View In:
ArcGIS JavaScript
ArcGIS Online Map Viewer
ArcGIS Earth
ArcGIS Pro
Service Description: 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.
Map Name: Layers
Legend
All Layers and Tables
Dynamic Legend
Dynamic All Layers
Layers:
Description:
Service Item Id: 5c4a6757e4114fd1bff6906e969b9413
Copyright Text: WWF-Kenya, KMFRI, KFS
Spatial Reference:
4326
(4326)
Single Fused Map Cache: false
Initial Extent:
XMin: 39.49844949086391
YMin: -2.8469475468950165
XMax: 41.60238295386726
YMax: -1.4539879734925103
Spatial Reference: 4326
(4326)
Full Extent:
XMin: 40.69408232400002
YMin: -2.3984844149999844
XMax: 123.32374126800005
YMax: 14.030708984
Spatial Reference: 4326
(4326)
Units: esriDecimalDegrees
Supported Image Format Types: PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP
Document Info:
Title: LamuMangroves2019
Author: Siro Abdallah (WWF- Kenya), Fred Mungai (Kenya Marine and Fisheries Authority(KMFRI))
Comments: 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.
Subject: This map shows cover of mangrove vegetation along Lamu County Coastline for the period 2018/2019.
Category:
Keywords: Lamu,NDC,Blue Carbon,Forest,Mangroves,Climate Change
AntialiasingMode: None
TextAntialiasingMode: Force
Supports Dynamic Layers: true
MaxRecordCount: 1000
MaxImageHeight: 4096
MaxImageWidth: 4096
Supported Query Formats: JSON, geoJSON, PBF
Supports Query Data Elements: true
Min Scale: 0
Max Scale: 0
Supports Datum Transformation: true
Child Resources:
Info
Dynamic Layer
Supported Operations:
Export Map
Identify
QueryLegends
QueryDomains
Find
Return Updates
Generate KML