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  • 1
    Keywords: Forschungsbericht ; Satellitenfernerkundung ; Datenfusion
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (50 Seiten, 1,56 MB) , Illustrationen, Diagramme
    Language: German
    Note: Förderkennzeichen BMBF 01IS14010A-C. - Verbund-Nummer 01155122 , Autoren dem Berichtsblatt der Druck-Ausgabe entnommen , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden
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  • 2
    Online Resource
    Online Resource
    [Berlin] : [Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, Geographisches Institut - Geomatik]
    Keywords: Forschungsbericht ; Ökosystem
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (40 Seiten, 4,93 MB) , Illustrationen, Diagramme, Karten
    Language: German , English
    Note: Förderkennzeichen BMBF 50EE1309 , Autoren und durchführende Institution dem Berichtsblatt entnommen , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Sprache der Zusammenfassung: Deutsch, Englisch
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  • 3
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: Online-Ressource (13 S., 557 KB) , Ill., graph. Darst.
    Language: German
    Note: Förderkennzeichen BMBF 50 EE 0949 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Systemvoraussetzungen: Acrobat reader.
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  • 4
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Development economics. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (370 pages)
    Edition: 1st ed.
    ISBN: 9783319336282
    Series Statement: Human-Environment Interactions Series ; v.6
    Language: English
    Note: Intro -- Preface -- Contents -- 1 Land Use Competition: Ecological, Economic and Social Perspectives -- Abstract -- 1.1 The Global Relevance of Land Use Practices -- 1.2 Land: Matter, Markets and Meaning -- 1.2.1 From Land Cover to Global Change: The Loss of Innocence -- 1.3 The Case for Land Use Competition: Going Beyond Drivers -- 1.3.1 Scales and Scaling -- 1.3.2 Interdisciplinarity: Alternatives to Integrative Theories -- 1.4 Land Use Competition in This Volume: Generative Differences -- References -- Going Beyond Distal Drivers in Land Use Competition -- 2 Conceptualizing Distal Drivers in Land Use Competition -- Abstract -- 2.1 Distal Drivers-A Conceptual Challenge -- 2.2 The Telecoupling Framework -- 2.2.1 Systems -- 2.2.2 Flows -- 2.2.3 Agents -- 2.2.4 Causes and Effects -- 2.3 Analytical Dimensions of 'Distal Drivers' in Land Use Competition -- 2.3.1 Going Beyond Proximate and Distal: Competition as a Distributed Process -- 2.3.2 Space: Material and Social Distance -- 2.3.3 Systemic and Relational Perspectives -- 2.3.4 Patterns of Practice in Land Use Competition -- 2.3.5 Power and Knowledge Structure What Counts as Legitimate -- 2.3.6 Technology Makes Connections -- 2.3.7 Recognizing Different Temporalities in Land Use Competition -- 2.4 Conclusion: The Contingency of Land Use Competition -- References -- 3 At a Distance from the Territory: Distal Drivers in the (Re)territorialization of Oil Palm Plantations in Indonesia -- Abstract -- 3.1 Conceptualizing Drivers of Plantation Expansion -- 3.2 (Re)terriorialization of Indonesia's Plantations -- 3.2.1 Centralization and the Influence of Jakarta on Plantation Expansion -- 3.2.2 Decentralization and the New Influence of District Governments -- 3.3 Competing Claims to Land as a Response to Plantation Expansion -- 3.3.1 Customary Land Rights -- 3.3.2 Social Justice -- 3.3.3 Economic Growth. , 3.3.4 Environmental Protection -- 3.4 Can the Distance Be Bridged? -- References -- 4 The Transformation of Land-Use Competition in the Argentinean Dry Chaco Between 1975 and 2015 -- Abstract -- 4.1 Introduction -- 4.2 Key Actors of Land-Use Competition in the Dry Chaco -- 4.3 Three Periods of Land-Use Change and Increasing Competition for Land in the Argentine Dry Chaco -- 4.3.1 Period I: Local Competition (1970-2000) -- 4.3.2 Period II: Upscaling of Competition to the National Level (2000-2007) -- 4.3.3 Period III: Moving to the Global Scale (The 2007-2014) -- 4.4 Strategies for Dealing with Emerging Land-Use Competition in the Dry Chaco -- 4.5 Conclusion -- Acknowledgments -- References -- 5 Mind the GAP: Vietnamese Rice Farmers and Distal Markets -- Abstract -- 5.1 Introduction -- 5.2 Historical Contextualization: The Molding of Local Assets Over the Past Four Decades -- 5.2.1 Regulatory and Ideological Transformations -- 5.2.2 Infrastructural Developments and Green Revolution Influence -- 5.2.3 Small Farmers, Large Fields Model: A Government-Initiated Attempt to Overcome Structural Deficiencies of the Rice Sector -- 5.3 The Current Situation: Transformations Under Distal Influences -- 5.3.1 The Global High-Value Rice Market: A Potentiality with Challenges -- 5.3.2 Mobilizing Tam -- 5.3.3 Mobilizing the Farmers -- 5.3.4 Reconfiguring Social and Spatial Arrangements in the Settlement -- 5.4 Concluding Remarks -- References -- 6 The Role of Maps in Capturing Distal Drivers of Deforestation and Degradation: A Case Study in Central Mozambique -- Abstract -- 6.1 Introduction -- 6.1.1 Why Do We Need Maps of Deforestation and Forest Degradation? -- 6.1.2 Mapping Forests: A Remotely Sensed Approach -- 6.1.3 Linking Deforestation and Degradation to Its Drivers: The Role of GIS -- 6.1.4 Who Else Has Participated in Changing the Forests?. , 6.2 Capture Distal Drivers in the Beira Corridor, Manica, Mozambique -- 6.2.1 Land Cover and Land Use History in the Beira Corridor -- 6.2.2 Can Spatial Patterns Reveal Hidden Distal Drivers? -- 6.2.2.1 Patterns of Deforestation and Degradation in Beira Corridor Region -- 6.2.2.2 Effects of Maize and Charcoal Markets -- 6.2.3 RS and GIS: An Unbiased Microscope or Distorting Mirror? -- 6.2.3.1 Linking Patterns to Processes -- 6.2.3.2 Uncertainties of Deforestation and Degradation Estimation -- 6.2.3.3 Can a Map Itself Become a Distal Driver? -- 6.3 Conclusion -- References -- 7 Nuts About Gold: Competition for Land in Madre de Dios, Peru -- Abstract -- 7.1 Introduction: Land Uses in a Biodiversity Hotspot -- 7.2 Observing the Conflict of Nuts, Gold and Other Land Resources -- 7.3 Local to Distal Drivers of Change and Their Impacts -- 7.4 Land Disturbances Conceptualized as Dynamic Processes -- 7.5 Concluding Remarks -- Acknowledgments -- References -- Land Use Competition and Ecosystem Services -- 8 Competition for Land-Based Ecosystem Services: Trade-Offs and Synergies -- Abstract -- 8.1 Introduction -- 8.1.1 What Is Competition? -- 8.1.1.1 Competition Occurs Between Actors -- 8.1.1.2 Disciplinary Approaches to Competition -- 8.1.1.3 Conceptualization of Competition for Land-Based Ecosystem Services -- 8.1.1.4 Land-Use Competition and Trade -- 8.1.1.5 Trade-Offs and Synergies in Competition for Land-Based Ecosystem Services -- 8.2 Spatial Scale -- 8.2.1 Scaling in the Case Study Chapters of This Section -- 8.3 Intervention and Governance -- 8.4 Synthesis -- Acknowledgments -- References -- 9 Contested Land in Loliondo: The Eastern Border of the Serengeti National Park between Conservation, Hunting Tourism, and Pastoralism -- Abstract -- 9.1 Introduction -- 9.2 Contested Land at the Eastern Border of the Serengeti National Park. , 9.2.1 The Loliondo Division/GCA becomes a Hunting Ground for the Ortello Business Corporation -- 9.2.2 Changing Legislation: The New Wildlife Conservation Act of 2009 -- 9.2.3 Redrawing of Boundaries: The District Land Use Framework Plan -- 9.2.4 Redrawing of Boundaries: Putting a Plan into Practice -- 9.2.5 The Loliondo Land Conflict: A Case Study for Competition over Provisioning Services and Recreational Services in a Nature Conservation Area -- 9.3 The Strip alongside the Eastern Border of the Serengeti as a Dry Season Grazing Area -- 9.4 Conclusions -- Acknowledgments -- References -- 10 How the Collapse of the Beef Sector in Post-Soviet Russia Displaced Competition for Ecosystem Services to the Brazilian Amazon -- Abstract -- 10.1 Introduction -- 10.2 Consumption, Production, and Trade of Beef -- 10.2.1 High Beef Consumption and Production in the Soviet Union -- 10.2.2 The Collapse of the Beef Sector After 1991 -- 10.2.3 Collapse of the Livestock Sector Triggered Land Abandonment -- 10.2.4 Russia's Beef Imports After 1991 -- 10.3 The Booming Beef Sector in Brazil -- 10.3.1 Export of Beef and Soy Fostered Widespread Deforestation in the Brazilian Amazon -- 10.3.2 The Contribution of Russian Beef Imports to Deforestation in the Brazilian Amazon -- 10.3.3 Complex Trade-Offs Between Beef Production and Carbon Sequestration -- 10.4 Conclusion -- Acknowledgements -- References -- 11 Of Trees and Sheep: Trade-Offs and Synergies in Farmland Afforestation in the Scottish Uplands -- Abstract -- 11.1 Introduction -- 11.2 Livestock Production and Carbon Sequestration in Glensaugh, North-East Scotland -- 11.3 Implications for Land-Use Competition -- 11.4 Conclusion -- References -- 12 Land Use Competition Related to Woody Biomass Production on Arable Land in Germany -- Abstract -- 12.1 Drivers of Land Use Change in Germany. , 12.2 Features of Agroforestry Systems and Short Rotation Coppice -- 12.2.1 Interactions with Food and Annual Biomass Crops -- 12.2.2 Interactions with Regulating and Supporting Ecosystem Services -- 12.2.3 Interactions with Biodiversity -- 12.2.4 Interaction with 'Cultural Services' -- 12.3 Synergies or Trade-Offs? The Selection of Suitable Sites Is the Key -- 12.4 Challenges to the Implementation of Agroforestry Systems and Short Rotation Coppice -- 12.5 The Implications for Sustainable Land Management -- 12.5.1 Assessing the Intensity of Land Use Competition -- 12.5.2 Integrating Ecological with Economic and Societal Demands -- 12.5.3 Integrating Knowledge, Sectoral Viewpoints and Values -- 12.5.4 Managing the Demand -- References -- 13 Land-Use Competition in the South American Chaco -- Abstract -- 13.1 Introduction -- 13.1.1 The Chaco -- 13.1.2 Land-Use Change in the Chaco -- 13.2 Drivers of Land-Use Change in the Chaco -- 13.2.1 Proximate Causes -- 13.2.2 Underlying Drivers -- 13.3 Land Competition in the Chaco -- References -- Understanding the Interactions of Land and Food Systems -- 14 The Future Is Made. Imagining Feasible Food and Farming Futures in an Unpredictable World -- Abstract -- 14.1 Introduction -- 14.2 Land System Futures -- 14.2.1 Relations of Space and Place -- 14.2.2 Biophysical Constraints -- 14.2.3 Social System, Social Change and Actors -- 14.3 Imagining Place-Related Land Use Futures -- 14.3.1 Relations Between Local Place and Global Space -- 14.3.2 Biophysical Constraints -- 14.3.3 Social Systems, Social Change and Actors -- 14.4 Conclusion -- References -- 15 Exploring a 'Healthy Foodshed': Land Use Associated with UK Fruit and Vegetables Supply -- Abstract -- 15.1 Introduction -- 15.2 Case Study: The 'Fruit and Veg' Shed of the UK -- 15.3 'Fruit and Veg' Foodshed Is Increasing. , 15.4 Where Does the UK's 'Fruit and Veg' Come from?.
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  • 5
    Keywords: Agrarboden ; Bodennutzungsintensität ; Ernährungssicherung ; Wasserversorgung ; Ökosystem ; Entwicklungsländer ; Schwellenländer ; Welt ; Environment ; Sustainable development ; Development economics ; Agricultural economics ; Human geography ; Economic policy ; Environment ; Sustainable development ; Development economics ; Agricultural economics ; Human geography ; Economic policy ; Aufsatzsammlung ; Bodennutzung ; Sozialökologie
    Description / Table of Contents: Conceptualising Distal Drivers in Land Use Competition -- Competition for Land-Based Ecosystem Services: Trade-Offs and Synergies -- The Emerging New Food Regime – Transition Towards Sustainability? -- Land-Water Competition.
    Type of Medium: Online Resource
    Pages: Online-Ressource (IX, 379 p. 48 illus., 32 illus. in color, online resource)
    ISBN: 9783319336282
    Series Statement: Human-Environment Interactions 6
    RVK:
    Language: English
    Note: Description based upon print version of record
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  • 6
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (24 Seiten, 2,88 MB) , Illustrationen, Diagramme
    Language: German
    Note: Förderkennzeichen BMBF 50EE1254 - 50EE1255. - Verbund-Nummer 01137685 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden
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  • 7
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (30 Seiten, 3,34 MB) , Illustrationen, Diagramme
    Language: German
    Note: Förderkennzeichen BMWi 50EE1622 , Autoren dem Berichtsblatt entnommen , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Sprache der Zusammenfassung: Deutsch, Englisch
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  • 8
    Publication Date: 2024-04-19
    Description: Warming induced shifts in tundra vegetation composition and structure, including circumpolar expansion of shrubs, modifies ecosystem structure and functioning with potentially global consequences due to feedback mechanisms between vegetation and climate. Satellite-derived vegetation indices indicate widespread greening of the surface, often associated with regional evidence of shrub expansion obtained from long-term ecological monitoring and repeated orthophotos. However, explicitly quantifying shrub expansion across large scales using satellite observations requires characterising the fine-scale mosaic of Arctic vegetation types beyond index-based approaches. Although previous studies have illustrated the potential of estimating fractional cover of various Plant Functional Types (PFTs) from satellite imagery, limited availability of reference data across space and time has constrained deriving fraction cover time series capable of detecting shrub expansion. We applied regression-based unmixing using synthetic training data to build multitemporal machine learning models in order to estimate fractional cover of shrubs and other surface components in the Mackenzie Delta Region for six time intervals between 1984 and 2020. We trained Kernel Ridge Regression (KRR) and Random Forest Regression (RFR) models using Landsat-derived spectral-temporal-metrics and synthetic training data generated from pure class spectra obtained directly from the imagery. Independent validation using very-high-resolution imagery suggested that KRR outperforms RFR, estimating shrub cover with a MAE of 10.6 and remaining surface components with MAEs between 3.0 and 11.2. Canopy-forming shrubs were well modelled across all cover densities, coniferous tree cover tended to be overestimated and differentiating between herbaceous and lichen cover was challenging. Shrub cover expanded by on average + 2.2 per decade for the entire study area and + 4.2 per decade within the low Arctic tundra, while relative changes were strongest in the northernmost regions. In conjunction with shrub expansion, we observed herbaceous plant and lichen cover decline. Our results corroborate the perception of the replacement and homogenisation of Arctic vegetation communities facilitated by the competitive advantage of shrub species under a warming climate. The proposed method allows for multidecadal quantitative estimates of fractional cover at 30 m resolution, initiating new opportunities for mapping past and present fractional cover of tundra PFTs and can help advance our understanding of Arctic shrub expansion within the vast and heterogeneous tundra biome.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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  • 9
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    PANGAEA
    In:  Supplement to: Griffiths, Patrick; Nendel, Claas; Hostert, Patrick (2019): Intra-annual reflectance composites from Sentinel-2 and Landsat for national-scale crop and land cover mapping. Remote Sensing of Environment, 220, 135-151, https://doi.org/10.1016/J.RSE.2018.10.031
    Publication Date: 2023-01-13
    Description: Many applications that target dynamic land surface processes require a temporal observation frequency that is not easily satisfied using data from a single optical sensor. Sentinel-2 and Landsat provide observations of similar nature and offer the opportunity to combine both data sources to increase time-series temporal frequency at high spatial resolution. Multi-sensor image compositing is one way for performing pixel-level data integration and has many advantages for processing frameworks, especially if analyses over larger areas are targeted. Our compositing approach is optimized for narrow temporal-intervals and allows the derivation of time-series of consistent reflectance composites that capture field level phenologies. We processed more than a years' worth of imagery acquired by Sentinel-2A MSI and Landsat-8 OLI as available from the NASA Harmonized Landsat-Sentinel dataset. We used all data acquired over Germany and integrated observations into composites for three defined temporal intervals (10-day, monthly and seasonal). Our processing approach includes generation of proxy values for OLI in the MSI red edge bands and temporal gap filling on the 10-day time-series. We then derive a national scale crop type and land cover map and compare our results to spatially explicit agricultural reference data available for three federal states and to the results of a recent agricultural census for the entire country. The resulting map successfully captures the crop type distribution across Germany at 30m resolution and achieves 81% overall accuracy for 12 classes in three states for which reference data was available. The mapping performance for most classes was highest for the 10-day composites and many classes are discriminated with class specific accuracies 〉80%. For several crops, such as cereals, maize and rapeseed our mapped acreages compare very well with the official census data with average differences between mapped and census area of 11%, 2% and 3%, respectively. Other classes (grapevine and forest classes) perform slightly less well, likely, because the available reference data does not fully capture the variability of these classes across Germany. The inclusion of the red edge bands slightly improved overall accuracies in all cases and improved class specific accuracies for most crop classes. Overall, our results demonstrate the valuable potential of approaches that utilize data from Sentinel-2 and Landsat which allows for detailed assessments of agricultural and other land-uses over large areas.
    Keywords: Germany; MULT; Multiple investigations
    Type: Dataset
    Format: application/zip, 54.1 MBytes
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  • 10
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    PANGAEA
    In:  Supplement to: Pflugmacher, Dirk; Rabe, Andreas; Peters, Mathias; Hostert, Patrick (2019): Mapping pan-European land cover using Landsat spectral-temporal metrics and the European LUCAS survey. Remote Sensing of Environment, 221, 583-595, https://doi.org/10.1016/j.rse.2018.12.001
    Publication Date: 2023-01-13
    Description: The pan-European land cover map of 2015 was produced by combining the large European-wide land survey LUCAS (Land Use/Cover Area frame Survey) and Landsat-8 data. We used annual and seasonal spectral-temporal metrics and environmental features to map 12 land cover and land use classes across Europe (artificial land, seasonal cropland, perennial cropland, broadleaved forest, coniferous forest, mixed forest, shrubland, grassland, barren, water, wetland, and permanent snow/ice). The classification was based on Landsat-8 data acquired over three years (2014-2016). Overall map accuracy was 75.1%. The spatial resolution and minimum mapping unit is 30 x 30 m. The map can be downloaded as a single GeoTiff file of 874Mbyte. The produced pan-European land cover map compared favourably to the existing CORINE (Coordination of Information on the Environment) 2012 land cover dataset. The mapped country-wide area proportions strongly correlated with LUCAS-estimated area proportions (r=0.98). Differences between mapped and LUCAS sample-based area estimates were highest for broadleaved forest (map area was 9% higher). Grassland and seasonal cropland areas were 7% higher than the LUCAS estimate, respectively. In comparison, the correlation between LUCAS and CORINE area proportions was weaker (r=0.84) and varied strongly by country. CORINE substantially overestimated seasonal croplands by 63% and underestimated grassland proportions by 37%. Our study shows that combining current state-of-the-art remote sensing methods with the large LUCAS database imporves pan-European land cover mapping.
    Keywords: Europe
    Type: Dataset
    Format: image/tiff, 874.1 MBytes
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