february 2007 METIER Graduate Course n°2 - 1
Information Management in Environmental Sciences Information Management in Environmental Sciences
Examples of EIS Examples of EIS
Global datasets and example applications Andy Nelson, JRC.
Global environmental information Global environmental information
Data sets and applications Data sets and applications
Andy Nelson, JRC
Background 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.
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
Overview 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
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
A question. What is a global data set?
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.
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
Why do we need global data sets?
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.
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
The development of global data 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.
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
However, all is not good 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.
Introduction -- Global data sets and their applications and limitationsGlobal data sets and their applications and limitations
Thematic groupings of data Thematic groupings of data
Introduction
Introduction -- Global data sets and their applications and limitations
I have certainly forgotten a few…
• Biodiversity and ecology
• Water and hydrology
• Vegetation
• Oceanic
• Pollution
• Fires
• Radiation
• Atmospheric
• Geology and soils
• Political
• Transport and infrastructure
• Population
• Elevation / Bathymetry
• Poverty
• Land Cover / Land Use
• Climate
• Socio-economic
• Agriculture
• Health
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
• 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
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
• 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…
1. Land cover 1. Land cover
Introduction
Introduction -- Global data sets and their applications and limitations
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) 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
2. Vegetation 2. Vegetation
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
2. Vegetation 2. Vegetation
Introduction
Introduction -- Global data sets and their applications and limitations
2. Vegetation 2. Vegetation
Introduction
Introduction -- Global data sets and their applications and limitations
2. Vegetation 2. Vegetation
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
3. Terrain 3. Terrain
Introduction
Introduction -- Global data sets and their applications and limitations
• 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
Introduction
Introduction -- Global data sets and their applications and limitations
3. Terrain
3. Terrain
3. Terrain 3. Terrain
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
3. Terrain 3. Terrain
Introduction
Introduction -- Global data sets and their applications and limitations
• 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.
Introduction
Introduction -- Global data sets and their applications and limitations