Dynamics of Tree outside Forest Land Cover Development and Ecosystem Carbon Storage Change in Eastern Coastal Zone, Bangladesh

Imranul Islam, Shenghui Cui, Muhammad Ziaul Hoque, Hasan Muhammad Abdullah, Kaniz Fatima Tonny, Minhaz Ahmed, Jannatul Ferdush, Lilai Xu and Shengping Ding
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Imranul Islam: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Shenghui Cui: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Muhammad Ziaul Hoque: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Hasan Muhammad Abdullah: Department of Agroforestry and Environment, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh
Kaniz Fatima Tonny: Coastal and Ocean Management Institute, Xiamen University, Xiamen 361005, China
Minhaz Ahmed: Department of Agroforestry and Environment, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh
Jannatul Ferdush: Department of Geosciences, Mississippi State University, Starkville, MS 39762, USA
Lilai Xu: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Shengping Ding: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China

Land, 2022, vol. 11, issue 1, 1-19

Abstract: Tree outside forest (TOF) has immense potential in economic and environmental development by increasing the amount of tree vegetation in and around rural settlements. It is an important source of carbon stocks and a critical option for climate change regulation, especially in land-scarce, densely populated developing countries such as Bangladesh. Spatio-temporal changes of TOF in the eastern coastal zone of Bangladesh were analyzed and mapped over 1988–2018, using Landsat land use land cover (LULC) maps and associated ecosystem carbon storage change by linking the InVEST carbon model. Landsat TM and OLI-TIRS data were classified through the Maximum Likelihood Classifier (MLC) algorithm using Semi-Automated Classification (SAC). In the InVEST model, aboveground, belowground, dead organic matter, and soil carbon densities of different LULC types were used. The findings revealed that the studied landscapes have differential features and changing trends in LULC where TOF, mangrove forest, built-up land, and salt-aquaculture land have increased due to the loss of agricultural land, mudflats, water bodies, and hill vegetation. Among different land biomes, TOF experienced the largest increase (1453.9 km 2 ), and it also increased carbon storage by 9.01 Tg C. However, agricultural land and hill vegetation decreased rapidly by 1285.8 km 2 and 365.7 km 2 and reduced carbon storage by 3.09 Tg C and 4.89 Tg C, respectively. The total regional carbon storage increased by 1.27 Tg C during 1988–2018. In addition to anthropogenic drivers, land erosion and accretion were observed to significantly alter LULC and regional carbon storage, necessitating effective river channel and coastal embankment management to minimize food and environmental security tradeoff in the studied landscape.

Keywords: land use change; satellite image analysis; ecosystem services; InVEST model; carbon storage; Bangladesh (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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