Global environmental information Examples of EIS Data sets and applications

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1 METIER Graduate Training Course n 2 Montpellier - february 2007 Information Management in Environmental Sciences Global environmental information Examples of EIS Data sets and applications Global datasets and example applications Andy Nelson, JRC. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences Territories, Environment, Remote Sensing & Spatial Information Joint Research Unit Cemagref - CIRAD - ENGREF 1

2 Background Ph.D. in Geography, M.Sc. in GIS Environmental/Natural Resource management CIAT, Colombia - International Centre for Tropical Agricultural World Bank, Washington DC UNEP CIESIN, Columbia University, NY FAO European Commission JRC Italy Worked on the development of several global/continental data sets: population, terrain, roads and, climate. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 2

3 Overview Part 1 Global/continental data State of affairs with global data Positives and negatives of the data Examples of global data, applications/limitations List of data sources and further info Part 2 Example of a continental environmental information system Monitoring Protected Areas in Africa Rationale Development Methods Results february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 3

4 A question. What is a global data set? In some senses there are two meanings to the term global data sets. One is the traditional meaning of a global-scale data set covering the entire world. The second addresses data sets that are required everywhere, in the sense of being widely applicable to many problems. Especially in regions where there is no other better data set. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 4

5 Why do we need global data sets? They represent the cumulative and collective knowledge of humanity about critical aspects of the environment and sustainable development. The are essential information resources needed by scientists, decision makers, applied users, educators, and many others to advance science, support education, ensure sustainable development, and meet the United Nations MDGs. The are a long-term foundation for shared understanding and effective action to improve the quality of human life and the environment. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 5

6 The development of global data 10 years ago there were few available data sets. Now there are hundreds of global data layers. Many different global datasets on environment and human development are being developed. They are disseminated by a range of institutions around the world. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 6

7 However, all is not good Increasing use and access to these data leads to a potential for: Increased problems related to inconsistent data integration. Huge amounts ot time spent converting and streamlining data. Variable data quality, documentation and version control. What is this, where did it come from, what does it mean & is it any good? Uncoordinated proliferation of different versions of the same data sets. Which one should I use? Unnecessary duplication of effort. Hey I didn t know you were doing this too! No centralised data base or clearing house Perhaps this is impossible, but Digital Earth, Google Earth and World Wind are proving to be more accessible than other established clearing houses. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 7

8 Thematic groupings of data Health Socio-economic Land Cover / Land Use Elevation / Bathymetry Transport and infrastructure Geology and soils Oceanic Pollution Fires Radiation Agriculture Climate Poverty Population Political Atmospheric Biodiversity and ecology Water and hydrology Vegetation I have certainly forgotten a few february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 8

9 1. Land cover Global land cover mapping A fundamental environmental data layer GLC2000 SPOT-VEGETATION data (1km) GLOBCOVER MERIS data (300m) MODIS 32 day composites Many other regional and continental datasets, Africover, Corine etc. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 9

10 1. Land cover The GLC2000 project uses the hierarchical FAO Land Cover Classification System (LCCS). LCCS allows the regionally defined legends to be translated into more generalised global land cover classes for the GLC2000 global product. So, we have both (a) regionally appropriate data and (b) a globally consistent generalisation. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 10

11 1. Land cover february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 11

12 1. Land cover february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 12

13 1. Land cover GLOBCOVER - 300m land cover for 2005 Started in 2004 as an ESA initiative collaborating with FAO, UNEP, JRC and others. To produce a global land-cover map for the year 2005, using the fine resolution (300 m) mode data from MERIS sensor on-board the ENVISAT satellite february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 13

14 1. Land cover A quick survey of current GLC products shows that a typical map will have 26 classes of Forest and 1 class of Agriculture This is only slightly facetious For example, GLC2000 has 10 classes of Forest 5 classes of Herbaceous Cover or Shrub land 1 class of Agriculture, plus 2 mosaic classes Others february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 14

15 1. Tree Cover, broadleaved, evergreen LCCS >15% tree cover, tree height >3m (Examples of sub-classes at regional level* : closed > 40% tree cove; open 15-40% tree cover) 1. Land cover 2. Tree Cover, broadleaved, deciduous, closed 3. Tree Cover, broadleaved, deciduous, open (open 15-40% tree cover) 4. Tree Cover, needle-leaved, evergreen 5. Tree Cover, needle-leaved, deciduous 6. Tree Cover, mixed leaf type 7. Tree Cover, regularly flooded, fresh water (& brackish) 8. Tree Cover, regularly flooded, saline water, (daily variation of water level) 9. Mosaic: Tree cover / Other natural vegetation 10. Tree Cover, burnt 11. Shrub Cover, closed-open, evergreen (Examples of sub-classes at reg. level *: (i) sparse tree layer) 12. Shrub Cover, closed-open, deciduous (Examples of sub-classes at reg. level *: (i) sparse tree layer) 13. Herbaceous Cover, closed-open (Examples of sub-classes at regional level *:(i) natural, (ii) pasture, (iii) sparse trees or shrubs) 14. Sparse Herbaceous or sparse Shrub Cover 15. Regularly flooded Shrub and/or Herbaceous Cover 16. Cultivated and managed areas (Examples of sub-classes at reg. level *: (i) terrestrial; (ii) aquatic (=flooded during cultivation), and under terrestrial: (iii) tree crop & shrubs (perennial), (iv) herbaceous crops (annual), non-irrigated, (v) herbaceous crops (annual), irrigated) 17. Mosaic: Cropland / Tree Cover / Other natural vegetation 18. Mosaic: Cropland / Shrub or Grass Cover 19. Bare Areas 20. Water Bodies (natural & artificial) 21. Snow and Ice (natural & artificial) 22. Artificial surfaces and associated areas february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 15

16 2. Vegetation Timeseries on vegetation growth MODIS 32 data composites AVHRR 18 year NDVI timeseries Geoland and VGT4AFRICA products 8km to 500m resolution NDVI normalised difference vegetation index is the most common Provides information on: seasonality, vegetation vigour, seasonal anomalies, drought, biomass. Links with other realtime timeseries: rainfall, water balance, active fires. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 16

17 2. Vegetation february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 17

18 2. Vegetation february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 18

19 2. Vegetation Need to link NDVI or other index values to real world implications What does a NDVI anomaly really mean? Growing seasons extracted from NDVI curves may not correspond to observed seasonality High frequency time series derived from passive methods always suffer from cloud cover and atmospheric effects, especially in the tropics. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 19

20 3. Terrain Elevation/Bathymetry and derivatives Another fundamental data source Global data sets vary from 5km to 90m resolution ETOPO 5km GLOBE 1km GTOPO30 1km SRTM 90m Plans for LIDAR (laser) generated data sets down to 5m february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 20

21 Examples of EIS. Global data sets and applications 3. Terrain february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 21

22 3. Terrain SRTM Shuttle Radar Topography Mission Almost global 90m resolution data Original data had problems with voids, poorly defined coastlines and noise. Now available in several GIS formats and most of these problems have been solved. It is based on classified 30m data which may be made available in the future. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 22

23 3. Terrain Used to derive many other data sets: Slope and aspect Wetness indices Landscape and landform metrics Catchments and drainage information Proxies for physical soil attributes Used for studies on climate, geomorphology, geology, hydrology, soil science, vegetation, precision agriculture, risk assessment and others. february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 23

24 february 2007 METIER Graduate Course n 2 - Information Management in Environmental Sciences 24

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