Wetlands mapping in North America using MODIS 500m imagery July 28, 2011 ○ Gegen Tana a, Ryutaro Tateishi b a Graduate Schools of Science, Chiba University.

Slides:



Advertisements
Similar presentations
The MODIS Land Cover Product MODIS Land Cover Team Boston University GLC 2000 – “FIRST RESULTS” WORKSHOP JRC – Ispra, March 2002.
Advertisements

Has EO found its customers? Global Vegetation Monitoring Unit GLC2000 GLOBAL LEGEND GLC 2000 – “FIRST RESULTS” WORKSHOP JRC – Ispra, March 2002.
Production of land cover map of Asia, Central Asia, and Middle East with emphasis of the development of ground truth database Ryutaro Tateishi, Hiroshi.
VEGETATION MAPPING FOR LANDFIRE National Implementation.
NLCD and MODIS Landuse Processing Tools and Projection Issues in Modeling Limei Ran and Alison Eyth Center for Environmental Modeling for Policy Development.
Spatial analysis tools for biodiversity indicators on habitats and ecosystems Expert meeting on multi-scales mapping and integrated analysis of landscape.
Forest Monitoring of the Congo Basin using Synthetic Aperture Radar (SAR) James Wheeler PhD Student Supervisors: Dr. Kevin Tansey,
Landforms By: Miss Scheftic.
Sistema de Monitoreo de la Cobertura del Suelo de América del Norte.
World Wetlands Day - February the 2 nd 2004 “From the Mountains to the Sea” Wetlands at Work for Us Febr.2 nd 2004, Central European University Central.
Has EO found its customers? Global Vegetation Monitoring Unit GLC2000 Land Cover Classification.
Published in Remote Sensing of the Environment in May 2008.
Overview Minimum required classifiers for mapping vegetation cover at global scale using the FAO-LCCS tool GLC LEGEND hjs/30-Apr-01.
Land Cover Classification System Class A Liaison Seminar of ISO TC 211 LCCS : An Approach to the Global Harmonisation of Land Cover John S. Latham and.
An Object-oriented Classification Approach for Analyzing and Characterizing Urban Landscape at the Parcel Level Weiqi Zhou, Austin Troy& Morgan Grove University.
THE IMPACTS OF URBANIZATION ON SURFACE ALBEDO IN THE YANGTZE RIVER DELTA INTRODUCTION Mélanie Bourré 06/02/2011.
TM Marsh Index: Healthy, Mod Deterioration, Severe Deterioration Assessing the Response of Coastal Marshes to Sea Level Rise at a Coast-Wide Scale Michael.
Global land cover mapping from MODIS: algorithms and early results M.A. Friedl a,*, D.K. McIver a, J.C.F. Hodges a, X.Y. Zhang a, D. Muchoney b, A.H. Strahler.
Estuary Landforms and Features Preparing for an Earth Science Scavenger Hunt!
A METHODOLOGY TO SELECT PHENOLOGICALLY SUITABLE LANDSAT SCENES FOR FOREST CHANGE DETECTION IGARSS 2011, Jul, 27, 2011 Do-Hyung Kim, Raghuram Narashiman,
Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data Michael D. King, 1 Eric G. Moody, 1,2 Crystal B. Schaaf, 3 and Steven Platnick.
Aquatic Ecosystems Chapter 7.
Winter precipitation and snow water equivalent estimation and reconstruction for the Salt-Verde-Tonto River Basin for the Salt-Verde-Tonto River Basin.
Lu Liang, Peng Gong Department of Environmental Science, Policy and Management, University of California, Berkeley And Center for Earth System Science,
Has EO found its customers? Results of GLC2000 Legend Workshop November 2000 JRC / Ispra.
Remote Sensing Classification Systems
Wet lands. Standing water ecosystem Lakes, ponds, puddles H2O circulates within themself Has O2 and nutrients.
Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other.
Earth: The Water Planet Water, Water Everywhere!! Where is water found on our planet??
U.S. Department of the Interior U.S. Geological Survey Topographic Data Update IGOL: Rome September 13-15, 2004 Doug Muchoney USGS.
4-4 Aquatic Ecosystems Water covers ¾ of Earth, has an average depth of 3.7 (deepest part is 11 km – 6.8 mi) miles, contains about 3% salt and only 3%
Wetlands in Swamps, Floodplains, and Estuaries
Ramsar Convention (International Treaty 1971).  The Convention on Wetlands (Ramsar, 1971) -- called the "Ramsar Convention" -- is an intergovernmental.
North American Croplands Teki Sankey and Richard Massey Northern Arizona University Flagstaff, AZ.
An Adaptive Management Model for the Red River Basin of the North.
North American Carbon Program Sub-pixel Analysis of a 1-km Resolution Land-Water Mask Source of Data: The North American sub-pixel water mask product is.
Understanding Glacier Characteristics in Rocky Mountains Using Remote Sensing Yang Qing.
Land Cover Characterization Program National Mapping Division EROS Data CenterU. S. Geological Survey The National Land Cover Dataset of the Multi- Resolution.
Wetlands Investigation Utilizing GIS and Remote Sensing Technology for Lucas County, Ohio: a hybrid analysis. Nathan Torbick Spring 2003 Update on current.
Land cover mapping of Asia , Central Asia, and Middle East for GLC2000 project Ryutaro Tateishi, Hiroshi Sato, and Zhu Lin Center for Environmental Remote.
Measuring Vegetation Characteristics
Wetlands Swamps and Marshes
Wetlands in the Water Framework Directive main arguments and issues Bruxelles January 29, 2003.
2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Aihua Li Yanchen Bo
H51A-01 Evaluation of Global and National LAI Estimates over Canada METHODOLOGY LAI INTERCOMPARISONS LEAF AREA INDEX JUNE 1997 LEAF AREA INDEX 1993 Baseline.
Citation: Moskal., L. M. and D. M. Styers, Land use/land cover (LULC) from high-resolution near infrared aerial imagery: costs and applications.
Identifying wetlands As per Wetland Rules (2010).
SeaWiFS Highlights July 2002 SeaWiFS Celebrates 5th Anniversary with the Fourth Global Reprocessing The SeaWiFS Project has just completed the reprocessing.
High Spatial Resolution Land Cover Development for the Coastal United States Eric Morris (Presenter) Chris Robinson The Baldwin Group at NOAA Office for.
GEOGRAPHY TERMS THESE ARE THE KEY TERMS/FEATURES ASSOCIATED WITH THE PHYSICAL GEOGRAPHY OF OUR PLANET LEARN THEM…..KNOW THEM…..LIVE THEM!!!!!
Integrating LiDAR Intensity and Elevation Data for Terrain Characterization in a Forested Area Cheng Wang and Nancy F. Glenn IEEE GEOSCIENCE AND REMOTE.
Biomes and Aquatic Ecosystems
The Ramsar Convention on Wetlands
Aquatic Ecosystems Chapter 7.
Terrestrial and Aquatic Biomes
David Gustafsson, Kristina Isberg, Jörgen Rosberg
Water-based regions home to a unique group of living things.
Key Knowledge At least two acts or conventions related to the management and sustainability of outdoor environments, including at least one from.
Paulo Gonçalves1 Hugo Carrão2 André Pinheiro2 Mário Caetano2
Limei Ran and Alison Eyth
4-4 Aquatic Ecosystems Water covers ¾ of Earth, has an average depth of 3.7 (deepest part is 11 km – 6.8 mi) miles, contains about 3% salt and only 3%
Image Information Extraction
Planning a Remote Sensing Project
Pushing THE LIMIT What limits the size of populations?
4-4 Aquatic Ecosystems Water covers ¾ of Earth, has an average depth of 3.7 (deepest part is 11 km – 6.8 mi) miles, contains about 3% salt and only 3%
Chapter 4.4 Aquatic ecosystems.
Igor Appel Alexander Kokhanovsky
4:4 Aquatic Ecosystems Water covers ¾ of Earth, has an average depth of 3.7 (deepest part is 11 km – 6.8 mi) miles, contains about 3% salt and only.
Aquatic Biomes.
The role of Earth Observation in monitoring and reporting SDG Indicator Jason Jabour, UN Environment,
Presentation transcript:

Wetlands mapping in North America using MODIS 500m imagery July 28, 2011 ○ Gegen Tana a, Ryutaro Tateishi b a Graduate Schools of Science, Chiba University b Center for Environmental Remote Sensing (CEReS), Chiba University

What is a wetland?

Background - Definition of wetlands (Broadly used) Ramsar Convention: The Convention on Wetlands, signed in Ramsar, Iran, in 1971, is an intergovernmental treaty which provides the framework for national action and international cooperation for the conservation and wise use of wetlands and their resources. (source – the Convention on Wetlands website) The Ramsar convention (Ramsar 2004) defined wetlands as areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six meters.

- Global wetlands locations in the Ramar Convention 160 countries participate in and 1953 wetlands are contained. Total surface area of designated sites (hectares): 190,455,433 (source – the Convention on Wetlands website) The Ramsar definition of "wetlands" is a broad one, including not just marshes, fen and peatland, but also lakes, coral reefs, temporary pools, even underground caves, and all sorts of other systems everywhere from the mountains to the sea, including man-made habitats. Background

- The values of wetlands The provision of water A supplement of groundwater Regulation of water quantity & flood control Wildlife habitat Retention of nutrients and carbon Wetlands are one of the most important ecosystems in the world. It is important to inventory and monitor wetlands. A source of methane gas

Background - Global wetland databases Problems existed in the wetlands maps on large scale: Global wetland databases: Global land cover maps which include wetlands:  Global wetland distribution ( )  Global distribution of wetlands map ( )  Global lakes and wetlands database ( )  GLC2000  GLCNMO  GLOBCOVER  Underestimate wetlands areas due to the spectral heterogeneity of wetlands.  Difficult to separate wetlands from other vegetation types such as forest, herbaceous and shrub.

 To extract wetlands in North America using MODIS 2008 data Objective Advantages of MODIS data: With high frequency repeat coverage Significant potential for mapping large wetland extent and dynamics Lower cost

Study area North America is defined in this study as Canada, United States, Mexico, the countries of Central America and the Caribbean Islands.

MCD43A4: Terra+Aqua Nadir BRDF-Adjusted Reflectance 16-Day L3 Global 500m SIN Grid V005 (All 23 periods of 2008) Spectral bands (1-7): Data used - Nadir BRDF-Adjusted Reflectance

Data used - Digital elevation model and reference data Digital elevation model: Reference data:  Landsat ETM+, 30m (Around 2008)  Existing land cover maps (GLCNMO, GLC2000, GLOBCOVER)  Google Earth images  Ramsar Convention sites  SRTM DEM, 90m (version 4.1)

CodeClass nameR,G,B (color code) 1Broadleaf evergreen forest0,50,0 2Broadleaf deciduous forest60,150,0 3Needleleaf evergreen forest0,110,0 4Needleleaf deciduous forest85,110,25 5Mixed forest0,200,0 6Tree open140,190,140 7Shrub190,190,0 8Herbaceous255,255,50 9Herbaceous with sparse tree / shrub180,230,100 10Sparse vegetation255,255,205 11Cropland255,175,80 12Paddy field145,50, Cropland / other vegetation mosaic220,160, Mangrove155,130,230 15Wetland180,250,240 16Bare Area,consolidated(gravel,rock)150,150,150 17Bare Area,unconsolidated (sand)200,200,200 18Urban255,0,0 19Snow / ice250,250,250 20Water bodies175,210,240 - Land cover legend 20 land cover classes are defined by Land Cover Classification System (LCCS) Definition

- Definition of wetlands in LCCS Wetland formula in LCCS2: Closed to Open Woody Vegetation Water Quality: Fresh Water // Closed to Open Woody Vegetation Water Quality: Brackish Water // Closed to Open Herbaceous Vegetation. Water Quality: Fresh Water or Brackish Water. Depending on the level of Total Dissolved Solids (TDS) expressed in parts per million (ppm), three classes are distinguished: fresh, brackish and saline water (Cowardin et al., 1979). 1) Fresh Water: Less than ppm TDS. 2) Brackish Water: Between and ppm TDS. 3) Saline Water: More than ppm TDS The main layer consists of closed to open woody vegetation. The crown cover is between 100 and 15%. The height is in the range of 7 - 2m. The main layer consists of closed to open herbaceous vegetation. The crown cover is between 100 and 15%. The height is in the range of m. Three main components: Hydrology, Soil and Vegetation LCCS definition: Land cover definition by Land Cover Classification System version 2 (LCCS2) developed by FAO ( Definition

Vegetated area Validation Wetland map Non-vegetated area Methodology - The flow of the study 23 period of MCD43A4(2008) NDWI Preprocessing Reference data Training data GLCNMO STRM 90m NDSI MODIS Tasseled Cap Indices Maximum likelihood classification Decision tree model III IV V I II

Methodology - Part I: MODIS preprocessing Download the MCD43A4 Mosaic the tiles Resampling Modis Reprojection Tool (MRT) Cloud removal Reprojection Cloud free data

MODIS TC coefficients (Lobster et al.(2007)): MODIS Tasseled Cap Indices: The tasseled cap transformation was first developed in 1976 for Landsat MSS data. It is one of the available methods for enhancing spectral information of Landsat TM. The tasseled cap transformation was extended to MODIS data (Zhang et al.(2002). Three of the six tasseled cap transform bands are often used. ZHANG, X.Y., SCHAAF, C.B., FRIEDL, M.A., STRAHLER, A.H., GAO, F. and HODGES, J.F.C.,2002, MODIS tasseled cap transformation and its utility. In Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS ’02), edited by, Toronto, Canada, 24–28 June (Piscataway, NJ: IEEE), pp. 1063–1065. LOBSER, S.E., COHEN, W.B., 2007, MODIS tasselled cap: land cover characteristics expressed through transformed MODIS data. International Journal of remote Sensing, 28, pp. 5079–5101. Brightness: Measure of vegetation and soil Greenness: Measure of vegetation Wetness: Interrelationship of soil and canopy moisture - Part II: MODIS Tasseled Cap Indices Methodology

Normalized Difference Water Index (NDWI): Normalized Difference Snow Index (NDSI): (Gao, 1996) - Part II: NDWI & NDSI Bo-Cai G.NDWI--A normalized difference water index for remote sensing of vegetation liquid water from space, Remote sensing of environment, 1996, pp Dorothy K. Halla, George A. Riggsb and Vincent V. Salomonsonc. NDSI:Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data Remote Sensing of Environment, 1995 (D.K Halla, 1996) Methodology

- Part III: Dominant wetland types in North America (source – the Convention on Wetlands website) O — Permanent freshwater lakes (over 8 ha) H — Intertidal marshes; includes salt marshes, salt meadows, saltings, raised salt marshes; includes tidal brackish and freshwater marshes. Tp - Permanent freshwater marshes/pools; ponds (below 8 ha), marshes and swamps on inorganic soils; with emergent vegetation water-logged for at least most of the growing season. F — Estuarine waters; permanent water of estuaries and estuarine systems of deltas. J — Coastal brackish/saline lagoons; brackish to saline lagoons with at least one relatively narrow connection to the sea. A — Permanent shallow marine waters in most cases less than six metres deep at low tide; includes sea bays and straits. E — Sand, shingle or pebble shores; includes sand bars, spits and sandy islets; includes dune systems and humid dune slacks. I — Intertidal forested wetlands; includes mangrove swamps, nipah swamps and tidal freshwater swamp forests. G — Intertidal mud, sand or salt flats. Xf - Freshwater, tree-dominated wetlands; includes freshwater swamp forests, seasonally flooded forests, wooded swamps on inorganic soils. Methodology

- Part III: Types of wetlands and Landsat ETM+ 1. Training data should satisfy the LCCS definition. Principles of training data collection: Totally 31 scenes of Landsat ETM+ images were used for collecting training sites. Methodology Forest/Shrub dominant wetland (Inland) Herbaceous dominant wetland (Inland) Sea grass dominant wetland (Coastal) According to the vegetation types described in the LCCS, wetlands in North America were classified into three types. 2. MCD43A4 is MODIS data with the spatial resolution of 500m. The pure training site area should be selected larger than 250ha (3×3 pixels).

Methodology - Part III: Training data collection Common part of existing maps Google Earth Ramsar Convention Landsat ETM+ Google Earth Non-vegetated* 1 and vegetated * 2 land cover types Wetland Collection of training data *1: Water, Snow, Urban, Bare (Rock&Sand) *2: Broadleaf evergreen forest, Broadleaf deciduous forest, Needleleaf evergreen forest, Needleleaf deciduous forest, Mixed forest, Tree open, Shrub, Herbaceous, Herbaceous with sparse tree/shrub, Sparse vegetation, Cropland, Paddy field, Cropland/other vegetation mosaic, Mangrove,

Methodology - Part IV: Decision tree model STRM 90m <1000m NDWI_8< Water Snow Wetland&Other vagetation NDSI_P10< Mask of Urban&Bare area (GLCNMO) Resampling No Yes No

Methodology - Part V: Maximum likelihood method  Input satellite data: MODIS Tasseled Cap Indices (Brightness, Greenness, Wetness)  Period of data: Totally 12 periods, 36 scenes. (1,4, 8,11-18, 20,22)  Training data: Wetland (3 types) and other vegetated land cover types (According to the monthly changed Tasseled Cap _Greenness pattern, each land cover type was subclassified. )  Integration: After classification, vegetated land cover types were integrated as “Others”, three types of wetlands were integrated as “wetland”.

Result Wetlands Others Water

Comparison (1) - Everglades National Park (United States) Google Earth image Result of this study GLOBCOVER GLC2000

Comparison (2) Result of this study GLOBCOVER GLC2000 - Reserva de la Biosfera Ría Celestún (Mexico) Google Earth image

Conclusions and future works In this study, wetlands defined in the LCCS were classified into three types and wetlands in North America with large spatial extent were successfully extracted. MODIS tasseled Cap Indices (brightness, greenness and wetness), SRTM 90m, NDWI and NDSI were confirmed useful for extracting wetlands. However, because of the spectral heterogeneity of wetlands, some small extent of wetlands and narrow wetlands were failed to be extracted in this study. Other reference data like Landsat ETM+ should be considered for mapping small and narrow wetlands. Quantitative validation should be also performed by using ground truth data. (National Wetland Inventory: ) Subclasses of land cover types especially for wetlands were very effective for classification in this study. Develop a wetland map of 2008 for global scale.

Thank you for your attention!

- Characteristics of remote sensing data for mapping wetlands Advantages: With high frequency repeat coverage Significant potential for mapping large wetland extent and dynamics Lower cost Benefit on mapping wetlands in local and regional scales With high accuracy in mapping small extent of wetlands Advantages: Disadvantages: Unavoidably underestimate wetland area due to the small and fragmented nature of many wetlands Lower map accuracy Difficult to get global or continent range of wetlands map Time consuming for mapping large wetlands Higher cost (SAR data) High spatial resolution remote sensing data: Moderate spatial resolution remote sensing data: Background

- Global wetland databases Name:Global wetland distribution Resolution: Year:1987 Name:Distribution of wetlands Resolution: Year: Wetlands Name: GLC2000 Resolution: 1km Year:2000 Name: GLCNMO Resolution: 1km Year:2003 Name: GLOBCOVER Resolution: 300m Year:2005 Name:Global lakes and wetlands database Resolution:1km Year:2004