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U.S. Department of the Interior U.S. Geological Survey Monthly Progress for Africa GCEV2 Jun Xiong, Prasad, Pardha 23 October, 2014.

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Presentation on theme: "U.S. Department of the Interior U.S. Geological Survey Monthly Progress for Africa GCEV2 Jun Xiong, Prasad, Pardha 23 October, 2014."— Presentation transcript:

1 U.S. Department of the Interior U.S. Geological Survey Monthly Progress for Africa GCEV2 Jun Xiong, Prasad, Pardha 23 October, 2014

2 Content  GCE V2.3 Product  Accuracy Assessment  GCE V2.3 Documents

3 GCE V2.3 nominal 2010 for Africa

4 GCEV2.03 Characteristics Geographic WGS84 projection Columns = 39574 Rows = 32140 Pixel size = 250 meters / 0.00224579 Dd Upper left x, y = -25.36837711, 37.34827711 Dd Lower right x, y = 63.50423673, - 34.82914002 Dd Projection = Geographic (Lat/Lon) Spheroid = WGS84 Layers  Global Croplands Extent, including croplands / non-croplands  Global Croplands Intensity, including single, double, continuous (class 3) and mixed  Global Croplands Watering, including irrigated and rainfed  Global Croplands Primary Type, TBD

5 GCE V2.3 nominal 2010 for Africa

6 Samples Bank (~6000 samples) Samples data (Reference data) will be uploaded to croplands.org for peer-review and sharing Q. How to set solid border between samples for training- purpose and assessment- purpose?

7 Accuracy Assessment  Use HSegLearn to perform computer assisted photointerpretation of high resolution imagery data (< 5m) to generate ground reference sample independently.  Alternative: get reference sample from GlobCover 300m  Compared with country-wide statistics from FAO, UNEP,…etc.

8 Algorithm theoretical documentation basic  Introduction  Existing studies and limitations  Version 2.3 product for Continental Africa  Products description  Contact information  FAQs  Algorithm theoretical documentation basic  Study area  Dataset: Satellite, Field data, Very high spatial resolution imagery  Methodology  Results  References  List of Tables and Figures

9 Manuscript Multi-temporal Analysis of Satellite Data to Automated Global Cropland Mapping: A Case Study in Continental Africa (In Manuscript) Jun Xiong 1,2 *, Prasad Thenkabail 1, Pardhasaradhi Teluguntla 1,3, Justin Poehnelt 2, Kamini Yadav 4 and Cristina Milesi 5 1 Flagstaff Science Center, US Geological Survey, Flagstaff, AZ 86001, USA; E-Mail: jxiong@usgs.gov 2 School of Earth Sciences and Environmental Sustainability, Northern Arizona University, Flagstaff, AZ 86001, USA 3 Bay Area Environmental Research Institute (BAERI), 596 1st St West Sonoma, CA 95476, USA 4 Department of Natural Resources and the Environment, University of New Hampshire, 56 College 12 Road, Durham, NH 03824, USA 5 NASA Ames Research Center, Naval Air Station, Moffett Field, Mountain View, CA 94035, USA jxiong@usgs.gov

10 Related Documents  ATDB (GCEV2-ATDB.docx)  Product self-description (GCEV2- readme.html)  Sample Collection Procedures (SampleGuide.docx)  Croplands.org Training Course (cropguide.html)  Presentation slides


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