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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, [email protected]
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