CHANGE DETECTION AND VEGETATION MONITORING OF CHIKANGAWA FOREST USING GIS AND REMOTE SENSING

Population growth has led to more pressure being faced by our environment especially forest reserves area where they compose much more of our vegetation. Monitoring environment changes has become a necessity as a result of current environment deteriorating due to human activities like deforestation. The present study provides The Normalized Difference Vegetation Index (NDVI) of the study area, Chikangawa forest. The main aim of the study is to monitor and evaluate changes in vegetation over the years, using NDVI time series output. The study had involved most of its work practically and had required involvement of remote sensing images were used for supervised classification and also GIS software such as ENVI, ArcMap and QGIS that had been used in analysis of the data collected. The NDVI technique involves the use of remote sensed data in different time series extracted from Landsat 5 and Landsat 8. The Landsat satellite images give us reliable information for monitoring vegetation change according in NDVI time series. According to the present study, the NDVI data generated gives us valuable information about vegetation. Landsat images were downloaded from United States Geological Survey (USGS) dataset website (https://earthexplorer.usgs.gov/) and these time intervals had helped to identify the changes that have happened within Chikangawa forest for the past years. The NDVI technique can be employed for monitoring vegetation cover and its values range from -1 to 1. The study shows monitoring vegetation changes for 2000, 2010 and 2020. The NDVI time series Chikangawa forest maps computed in the study, range from -0.16 to 0.96 in 2000, from -0.18 to 0.75 in 2010 and -0.81 to 1 in 2020.

Population growth has led to more pressure being faced by our environment especially forest reserves area where they compose much more of our vegetation. The study had involved most of its work practically and had required involvement of remote sensing images were used for supervised classification and also GIS software such as ENVI, ArcMap and QGIS that had been used in analysis of the data collected. Landsat images were downloaded from United States Geological Survey (USGS) dataset website (https://earthexplorer.usgs.gov/) and these time intervals had helped to identify the changes that have happened within Chikangawa forest for the past years. The NDVI time series Chikangawa forest maps computed in the study, range from -0.16 to 0.96 in 2000, from -0.18 to 0.75 in 2010 and -0.81 to 1 in 2020.

The study was based in Chikangawa forest, Mzimba district which is in northern part of Malawi. South Viphya forest reserve, established in 1948, has an area of 1147.8km2 covering much of the southern range. The reserve home to the vast Viphya plantation, also known as the Chikangawa forest, which is mostly composed of exotic pine trees.

Traditional authority: Sckampingo Sibande

District: Mzimba

Coordinates: -11.6761, 33.75795