Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Schlagworte: | |
| Online-Zugang: | Volltext Inhaltsverzeichnis |
| Beschreibung: | Zsfassung in dt. und engl. Sprache |
| Beschreibung: | XX, 180, XXII S. Ill., graph. Darst., Kt. |
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| 245 | 1 | 0 | |a Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |c von Sarah Asam |
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Datensatz im Suchindex
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|---|---|
| adam_text | POTENTIAL OF HIGH RESOLUTION REMOTE SENSING DATA
FOR LEAF AREA INDEX DERIVATION
USING STATISTICAL AND PHYSICAL MODELS
INAUGURAL-DISSERTATION
ZUR ERLANGUNG DES NATURWISSENSCHAFTLICHEN DOKTORGRADES
DER PHILOSOPHISCHEN FAKULTAT I
DER JULIUS-MAXIMILIANS-UNIVERSITAT WIIRZBURG
VORGELEGT VON
SARAH ASAM
AUS MURNAU AM STAFFELSEE
WIIRZBURG 2014
HTTP://D-NB.INFO/1066776903
TABLE OF CONTENTS
ABSTRACT I
ZUSAMMENFASSUNG III
LIST OF FIGURES XI
LIST OF TABLES XV
LIST OF ABBREVIATIONS XVII
1. INTRODUCTION 1
1.1. REMOTE
SENSING FOR ENVIRONMENTAL MONITORING 1
1.2. RELEVANCE OF LAI FOR
ECOLOGICAL PROCESSES 2
1.3. LAI DERIVATION IN MOUNTAINOUS GRASSLAND 4
1.4. OBJECTIVES AND
INNOVATIVE ANALYSES 6
2. STATE OF THE
ART IN LAI DERIVATION 9
2.1. IN SITU MEASUREMENT METHODS 9
2.1.1. DIRECT AND SEMI-DIRECT MEASUREMENTS 9
2.1.2. INDIRECT MEASUREMENT METHODS 11
2.2. ESTIMATION OF LAI FROM REMOTE
SENSING DATA 17
N
2.2.1. THEORETICAL BACKGROUND OF VEGETATION REMOTE SENSING 17
2.2.2. EMPIRICAL-STATISTICAL LAI DERIVATION 24
2.2.3. PHYSICAL APPROACH 29
2.3. LAI PRODUCTS 42
2.4. CURRENT RESEARCH NEEDS 44
3. STUDY AREA 47
3.1. CLIMATE 48
3.2. GEOLOGY, GEOMORPHOLOGY
AND SOILS 49
3.3. LAND COVER 52
3.4. ECONOMY 53
3.5. GRASSLANDS 54
4. DATA AND PREPROCESSING 57
4.1. RAPIDEYE DATA 58
4.1.1. DATA SPECIFICATIONS 58
VII
TABLE OF CONTENTS
4.1.2. DATA PREPROCESSING 59
4.1.3. LAND COVER CLASSIFICATION 62
4.2. DIGITAL ELEVATION MODEL 66
4.3. FIELD MEASUREMENTS 66
4.3.1. SAMPLING DESIGN 67
4.3.2. MEASUREMENT OF BIOPHYSICAL PARAMETERS 69
4.3.3. RESULTS OF IN SITU MEASUREMENTS 74
5. LAI DERIVATION
USING
EMPIRICAL-STATISTICAL MODELS 79
5.1. ESTABLISHMENT OF TRANSFER FUNCTIONS 80
5.2. RESULTS OF LAI DERIVATION USING
STATISTICAL MODELS 83
5.2.1. SINGLE DATA
SET ANALYSIS 83
5.2.2. TEMPORAL TRANSFERABILITY OF STATISTICAL RELATIONSHIPS 88
5.2.3. COMBINED DATA
SETS ANALYSIS 89
5.2.4. RED EDGE POTENTIAL
FOR LAI DERIVATION 91
5.3. POTENTIAL OF STATISTICAL MODELS FOR LAI
DERIVATION 93
6. LAI DERIVATION USING
THE PROSAIL
MODEL 95
6.1. THE PROSAIL
MODEL 97
6.1.1. MODEL CHARACTERISTICS 97
S
6.1.2. PROSAIL
SUITABILITY FOR GRASSLAND LAI 100
6.2. PROSAIL
SENSITIVITY ANALYSIS 100
6.2.1. TYPES OF SENSITIVITY ANALYSIS 100
6.2.2. THE EXTENDED FOURIER AMPLITUDE SENSITIVITY TEST 102
6.3. PARAMETERIZATION OF PROSAIL 110
6.4. INTEGRATION OF TOPOGRAPHIC CONDITIONS 113
6.5. PROSAIL INVERSION 114
6.5.1. LUT INVERSION APPROACH 114
6.5.2. LEAST SQUARES
ESTIMATE COST FUNCTION 116
6.5.3. MULTIPLE LAI SOLUTIONS
AND UNCERTAINTY MEASURES 117
6.5.4. IMPROVEMENT OF SPECTRAL MODEL INPUT FEATURES 120
6.6. RESULTS OF LAI
DERIVATION USING THE PROSAIL MODEL 122
6.6.1. COMPARISON OF RAPIDEYE AND
PROSAIL REFLECTANCES 122
6.6.2. PROSAIL LAI DERIVATION RESULTS AND
ACCURACY 125
6.6.3. ANALYSIS OF SPATIALLY EXPLICIT
INVERSION UNCERTAINTY 129
6.6.4. DERIVATION OF A RAPIDEYE LAI TIME
SERIES 135
TABLE OF CONTENTS
6.7. POTENTIAL OF PHYSICAL MODELING FOR RAPIDEYE
BASED LAI DERIVATION 136
7. SYNTHESIS ON LAI DERIVATION USING
HIGH SPATIAL RESOLUTION REMOTE SENSING DATA 139
7.1. ASSESSMENT AND COMPARISON OF EMPIRICAL-STATISTICAL AND PHYSICAL LAI
MODELING.. 139
7.2. POTENTIAL AND LIMITATIONS OF HIGH RESOLUTION DATA FOR GRASSLAND LAI
DERIVATION 144
7.3. OUTLOOK 145
REFERENCES 147
APPENDIX I
ACKNOWLEDGEMENTS XXI
|
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| spelling | Asam, Sarah 1984- Verfasser (DE-588)1067080236 aut Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models von Sarah Asam Potenzial hochaufgelöster Fernerkundungsdaten für die Ableitung des Blattflächenindex aus statistischen und physikalischen Modellen 2014 XX, 180, XXII S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Zsfassung in dt. und engl. Sprache Dissertation Universität Würzburg 2014 Strahlungstransport (DE-588)4183546-3 gnd rswk-swf Optische Fernerkundung (DE-588)4172662-5 gnd rswk-swf Blattflächenindex (DE-588)4791747-7 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Optische Fernerkundung (DE-588)4172662-5 s Strahlungstransport (DE-588)4183546-3 s Blattflächenindex (DE-588)4791747-7 s DE-604 Erscheint auch als Online-Ausgabe urn:nbn:de:bvb:20-opus-108399 https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-108399 Resolving-System kostenfrei Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027809697&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Asam, Sarah 1984- Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models Strahlungstransport (DE-588)4183546-3 gnd Optische Fernerkundung (DE-588)4172662-5 gnd Blattflächenindex (DE-588)4791747-7 gnd |
| subject_GND | (DE-588)4183546-3 (DE-588)4172662-5 (DE-588)4791747-7 (DE-588)4113937-9 |
| title | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |
| title_alt | Potenzial hochaufgelöster Fernerkundungsdaten für die Ableitung des Blattflächenindex aus statistischen und physikalischen Modellen |
| title_auth | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |
| title_exact_search | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |
| title_full | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models von Sarah Asam |
| title_fullStr | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models von Sarah Asam |
| title_full_unstemmed | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models von Sarah Asam |
| title_short | Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |
| title_sort | potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models |
| topic | Strahlungstransport (DE-588)4183546-3 gnd Optische Fernerkundung (DE-588)4172662-5 gnd Blattflächenindex (DE-588)4791747-7 gnd |
| topic_facet | Strahlungstransport Optische Fernerkundung Blattflächenindex Hochschulschrift |
| url | https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-108399 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027809697&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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