Mapping Land Cover Change over a 25-Year Period (1993–2018) in Sri Lanka Using Landsat Time-Series

Abstract

Land use and land cover change (LULCC) are dynamic over time and space due to human and biophysical factors. Accurate and up-to-date LULCC information is a mandatory part of environmental change analysis and natural resource management. In Sri Lanka, there is a significant temporal gap in the existing LULCC information due to the civil war that took place from 1983 to 2009. In order to fill this gap, this study presents a whole-country LULCC map for Sri Lanka over a 25-year period using Landsat time-series imagery from 1993 to 2018. The LandTrendr change detection algorithm, utilising the normalised burn ratio (NBR) and normalised difference vegetation index (NDVI), was used to develop spectral trajectories over this time period. A land cover change and disturbance map was created with random forest, using 2117 manually interpreted reference pixels, of which 75% were used for training and 25% for validation. The model achieved an overall accuracy of 94.14%. The study found that 890,003.52 hectares (ha) (13.5%) of the land has changed, while 72,266.31 ha (1%) was disturbed (but not permanently changed) over the last 25 years. LULCC was found to concentrate on two distinct periods (2000 to 2004 and 2010 to 2018) when social and economic stability allowed greater land clearing and investment opportunities. In addition, LULCC was found to impact forest reserves and protected areas. This new set of Sri Lanka-wide land cover information describing change and disturbance may provide a reference point for policy makers and other stakeholders to aid in decision making and for planning purposes.

Tracking Rates of Forest Disturbance and Associated Carbon Loss in Areas of Illegal Amber Mining in Ukraine Using Landsat Time Series

“…For example, Bright et al [37] analyzed post-fire vegetation recovery using LandTrendr-fitted spectral trajectories of NBR as an indicator variable for its conditions. The NBR and NDVI were found to be the most suitable for interannual vegetation changes in LTS analysis [42]. Similarly, Hislop et al [43] demonstrated that both indices accurately capture wildfire disturbance in pixel-based approaches; however, it was shown that NDVI is not so reliable in southeast Australia for detecting post-fire recovery of sclerophyll forests.…”

Seasonal land use land cover change and the drivers in Kafta-Sheraro National Park, Tigray, Ethiopia

“…This report is inconsistent with what happened in the Syria conflict (2011 to 2018) significantly changes the LULC from 2010 to 2018 and the conflict influenced local environmental resources [144]. Similarly, the civil war of Sri Lanka (1983 to 2009) and the post-war assessment of LULC change between 1993 and 2018 influenced forest reserves and protected areas of the country [145]. During the war period of Sierra Leones (civil war 1991-2002) caused LULC change of Kono district, forest cover structure and spatial extent was contracted [146].…”

An Overview of Ecosystem Service Studies in a Tropical Biodiversity Hotspot, Sri Lanka: Key Perspectives for Future Research

“…At present, though some reports state Sri Lanka has 16.5% forest cover [31], no published data support this claim. Recent years have recorded the worst forest cover clearing due to infrastructure development activities in Sri Lanka [32], in addition to illegal logging activities recorded throughout the country, though the country has suspended any form of commercial timber extraction [33]. Considering the intensity of resource and environmental degradation and exploitation occurring in the country, it is essential to assess the ecosystem services for better planning of resource utilization and sustainable development.…”