Using ALOS/PALSAR and RADARSAT-2 to Map Land Cover and Seasonal Inundation in the Brazilian Pantanal Teresa Evans Maycira Costa

Slides:

Advertisements

Similar presentations

Lab for Remote Sensing Hydrology and Spatial Modeling Dept. of Bioenvironmental Systems Engineering, NTU Satellite Remote Sensing for Land-Use/Land-Cover.

Advertisements

U.S. Department of the Interior U.S. Geological Survey USGS/EROS Data Center Global Land Cover Project – Experiences and Research Interests GLC2000-JRC.

Using ALOS/PALSAR, RADARSAT ‐ 2 & ENVISAT/ASAR Imagery to Define Habitats in the Nhecolândia Region, Brazilian Pantanal Teresa Evans

September 5, 2013 Tyler Jones Research Assistant Dept. of Geology & Geography Auburn University.

Regionalization of Methane Emission from the Amazon Basin with Microwave Remote Sensing John M. Melack University of California, Santa Barbara Laura L.

Jet Propulsion Laboratory California Institute of Technology The NASA/JPL Airborne Synthetic Aperture Radar System (AIRSAR) Yunling Lou Jet Propulsion.

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.

Estimating forest structure in wetlands using multitemporal SAR by Philip A. Townsend Neal Simpson ES 5053 Final Project.

ORNL DAAC ORNL DAAC: SAR Data Use Applying SAR subsets for scientific use Using SAR data to identify freeze-thaw.

ReCover for REDD and sustainable forest management EU ReCover project: Remote sensing services to support REDD and sustainable forest management in Fiji.

Climate Variability and Prediction in the Little Colorado River Basin Matt Switanek 1 1 Department of Hydrology and Water Resources University of Arizona.

Classification of Tidal Wetland Communities Using Multi-temporal, Single Season Quickbird Imagery Emily Wilson, Sandy Prisloe, James Hurd & Dan Civco Center.

IPY Satellite Data Legacy Vision: Use the full international constellation of remote sensing satellites to acquire spaceborne ‘snapshots’ of processes.

Published in Remote Sensing of the Environment in May 2008.

Akira Kato 1, Manabu Watanabe 2, Tatsuaki, Kobayashi 1, Yoshio Yamaguchi 3,and Joji Iisaka 4 1 Graduate School of Horticulture, Chiba University, Japan.

Has EO found its customers? 1 Space Applications Institute Directorate General Joint Research Centre European Commission Ispra (VA), Italy

Global Inter-agency IPY Polar Snapshot Year (GIIPSY): Goals and Accomplishments Katy Farness & Ken Jezek, The Ohio State University Mark Drinkwater, European.

Wetlands By: Gus Naughton.

An Object-oriented Classification Approach for Analyzing and Characterizing Urban Landscape at the Parcel Level Weiqi Zhou, Austin Troy& Morgan Grove University.

A SYNERGETIC USE OF ACTIVE MICROWAVE OBSERVATIONS, OPTICAL IMAGES AND TOPOGRAPHY DATA FOR IMPROVED FLOOD MAPPING IN THE GULF OF MEXICO AREA Marouane Temimi.

JAXA Agency Report ~The Latest Status on “ALOS Kyoto & Carbon Initiative” CEOS Plenary Doc. 31 Satoko Horiyama MIURA JAXA 1 23 rd CEOS Plenary I Phuket,

Microwave Remote Sensing Group 1 P. Pampaloni Microwave Remote Sensing Group (MRSG) Institute of Applied Physics -CNR, Florence, Italy Microwave remote.

ALOS-2 Mission Status and Basic Observation Scenario (BOS)

Using spectral data to discriminate land cover types.

DOCUMENT OVERVIEW Title: Fully Polarimetric Airborne SAR and ERS SAR Observations of Snow: Implications For Selection of ENVISAT ASAR Modes Journal: International.

BUILDING EXTRACTION AND POPULATION MAPPING USING HIGH RESOLUTION IMAGES Serkan Ural, Ejaz Hussain, Jie Shan, Associate Professor Presented at the Indiana.

Slide: 1 CEOS SDCG-2 Meeting|Reston, Virginia, USA| September 2012 CEOS Data Acquisition Plan – Global Baseline strategy (Level 1) EO monitoring.

Long Time Span Interferograms and Effects of Snow Cover on Interferometric Phase at L-Band Khalid A. Soofi (ConocoPhillips), David Sandwell (UCSD, SCRIPPS)

Michigan Tech Research Institute (MTRI)  Michigan Technological University 3600 Green Court, Suite 100  Ann Arbor, MI (734) – Phone 

The use of 7 Be to quantify downstream trends in sediment transport below a flood-control dam Paper number: H53B-1237 Results 7 Be-derived transport rates.

The study area is the Sub-Saharian Africa. According to the IGBP vegetation map the major vegetation types present in the area include savanna and woody.

Vegetation Mapping An Interagency Approach The California Department of Forestry and Fire Protection and the USDA Forest Service Mark Rosenberg: Research.

Monitoring Tropical forests with L-band radar: lessons from Indonesian Peat Swamps Matt Waldram, Sue Page, Kevin Tansey Geography Department.

Paddy Damage Assessment due to Cyclonic Storm using Remotely Sensed Data By ABHIJAT ARUN ABHYANKAR October 4, 2010.

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.

Wetlands By: Gus Naughton. What are wetlands? A wetland is an area of land whose soil is saturated with moisture either permanently or seasonally. Such.

The global hydrologic cycle Ground water, surface water, soil moisture, snow pack, glaciers, ocean, atmosphere.

Envirothon. What is it? ○ Envirothon is an annual competition in which teams compete for recognition and scholarships by demonstrating their knowledge.

Comparison of L and P band radar time series for the monitoring of Sahelian area P.-L. Frison, G. Mercier, E. Mougin, P. Hiernaux.

Scaling Up Above Ground Live Biomass From Plot Data to Amazon Landscape Sassan S. Saatchi NASA/Jet Propulsion Laboratory California Institute of Technology.

Systematic Terrestrial Observations: a Case for Carbon René Gommes with C. He, J. Hielkema, P. Reichert and J. Tschirley FAO/SDRN.

Manifestation of Land Use/Land Cover Change Analysis and Its Impacts on Soil Properties in Gadarif Region, Sudan Faculty of Forest, Geo and Hydro Sciences,

0 Riparian Zone Health Project Agriculture and Agri-Food Canada Grant S. Wiseman, BS.c, MSc. World Congress of Agroforestry Nairobi, Kenya August 23-28,

Object-oriented Land Cover Classification in an Urbanizing Watershed Erik Nordman, Lindi Quackenbush, and Lee Herrington SUNY College of Environmental.

Roger De Abreu, Matt Arkett, Dean Flett Canadian Ice Service Pablo Clemente-Colón, Sean Helfrich, Brian Melchior U.S. National Ice Center Evaluation of.

Measurement of a Temporal Sequence Of DInSAR Phase Changes Due to Soil Moisture Variations Keith Morrison 1, John Bennett 2, Matt Nolan 3, and Raghav Menon.

Mapping Canada’s Rangeland and Forage Resources using Earth Observation Emily Lindsay MSc Candidate – Carleton University Supervisors: Doug J. King & Andrew.

The Pacific GIS/RS User Conference Suva, Fiji Island, November 2012 Sharon R. Boe, SPC/GIZ-SOPAC ) SPC/GIZ Regional REDD+ Project:

 Geospatial Information for Climate Change and Disaster Mitigation Shuaib Lwasa Department of Geography Geoinformatics and Climatic Sciences Makerere.

Citation: Moskal, L. M., D. M. Styers, J. Richardson and M. Halabisky, Seattle Hyperspatial Land use/land cover (LULC) from LiDAR and Near Infrared.

Assessing the Tree Canopy in Jefferson County, WV Jarlath O’Neil-Dunne University of Vermont Spatial Analysis Laboratory.

Time Dependent Mining- Induced Subsidence Measured by DInSAR Jessica M. Wempen 7/31/2014 Michael K. McCarter 1.

High Spatial Resolution Land Cover Development for the Coastal United States Eric Morris (Presenter) Chris Robinson The Baldwin Group at NOAA Office for.

Dengsheng Lu Professor Center for Global Change and Earth Observations Michigan State University, East Lansing, Michigan April.

LAND USE/LAND COVER CHANGE IN BEXAR COUNTY, TEXAS Maryia Bakhtsiyarava FNRM 5262.

Resource Appraisal with Remote Sensing techniques A perspective from Land-use/Land-cover by Basudeb Bhatta Computer Aided design Centre Computer Science.

Using SAR Intensity and Coherence to Detect A Moorland Wildfire Scar.

1 Thursday 04-Jun ASAR WORKSHOP 2011 Canadian Government Calibration Operations within the RADARSAT Program Assessment of Distributed Target Sites.

Mapping Vegetation with Synthetic Aperture Radar:

Matthew Casali and Robert Fahey

Ecosystem Model Evaluation

Developing the Vegetation Drought Response Index (VegDRI): Monitoring Vegetation Stress from a Local to National Scale Dr. Brian Wardlow National Drought.

Built-up Extraction from RISAT Data Using Segmentation Approach

Factsheet # 9 Decadal Analysis of Wetland & Agricultural Change

HIERARCHICAL CLASSIFICATION OF DIFFERENT CROPS USING

Objectives Using a time series of data from radar sensors to detect and measure forest changes Combining different types of data, including: Multi polarisations.

An Introduction to VegDRI

Website: Contact No: ID:

الدكتور: أحمد رأفت غضية صفاء عبد الجليل كامل حمادة

Forest / Non-forest (FNF) mapping for Viet Nam using PALSAR-2 time series images 2019/01/22 Truong Van Thinh – Master’s Program in Environmental.

Presentation transcript:

Using ALOS/PALSAR and RADARSAT-2 to Map Land Cover and Seasonal Inundation in the Brazilian Pantanal Teresa Evans Maycira Costa University of Victoria, Department of Geography, SPECTRAL Laboratory

Study Area – The Brazilian Pantanal

Importance, threats…

Radar Backscatter Variability

HIERARCHICAL CLASSIFICATION STRATEGY Multiresolution Segmentation using ALOS Feb and July, RSAT HH/HV Multiple hierarchical classification rules determined based on objects values and backscattering variability Level 1 Level 2 Open Water Aquatic Vegetation Savanna Forest Multiresolution Segmentation - single date ALOS imagery > -5dB Flooded Forest < -5dB Non-Flooded Forest Grassland/Agriculture < -18dB Flooded Grassland/Agriculture > -18dB Non-Flooded Grassland/Agriculture Jan-07Feb-07May-07Jul-07Aug-08Nov m 50m100m HH HH/HVHH L-band C-bandL-band

Level 1 Overall Accuracy ~ 81% Highest degree of confusion between Savanna class and both Forest, and Grasslands/Agriculture due the high degree of cross-over between classes

Level 2 The first temporal flood distribution data of the entire Pantanal over one hydrological cycle

Current research...(new and improved!) Jan-07Feb-07 Feb/Mar- 08Apr-09May-07Jul-07 Aug/Sept -08Aug-08Aug-09Oct-07Nov m 50m100m 50m 100m HH HH/HVHH L-band C-bandL-band Fine spatial resolution 12.5m L and C-band dual- season for Nhecolândia sub- region; Additional dates and addition of dual- season 50m for coarse resolution Pantanal flood analysis for 100m

Will be used for: 1) ongoing local habitat studies in the region (marsh deer, jaguar) 2) Baseline data for monitoring 3) Important information to aid in defining conservation areas

Acknowledgements SAR Imagery Ancillary Data FUNDING! FOR MORE INFORMATION… Contact me (Teresa Evans) Or visit my website: Questions?