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John Lowry and Students from GS211 (Remote Sensing I) Semester 2, 2013.

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Presentation on theme: "John Lowry and Students from GS211 (Remote Sensing I) Semester 2, 2013."— Presentation transcript:

1 John Lowry and Students from GS211 (Remote Sensing I) Semester 2, 2013

2 NASA Earth Observatory Image of the Day Dubai, UAE ASTER Image Feb 8, 2010 IOTD Mar 12, 2010

3 Sydney Hall Road Fire Linksview Road Fire State Mine Fire NASA Earth Observatory Image of the Day Fires Around Sydney, Austraila MODIS Image Oct 17, 2013 IOTD Oct 18, 2013

4 NASA Earth Observatory Image of the Day Sundarbans, Bangladesh Landsat 7 Image Nov 24, 1999 IOTD Oct, 2006

5 NASA Earth Observatory Image of the Day Fiji Islands MODIS Image Jul 21, 2011 IOTD Aug 13, 2011

6  Student learning more meaningful with “hands-on” learning through project-based activities  Remote sensing students at USP create first MODIS-based land use/cover map for Fiji Islands  Learning/teaching fundamentals of remote sensing accomplished using tools in ArcGIS & Google Earth

7  Launched in 1999  Terra & Aqua Satellites  36 spectral bands  250 m (bands 1 & 2)  500 m (bands 3-7)  1000 m (bands 8-36) BandBandwidthDescription o.67 µmRed µmNear IR µmBlue µmGreen µmMid IR µmMid IR µmMid IR

8 Primary Elements Color Tone (light-dark) Spatial Arrangement of Tone and Color Spatial Arrangement of Tone and Color Size Shape Texture Pattern Based on Analysis of Primary Elements Height Shadow Contextual Elements Site Association

9  Principal Vegetation Types of Fiji from Mueller-Dombois and Fosberg (1998) 10 Cloud Forest 20 Upland Rainforest 30 Lowland Rainforest 40 Mixed Dry Forest 50 Talasiga (grassland) 60 Mangrove forest and scrub 70 Plantation & Production 71 Hardwood Plantation 72 Softwood Plnatation 73 Coconut Palm 80 Anthropogentic Landscapes 81 Urban/Developed 82 Agriculture 90 Waterscapes 91 Water 92 Coral reef 100 Cloud cover

10 Fiji Landcover Key Colour: Black, Blue & Grey Colour & tone: surface is smooth, uninterrupted blackish-blue expanse 91_WATER Colour & tone: Surface varies between greenish- blue and turquoise with irregular prey patches 92_CORAL REEFS Colour: Green, Brown and White Colour & tone: Surface is less than 95%, of a lighter tone and also consists of brown patches Pattern: Surface pattern of rows of "bumpy" shapes, spaced at regular intervals 73_COCONUT PLANTATION Pattern: Surface mainly covered with flat expanse with few scattered aggregates of darker green 50_TALASIGA GRASSLANDS Colour & tone: Surface is at least % green, of medium dark to very dark tone Texture & pattern: Surface appears medium to highly coarse/rough, consisting of large aggregates /masses of green covering % of image area Site: Elevation above 400m Site & association: Located at m, on ridges. 10_CLOUD RAINFOREST Site: located at m 20_UPLAND RAINFORST Site: Located below 600m 30_LOWLAND RAINFOREST Site: Elevation below 400m Site & association: Found on leeward side of slopes 40_MIXED DRY RAINFOREST Site & association: Found exclusively near water bodies 60_MANGROVE RAINFOREST Texture & pattern: Surface appears lightly or finely coarse/rough, with smaller aggregates of green covering less that 80% of image. White regular shapes of buildings present Pattern: Large aggregates of white buildings, curvilinear road networks, exposed bare patches of soil. 81_URBAN/SUBURBAN /DEVELOPED Pattern: Few scattered houses. Landscape largely divided into regular rid shapes with greenery and patches of brown exposed soil 82_AGRICULTURE Texture & pattern: Surface appears medium coarse with aggregates of greenery broken up by network or roads, buildings near the edges. 72_SOFTWOOD PLANTATION

11 Talasiga (Grassland)Upland Rainforest Agriculture

12 Mapping zones created: Visually merged groups 2-3 Tikinas in ArcMap

13 Footprint created: Conversion Tools > From Raster > Raster to Polygon Converted to KML: Conversion Tools > To KML > Layer To KML

14  Each student:  Digitizes polygons in mapping zone  Interprets homogenous land use/cover types that are 3+ footprint grid cells in size  Assigns numeric label to each sample polygon  Converted & Merged to ESRI Geodatabase Conversion to Geodatabase: Conversion Tools > From KML> KML to Layer (Batch) Then, Data Management > General > Merge

15  Roughly 900 sample polygons total  After cleaning, 790 sample polygons total  Randomly divided: 50% Training 50% Accuracy Randomized division: Geostatistical Analyst > Utilities > Subset Features

16  Students experimented with EQUAL and SAMPLE prior probabilities  Produced classified maps and error matrices  Compared results visually & quantitatively Create signatures: Spatial Analyst > Multivariate > Create Signature Classification: Spatial Analysts > Multivariate >Maximum Likelihood Classifier

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18 Reference Data Mapped Data Cloud For % Up. Rainfor % Lo. Rainfor % Mix Dry For % Talasiga % Mangrove % Developed % Agriculture % Water % Coral Reef % Cloud Cover % %10%38%48%32%50%67%56%68%88%100% Overall Accuracy: 48.84% Kappa Coefficient: Accuracy Assessment: Kappa Stats tool (Python script) from

19 Create signatures: Spatial Analyst > Multivariate > Create Signature  Graph in Excel

20 Elevation: 100 m resolution Ave July Precip: 100 m resolution Resample to 500 m: Data management> raster > resample Normalized to same range as imagery: Spatial analyst > map algebra > raster calculator Create “Layer stack”: Data management > raster > raster processing > composite bands

21 Create signatures: Spatial Analyst > Multivariate > Create Signature  Graph in Excel

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23 Reference Data Mapped Data Cloud For % Up. Rainfor % Lo. Rainfor % Mix Dry For % Talasiga % Mangrove % Developed % Agriculture % Water % Coral Reef % Cloud Cover % %39%79%67%44%50%83%68% 92%100% Overall Accuracy: 70.18% Kappa Coefficient: Accuracy Assessment: Kappa Stats tool (Python script) from

24  Students experienced land use/cover classification project start-to-finish  Learned skills & understand theory by practice  Visual interpretation, sampling, spectral signatures, supervised classification, data fusion, accuracy assessment  1:1,000,000* scale land use/cover map of Fiji Islands (2011)  Improvements with more training samples  Further experimentation, PCA, 250 m res. * Based on Tobler’s (1987) Rule of Thumb that map scale is 1,000 times double the pixel size ( Another useful website:

25 Thank You!


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