iGETT Exercise Classify PowerPoint

Supporting Conservation Efforts and Aiding in Poaching Reduction with Satellite Imagery and Geospatial

Analysis in a Zambian National Park

Graphics and Screenshots

iGETT Lesson Land Cover Classifications

South Luangwa National Park, Zambia, Africa

Michelle Kinzel, kinzelm@cox.net

Zambia, Africa

Landsat 8 Satellite Data Row 170 Path 69

South Luangwa National Park

Selecting Satellite Images from Earth Explorer What images to compare?

1. Define ideal times. Choose end of dry season and end of wet season. Use graphs and

descriptions provided.

Wet versus Dry Season

Wet Versus Dry Season • Zambia’s weather in general • • Zambia is situated in the tropics and receives good rainfall. It has a dry season from May to the end of October and a wet

season from November to April. At this time many areas become inaccessible and most camps in Kafue, Lower Zambezi and more remote parks close down. The Mfuwe sector of South Luangwa is accessible year-round. The further north, the earlier the rains arrive and the later they leave. Eastern and higher areas generally receive more rain than western and lowland areas. The dry season is divided into the cool dry season (May to August) and the hot dry season (September and October).

• Dry season - May to October - Winter •

• Zambia Dry Season • Dry Season There is little to no rainfall during the entire winter and humidity is very low. Wildlife will congregate around

waterholes when other water resources become scarce. May - This is the end of summer. Temperatures are relatively cool, typically 12°C/52°F in the morning and 25°C/77°F in the afternoon. The nighttime temperatures start to drop. The rain is almost gone.

• June, July & August - The average morning temperature is 10°C/50°F. So it is advised to bring warm winter clothing for the cold morning game drives in open vehicles. Afternoons will be more pleasant with temperatures around 23°C/73°F. South Luangwa, Lower Zambezi and other parks at lower altitude will be hotter.

• September & October - The heat gradually builds and the first rains bring relief from very dry conditions. Daytime temperatures will be around 29°C/84°F in September and 31°C/88°F in October, which is the hottest month. In the lower-lying parks, temperatures often peak at over 40°C/104°F and the rising humidity can make it uncomfortably hot.

• Wet season - November to April - Summer •

• Zambia Wet Season • Wet Season November - This month is unpredictable and it starts raining some afternoons. Temperatures are between

18°C/64°F in the morning and 29°C/84°F in the afternoon. • December, January & February & March - These are the wettest months, characterized by torrential downpours in the

afternoon. Afternoon temperatures are around 26°C/78°F and the humidity is high.

Images on Earth Explorer Selecting Satellite Images from Earth Explorer

Satellite Platform - Landsat 8 – 2013

2. Search Earth Explorer for Date Range you choose

1. Search for Address/Place – ‘South Luangwa National Park’

2. Click on the Address/Place in results 3. Enter Date Range You Choose 4. Select the Satellite Platform – Click on Data Sets Landsat 8 OLI/TIRS

Images on Earth Explorer Selecting Satellite Images from Earth Explorer

3. Check Images for Cloud Cover 1. Click on ‘Show Browse Overlay’ icon

2. Examine Image in Map View for cloud cover

Images on Earth Explorer Selecting Satellite Images from Earth Explorer

4. Download Image

Images on Earth Explorer Selecting Satellite Images from Earth Explorer

5. Select Image for this Project

Images on Earth Explorer Selecting Satellite Images from Earth Explorer

5. Select Image for this Project

• Also download GeoTIFF Data Product to get all Landsat 8 bands

Study Area Showing Unsupervised Classification – 10 classes

Study Area Showing Supervised Classification

Clip Raster to Study Area

Unsupervised Classification Run different classes

40 Classes

Unsupervised Classification 20 Classes

Unsupervised Classification 10 Classes

Unsupervised Iso Classification Comparison of 3 different class sizes

Unsupervised Iso Classification 40 classes

Unsupervised Iso Classification 20 classes

Unsupervised Iso Classification 10 classes

After examining the results of 3 different size classes, you should decide on an acceptable number of classes for classification – 20 classes seems just right here.

Water

Bare Ground

Riverine

Open Grass

Mopani

Mixed Pixels

Healthy Mopani

Elephant Grazing on Mopani

Overgrazed Mopani

Satellite Image with Identifiable Features

Differing Vegetation

River Line Mountain Ranges, Elevation

Assigning Training Classes Clues and Tips

1 1

1

2 2

2 3

3 3

4

4 4

River River Bed = Bare Ground Thick Vegetation Open Grass

GPS Data

Defining Classes - Water

Define Training Classes Mopani

Define Training Classes – Open Grass

Open Grass

Mopane

Mopane

Defining Classes - Mopane

Save Signature File Classify_125_2013

Histograms 5 Land Cover Classes,

Water, Bare Ground, Riverine, Open Grass and Mopane

The histograms indicate that there is complete overlap between the water and riverine classes (yellow ovals). The other 3 classes show acceptable separation (red rectangles). Based on this observation, you need to go back and reclassify the training class marked as Mopane as water and find other areas of Mopane.

Reassign ‘Mopane’ using Training Sample Manager

Histograms Even after splitting classes, the Riverine and Water are still showing overlap. Possible

explanation – the water class could be too broad, the Riverine Class could be mislabeled. We will reclassify the Riverine Class.

Histograms with Riverine Reclassified

Scatterplots

• Examining the Scatterplots provides another possible explanation. Note that the overlap is actually still clustered, showing some distinction between classes. This could indicate that Riverine Vegetation has a high water content and is registering strongly in the same bands as water.

Scatterplots, Riverine Reassigned

Statistics Water, Bare Ground, Riverine, Open Grass and Mopane

Statistics With Riverine Reassigned

Maximum Likelihood Classification Counts

Supervised Classification Julian Day - 125

Supervised Classification Julian Day 221 –

Land Cover Pixel Counts from Maximum Likelihood Classification

End of Wet Season (125 Julian Day) vs. End of Dry Season (221 Julian Day)

0

100000

200000

300000

400000

500000

600000

700000

800000

BareGround

Riverine OpenGrass

Mopane Water

Julian Day = 125

Julian Day = 221

Land Cover Percentages Dry Season (109 Julian Day) vs.

Wet Season (173 Julian Day)

(Green is Data from 2003, Julian Day 120)

0

10

20

30

40

50

60

Water Riverine Open Grass Mopane

Julian Day = 109

Julian Day = 173

Land Cover Percentages Julian Day 122

Land Cover

Water

Riverine

Open Grass

Mopani

Bare Ground

Land Cover Percentages Julian Date 221

Land Cover

Water

Riverine

Open Grass

Mopane

Bare Ground