TY - JOUR

T1 - Using open-source software GRASS GIS for analysis of the environmental patterns in Lake Chad, Central Africa

AU - Леменкова, Полина Алексеевна

PY - 2023/11/15

Y1 - 2023/11/15

N2 - Lake Chad, situated in the semi-arid region of African Sahel, plays a vital role in hydrogeological balance of regional ecosystems. It presents an essential water source and provides a habitat for rare wildlife species including migrating waterbirds. However, the lake has shrunk significantly and has continued to reduce in size and extent during recent decades. Trends in drying and shrinking of Lake Chad are caused by environmental factors and changed climate. The desiccation of the lake is threatening environmental sustainability. This study focused on identification of changes in the Chad Lake area, wetland extent, and associated land cover types. The methods include the GRASS GIS for remote sensing data classification. The maximum likelihood discriminant analysis classifier was applied for analysis of multispectral Landsat images. Detected changes in land cover types reflect variations in water balance and wetland area and extent around Lake Chad over recent decades. Cartographic scripting tools of GRASS GIS provide an efficient method of digital image processing for monitoring endorheic lakes of Central Africa. GRASS GIS methods provide an opportunity to automatically classify Earth observation data with cartographic scripts for environmental monitoring.

AB - Lake Chad, situated in the semi-arid region of African Sahel, plays a vital role in hydrogeological balance of regional ecosystems. It presents an essential water source and provides a habitat for rare wildlife species including migrating waterbirds. However, the lake has shrunk significantly and has continued to reduce in size and extent during recent decades. Trends in drying and shrinking of Lake Chad are caused by environmental factors and changed climate. The desiccation of the lake is threatening environmental sustainability. This study focused on identification of changes in the Chad Lake area, wetland extent, and associated land cover types. The methods include the GRASS GIS for remote sensing data classification. The maximum likelihood discriminant analysis classifier was applied for analysis of multispectral Landsat images. Detected changes in land cover types reflect variations in water balance and wetland area and extent around Lake Chad over recent decades. Cartographic scripting tools of GRASS GIS provide an efficient method of digital image processing for monitoring endorheic lakes of Central Africa. GRASS GIS methods provide an opportunity to automatically classify Earth observation data with cartographic scripts for environmental monitoring.

U2 - 10.2478/boku-2023-0005

DO - 10.2478/boku-2023-0005

M3 - Article

VL - 74

SP - 49

EP - 64

JO - Bodenkultur

JF - Bodenkultur

SN - 0006-5471

IS - 1

ER -