| snippet:
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This map shows cover of mangrove vegetation along Lamu County Coastline for the period 2018/2019. |
| summary:
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This map shows cover of mangrove vegetation along Lamu County Coastline for the period 2018/2019. |
| extent:
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[[40.6940823240001,-2.39848441499993],[41.510578814,-1.73843895999994]] |
| accessInformation:
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WWF-Kenya, KMFRI, KFS |
| thumbnail:
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thumbnail/thumbnail.png |
| typeKeywords:
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["Data","Service","Map Service","ArcGIS Server"] |
| description:
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The mangrove layer was generated to depict dorminant species formation in 5 key Mangrove Swamps (Blocks) as defined by Kenya Forest Service (KFS) in the Mangrove Management Plan. Semi-Automated remotesensing approaches were used to map and maximise consistency and accuracy of discriminating mangroves from other vegettative cover.
2.3.1 Mapping current mangrove extent
This method begun with step1. Radiometric calibration of the Landsat bands converting DN values into top of atmosphere (TOA) planetary reflectance. Followed by step2. Generation of the Combined Mangrove Recognition Index (CMRI) which is considered highly accurate in discriminating mangroves from non-mangrove features (Kaushik G, 2018) by utilizing the greenness and wetness index values considering both high and low tide seasons .Subsequently a combination of standard indices were developed like Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index(NDWI). The following band ratios were therefor calculated red and shortwave infrared (SWIR), and SWIR and NIR, and Green and NIR band ratios. Indices applied in assessing mangrove
Index Formulas Reference
Normalized Difference Vegetation Index (NDVI) (NIR – RED)
(NIR + RED) (Pearson etal, 1972)
Normalized Difference Water Index (Green - NIR)
(Green + NIR) (Gao, 1996)
Combined Mangrove Recognition Index (CMRI) (NDVI - NDWI) (Kaushik G, 2018)
Step4 was the actual analysis of the mangrove, this study was interested with both extent and species formation. Several classification methods were tested but the unsupervised ISOData provided the most accurate results. In step 5, the results from unsupervised classification was then recoded based on field ground truth points and high resolution imagery into several species formations observed. Step 6 was accuracy assessment after which the final mangrove species formation layer for 2018/2019 epoch was released.
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| licenseInfo:
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This layer is not an authority, Overall species formation accuracy 71.3%, Kappa Statistic 0.6153 |
| catalogPath:
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| title:
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LamuMangroves2019 |
| type:
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Map Service |
| url:
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| tags:
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["Lamu","NDC","Blue Carbon","Forest","Mangroves","Climate Change"] |
| culture:
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en-US |
| name:
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Mangroves_Classification2019 |
| guid:
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9D6F917D-D4D6-4B83-9721-5046D34507EF |
| spatialReference:
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GCS_WGS_1984 |