfung der Ergebnisse wurden eine Reihe von Trainingsgebieten in dem Untersuchungsgebiet festgelegt. Insgesamt 120 Plots wurden im Gelände angelegt, verteilt auf die vier unterschiedenen, natürlichen Waldklassen sowie für vier weiteren Landbedeckungsklassen. In den Plots wurden forstliche Parameter wie BHD, Baumhöhe, Kronendurchmesser, Position der Bäume und deren relative Lage zu den Nachbarbäumen gemessen, Kronenschluß und Bedeckungsgrad wurden geschätzt. Zur Berechnung der Zusammenhänge zwischen den erhobenen forstlichen Variablen selbst sowie den Variablen und den spektralen Fernerkundungsdaten wurden Regressionsanalysen angewandt. Dabei wurden enge Zusammenhänge zwischen spektralen Eigenschaften mit der Dichte des Kronendaches, dem mittleren Durchmesser, sowie der Dichte aller Bäume über 35 cm Durchmesser gefunden. Für die Berechnung von charakteristischen spektralen Eigenschaften der einzelnen Waldklassen wurde J-shaped Verteilung Meyer N-BHD zu Grunde gelegt. Basierend auf den Ergebnissen der Satellitenbildklassifikation und den berechneten Kennziffern wird in einem letzten Schritt ein neues, verbessertes Klassifikationsschema für natürliche tropische Wälder in vorgeschlagen. Für die Schätzung des Holzvorrates wurden die vier Kanäle der Spot 5 Szene, drei Principle Component Berechnungen sowie der Normalized Difference Vegetation Index (NDVI) herangezogen. iv Dabei kamen verschiedene Methoden aus der Geostatistik, Regressionsanalyse und kNN vergleichend zur Anwendung. Die besten Ergebnisse erzielte der geostatistische Ansatz des „Regression Krigings“ mit den SPOT 5 daten. Als zusätzliche Information wurde das potentielle Risiko für ungeregelte Waldnutzungen in Abhängigkeit von der Zugänglichkeit der Waldflächen modelliert. Vier abgestufte „Impact“ Klassen wurden für die zwei betroffenen Waldformationen mit GIS Techniken ausgeschieden. Die daraus resultierenden thematischen Karten zeigen die gefährdeten Flächen und dienen für die Planung entsprechender Maßnahmen bei der Waldbewirtschaftung. Sowohl für Beobachtung der Waldentwicklung als auch für die nachhaltige Bewirtschaftung der Wälder Vietnams werden durch die Kombination von Fernerkundungsdaten und Feldaufnahmen sehr brauchbare Forstkarten zur Verfügung gestellt. In Verbindung mit der Abschätzung potentieller Risiken sind diese ein Planungsinstrument von großer praktischer Bedeutung für die Forstwirtschaft in Vietnam. v Acknowledgements First of all, I would like to express my deep appreciation to Professor Dr. Barbara Koch and Dr. Claus-Peter Gross of the Depatement of the Remote Sensing Lanscape Information Systems (Felis) of the Albert Luwig University Freiburg for their kind supervision, guidance and support. I also thank Prof. Dr. Dr. h. c. Dieter R. Pelz of Department of Forest Biometry for his valuable comments and for taking up the role of co-referent of this study. The warmest thanks go to Assoc. Prof. Dr. Bao Huy, who has been giving me valuable suggestions and kind assistance during my research. I wish to thank Mr. Sandeep Gupta, Mr. Johannes Heinzel and Dr. Fillip Langa for their technical support. My special gratitude goes to forest staff in Quang Tan forest enterprise, farmers, lecturers and forestry students from Tay Nguyen University for their kind assistance during field work. Without their support it would not have been possible to conduct such an extensive forest inventory. I would like to give my thanks to the Government of Vietnam for granting me the scholarship and research subsidy support by the DAAD (German Academic Exchange Service). I am also greatly indebted to the OASIS for providing remote sensing images. I would like to express my sincere appreciation to all of the friends and colleagues of Felis, Freiburg University, Germany and Department of Forest Resource and Environment Management, Tay Nguyen University, Vietnam for their kind assistance during my research. Last but not least, my deepest thanks go to my family for their patience, support and encouragement throughout my many years of higher education. My parents have been an endless source of love and understanding throughout my life. My husband, daughter, brothers and sisters have always given me all their infinite love and best wishes. To all I am grateful for their roles in my life. Nguyễn Thị Thanh Hương vi Table of Contents Abstract i Zusammenfassung iii Acknowledgements v List of Tables xi Illustrations xiii List of Abbreviation xv 1 INTRODUCTION……………………………………………………….1 1.1 Background 1 1.2 Problem analysis 3 1.3 Objectives 7 1.4 Hypothesis 8 1.5 Outline 8 2 FOREST CLASSIFICATION SYSTEM…………………………….10 2.1 The forest classification systems 10 2.2 The classification syste ms of forest in Vietnam 13 2.2.1 Several forest classification systems before 1975 13 2.2.2 The developed classifications in the post-war period 14 3 MULTI-DATA SOURCES IN FOREST INVENTORY…………….19 3.1 Remote sensing techn iques 19 3.1.1 Pre-processing remote sensing images 19 3.1.2 Image processing 22 3.1.3 Normalized Difference Vegetation Index (NDVI) 27 vii 3.1.4 Principle component analysis (PCA) 28 3.2 Forest para meter considerations 29 3.2.1 Definiton of some forest characteristics 29 3.2.2 Regression analysis considered as the major double sampling among forest parameters 30  3.3 Combining of remote sensing and te rrestrial data 31 3.3.1 Multiphase sampling 31 3.3.2 Determining the sample size 33 3.3.3 Estimation of forest variable using remote sensing 33 3.4 GIS technique 36 3.5 Relation bet ween relevant factors and forest status 37 3.6 Literature re view 37 3.6.1 Classification of forest using remote sensing images 37 3.6.2 Prediction of forest parameters using remotely sensed data 38 4 DESCRIPTION OF RESEARCH AREA…………………………….43 4.1 Location 43 4.2 Topography 44 4.3 Geology an d soil 44 4.4 Climate 44 4.5 Description of forest types 45 4.6 Forest jurisd iction 46 5 METHODOLOGY…………………………………………………… 48 5.1 Data, Software and equipment 49 5.1.1 Data availability 49 5.1.2 Software 51 viii 5.1.3 Equipment and tools 51 5.2 Developme nt of a set of field data 52 5.2.1 Pre-field preparation 52 5.2.2 Field measurement 53 5.2.3 Statistical approach to field data survey 54 5.3 Pre-processing remote sensing data 56 5.3.1 Ortho-rectification 56 5.3.2 Topographical correction 57 5.4 Multispectra l classification 60 5.4.1 Unsupervised classification 60 5.4.2 Supervised classification 60 5.4.3 Accuracy assessment 63 5.5 Statistical d escription of forest classes 65 5.5.1 Transformation of data 65 5.5.2 Regression analysis technique 66 5.6 Estimation of stand volume by different methods 67 5.6.1 Using empirical regression 67 5.6.2 The k-NN algorithm 68 5.6.3 Geostatistics with regression kriging 69 5.6.4 Model evaluation 72 5.7 Assessing risk potential of forest status by indirect factors for forest management ………………………………………………………………………………………… 73 5.7.1 Basis of assessment 73 5.7.2 An analysis based on database and forest map 74 6 RESULTS……………………………………………………………….77 [...]... Limitation of education/ training in RS and GIS Difference of natural forests of the Central Highlands from other parts in the Country Rapid change in forest status in overtime Linkage between RS + GIS and Inventory Mechanism for application and updating Figure 1.2 Main concerns of the thesis 1.3 Objectives Originating from the analysed problems above, the goal of the current study is to improve existing... mosaic of forest formations in varying degrees of several kinds of degradations in the past Daknong is one of the similar provinces that has the most abundant forest resource in Vietnam But, as in other provinces in the Central Highlands, the forests in Daknong appear as a mosaic of different communities and characteristics, distinct from others with respect to their structural parameters However, with the. .. from the beginning of the last century 2.2.1 Several forest classification systems before 1975 In 1918, Chavalier performed the first classification system for the forests in the North of Vietnam based on vegetation types By 1943, Maurand divided vegetation in Indochina into three vegetation zones including North Indochina vegetation, South Indochina vegetation and an intermediate one In the south of. .. the requirements for sustainable forest management planning with reasonable costs and within a rational time period Combination of spectral and forest field data can demonstrate the relationship between them The variance of forest characteristics can influence the spectral parameters of the satellite image The forest at the research site is of the same origin, but the different status of existing forest... forest management planning at the location 1.2 Problem analysis The forestry issues in Continental Southeast Asia are probably the most complex in the world (Stibig, 2003) As in many Southeast Asian countries, Vietnam has experienced the highest rates of net forest cover decline Estimates of the change in forest cover in Vietnam in the last half century vary greatly in measurement The forests have dramatically... are mainly descriptive, making it difficult to specify and distinguish in practice As presented alrealdy, one of the vital causes of ineffective management of the forests is lack of spatial information resources Thus, the combination of remote sensing data in forest inventories has not been done, the forest data have not been frequently updated and the forest maps are coarse As a result, out -of- date... contribute in this change 1.5 Outline Chapter 2 provides an overview of the general basis of tropical forest classification Some classication systems of Vietnamese forests are also mentioned in this chapter The multidata sources in forest inventory are revealed in Chapter 3 This chapter contains an overview of processing techniques of satellite image, field data analysis, the combination of remote sensing... different scales of forest organization (Franklin, 2001) Jensen (1996) defined classification as an abstract representation of the situation in the field using well-defined diagnostic criteria A classification describes the systematic framework with the names of the class and the criteria used to distinguish among them Classification of tropical forest can be important in determining management plans... forests on mountains of small tropical islands according to rainfall and elevation Elevation of each forest type varies, depending on the size of island and the direction of wind relative to the mountains Although some aspects of forest function are reflected by climatic classification, others such as tightness of nutrient cycling are not, therefore, climatic classifications alone are often inadequate as... with the inflexible system for the aforementioned reasons, the forest management in the Central Highlands in general, but in Daknong in particular, has encountered more difficulty in forest resource assessment than other provinces as well as in forest management planning Therefore, adjustment of the countrywide classification system to the conditions and requirements of specific area e.g the Central . CLASSIFICATION OF NATURAL BROAD-LEAVED EVERGREEN FORESTS BASED ON MULTI-DATA FOR FOREST INVENTORY IN THE CENTRAL HIGHLANDS OF VIETNAM Thesis submitted in partial fulfillment of the requirements. forest inventories. Integrating these techniques and tererrestrial data as an analysis of multi-source information is therefore of particular value. According to Franklin (2001), remote sensing. as being important for defining appropriate management interventions. Characterizing the disturbance regime typically involves assessing the severity, timing, and spatial distribution of the