Land Cover Classification

Transcription

1 Land Cover Classification Prof. Dr. Christiane Schmullius Friedrich Schiller University Jena, Germany Department of Geoinformatics and Remote Sensing

2 ( ) ( ) 3 (-5) directly retrievable from EO out of 13 Variables from GCOS Adequacy Report

3 Land Cover Bodenbedeckung... Land Use - Bodennutzung Definition Land cover is the observed (bio)physical cover on the Earth s surface. When considering land cover in a very pure and strict sense it should be confined to describe the vegetation and the man-made features. Consequently, areas where the surface consists of bare rock or bare soil describe land itself rather than land cover. Also water surfaces can be disputed as being real land cover. However, in practise the scientific community is used to describe those aspects under the term land cover. Land cover is not to be confused with land use. Example: woodland or forest are land covers, but the land use may be hunting or rubber tapping (LCCS, UN FAO).

4 IGBP Land Cover LPJ Land Cover DISCREPANCIES Sitch et al. 2000

5 Land use is characterised by the arrangements, activities and inputs people undertake in a certain land cover type to produce, change or maintain it. Land use defined in this way establishes a direct link between land cover and the actions of people in their environment. (LCCS, UN FAO)

6 - Multispectral Systems - Disadvantages: - Dependent on Illumination - Atmospheric Effects ALBERTZ

7 - Radar Komplex dependences between backscatter and surface phenomena Polarisation Roughness Frequency Dielectric Const. Incidence Angle Soil Type Vegetation Structure Advantages: - penetrates clouds - illumin. independent NASA

8 -Additional Data - - Statistics - Maps - Ground truth - Aerial Photos - DEMs - Expert Knowledge Additional Data necessary for - methodological development - reference data

9 Nomenclature Requirements - Spatial consistent - Temporal consistent - Sensor independent - Scale consistent - Completeness - no overlaps - rule based - compatibel - multi-user capabilities

10 Nomenclature: systematic composition of surface objects Theoretischer Aufbau CORINE

11 Comparison of Level I Categories Anderson - CORINE 1 Urban or built-up areas 2 Agricultural Regions 3 Rangeland 4 Forested Areas 5 Water 6 Wetlands 7 Unvegetated open land 8 Tundra 9 Snow/Ice 1 Built-up Areas 2 Agricultural Regions 3 Forests and quasi-natural regions 4 Wetlands 5 Water Surfaces

12 IGBP Land Cover LPJ Land Cover DISCREPANCIES Sitch et al. 2000

13 EXAMPLE OF MISMATCH CLASSIFICATION FAO Classification LCLUC Classification Scheme NFI Classification Scheme Southeast Asia Scheme Indonesia A12 Natural Semi Natural F Forest Hr Lowland forest < 1000 m Vegetated F.1 Evergreen Forest Ht Submontane forest Forest F.1.1. Tropical evergreen Forest 1000 m 2000 m Woodland F.1.2. Mangrove Forest Hp Montane forest > 2000 m Thicket F.1.3. Swamp Forest Hm Mangrove forest Sparse Vegetation F.1.4. Caniferous Forest Hs Swamp forest Lichens /Mosses F.1.5. Bamboo Forest Hti Manmade forest F.1.6. Beach Forest F.1.7. Mossy / Montane Forest F.1.8. Decideous Forest F.1.9. Mixed Forest F.1.10.Forest Plantation F.1.11.Disturbed Forest / Secondary Forest Shurbland G Grassland Lktp Unproductive Dryland Grassland G.1. Grass G.2. Shrubland (Bush) B16 Bare Land O Bare land / Open land Consolidated Areas O.1. Mining Unconsolidated Areas O.2. Cleared Land O.3. Abandoned Land / Idled Land O.4. Sand Bar O.5. Mud Flat O.6. Fire Scar

14 FAO Land Cover Classification System (LCCS-2) Scheme

15 GOFC-GOLD Land Cover Implementation plan 2-4 March Jena Africover/GLCN LCCS is a comprehensive methodology for description, characterization, classification and comparison of most of land cover features identified anywhere in the world, at any scale or level of detail. LCCS was created in response to a need for: a harmonized and standardized collection of land cover data; availability of land cover data for a wide range of applications and users; and comparison and correlation of land cover classes.

16 GOFC-GOLD Land Cover Implementation plan 2-4 March Jena Africover/GLCN THE OBJECTIVE To produce a world-wide reference system for land cover able to combine an high level of flexibility (ability to describe land cover features all over the world at any scale or level of detail) with an absolute level of standardization of the class definition between different users THE IDEA A system that allows a dynamic creation of classes without to oblige the user to relate to a pre-defined list of names THE BASIC CONCEPT In LCCS the creation of a class is done by a dynamic combination of land cover diagnostic attributed called classifiers

17 Contrast Stretch Image Enhancement Techniques IHS Transformation ALBERTZ + CRISP

18 RSRG Bonn

19 Visual Interpretation Techniques! RSRG Bonn

20 RSRG Bonn

21 FSU Jena Institut für Geographie Vorlesung Bildverarbeitung Prof. Dr. C. Schmullius Role of Classification

22 FSU Jena Institut für Geographie Vorlesung Bildverarbeitung Prof. Dr. C. Schmullius

23 Multispectral Classification ALBERTZ

24 TERRA Instrumente: ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) CERES-2 (Cloud and Earth Radiant Energy System) MISR (Multi-angle Imaging Spectro Radiometer) MODIS (Moderate Resolution Imaging Spectro Radiometer) MOPITT (Measurements of Pollutants in the Troposphere)

25 TERRA MODIS-Produkte surface temperature water leaving radiance chlorophyll fluorescence concentration of chlorophyll-a within 35 percent, net ocean primary productivity, other optical properties; vegetation/land-surface cover, conditions, and productivity; cloud mask containing confidence of clear sky (or the probability of cloud), shadow, fire, and heavy aerosol at 1-km resolution; cloud properties characterized by cloud phase, optical thickness, particle size and mass transport; fire occurrence, temperature, and burn scars; global distribution of total precipitable water; cirrus cloud cover.

26 Terra-MODIS-Products - pre-preocessed by NASA Goddard Space Center and - distributed via the Land Processes section of the NASA DAAC (Distributed Active Archive Centre)

27 Segment-based Classifications Multilayer segmentation ASTER RGB Channel ASTER RGB Channel

28 Objektorientierte Bildanalyse mit ecognition - Einleitung Salt-and-Pepper Effect of conventional classifiers not usable in a GIS Result of a pixel-based maximum-likelihood classifier

29 Objektorientierte Bildanalyse mit ecognition Grundlagen Segmentation

30 Objektorientierte Bildanalyse mit ecognition Grundlagen Hierarchical Network of Image Objects Advantages: each image object contains besides ist spectral information further image characteristics (Standard Deviation, Form, Texture) and context informations (Exp.: neighbour to class A and B) Averaging of spectral heterogeneities over the whole object Object characteristics in different generalisation scales Reduction of classifiable units

31 Objektorientierte Bildanalyse mit ecognition Beispiele Foto

32 Objektorientierte Bildanalyse mit ecognition Beispiele Level 1

33 Objektorientierte Bildanalyse mit ecognition Beispiele Level 2

34 Objektorientierte Bildanalyse mit ecognition Beispiele Level 3

35 Objektorientierte Bildanalyse mit ecognition Beispiele Level 3: Area

36 Objektorientierte Bildanalyse mit ecognition Beispiele Level 3: Length/Width

37 Objektorientierte Bildanalyse mit ecognition Klassifikation von E-SAR und HyMap Daten E-SAR - RGB =X-HH, C-VV, L-VV

38 Objektorientierte Bildanalyse mit ecognition Klassifikation von E-SAR und HyMap Daten objektorientiertes Klassifikationsergebnis (E-SAR) pixelbasiertes Klassifikationsergebnis (E-SAR)

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40 State of the Art E.g. GLC 2000 Continental or global in coverage Hard Classification Kilometre pixel size Temporally static University of Wales Swansea

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42 Level 1 comparison MODIS 16-day composite Summer 2002 Days bands 6,2,1 SWIR, NIR, RED University of Wales Swansea

43 LC Maps from Remote Sensing MODIS LC (IGBP Classes) Classes) MODIS LC (UMD University of Wales Swansea

44 LC Maps from Remote Sensing GLC2000 LC Map (SPOT VGT S1 2000) University of Wales Swansea

45 Southern Cropland University of Wales Swansea SibII Lvl2 GLC2000

46 NW Wetlands University of Wales Swansea SibII Lvl2 GLC2000

47 FAO Land Cover Classification System (LCCS-2) Scheme

48 GLC2000, 1km Result: Agricultureforest-tundra MODIS, 500m MERIS, 300m

49 GLC2000, 1km Result: River in forest MODIS, 500m MERIS, 300m

50 Heterogeneity - Mismatch in spatial scale - Scaling issues University of Wales Swansea

51 Advancing the science MODIS Land-cover Product - Hard classification - 1km pixel size - Updated every 3 months - IGBP, UMD, LAI/fPAR, BGC biomes Red=Tree Cover, Green=Herb. Cover, Blue=Bare ground MODIS Continuous Fields Product - 500m pixel size - NOT hard classification - Life form, leaf type, leaf longevity

52 % tree cover derived from km AVHRR (DeFries et al, 2000)

53 Training from Landsat Hansen Defries and Townshend For For details see see MODIS 250m U.S. Tree Cover Prototype Tree Cover 0% 100%

54 Leaf type % broadleaf % needleleaf Leaf longevity % deciduous % evergreen Defries, Townshend and Hansen

55 Fractional Cover Modeling (VGT4 image)

56 Fractional Cover Modeling (VGT-fc fc)

57 Source: Fernandes

58 Jena GOFC-GOLD Land Cover Implementation Meeting and ESA Project Office Inauguration March 2004

59 What is GOFC? An ambitious, multifaceted international strategy to bring the Earth s forests/land cover under continuous observation. A vision to share data, information and knowledge, leading to informed action. A coordinated program of activities to ensure that earth observation and other data are used effectively for global monitoring for natural resource management, policy and global change research. A network of participants implementing coordinated demonstrations of the use of geospatial information and technology for sustainable development An international organization of space agencies and end users working together. A long term process of building an improved match between data products and user needs.

60 Organizational Status Started as a project of the Integrated Global Observation Strategy proposed by CSA. Panel of the Global Terrestrial Observing System Two main implementation teams: Landcover, Fire Scope: transitioning from GOFC (Global Observations of Forest Cover) to GOLD (Global Observations of Landcover Dynamics) Principal Role of GOFC/GOLD is to act as a coordinating mechanism for national and regional activities. Active regional networks developing Secretariat established with Canadian Forest Service

61 Roles of GOFC/GOLD Facilitate end-to-end international coordination mechanism: from observation to use Improve technical development and application of new methods of observation, especially remote sensing. Improve integration of satellite and in situ observations. Improve understanding of the causes of changes and their impacts

62 ESA s GOFC-GOLD Land Cover Implementation Project Office (LC PO) moderates the development of methods, tools and products for land cover measurements and monitoring using space-borne and in-situ observations; the assessment of current needs and deficiencies for global and regional land cover monitoring to support Global Change research, national and regional forest inventories and international policy; close cooperation with the Fire Implementation Team and regional networks in Asia and Africa in agreement with CFS GOFC-GOLD Project Office and the GOFC-GOLD Executive Committee.

63 Land Cover Classification Prof. Dr. Christiane Schmullius Friedrich Schiller University Jena, Germany Department of Geoinformatics and Remote Sensing