Using satellite image fusion to evaluate the impact of land use changes on ecosystem services and their economic values

Wang Shuangao, Rajchandar Padmanaban, Aires A. Mbanze, João M.N. Silva, Mohamed Shamsudeen, Pedro Cabral, Felipe S. Campos

Research output: Contribution to journalArticlepeer-review

Abstract

Accelerated land use change is a current challenge for environmental management world-wide. Given the urgent need to incorporate economic and ecological goals in landscape planning, cost-effective conservation strategies are required. In this study, we validated the benefit of fusing imagery from multiple sensors to assess the impact of landscape changes on ecosystem services (ES) and their economic values in the Long County, Shaanxi Province, China. We applied several landscape metrics to assess the local spatial configuration over 15 years (2004–2019) from fused image-ries. Using Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Im-ager (OLI) and Indian Remote Sensing Satellite System Linear Imaging Self Scanning Sensor 3 (IRS LISS 3) imageries fused for 2004, 2009, 2014 and 2019, we reclassified land use/land cover (LULC) changes, through the rotation forest (RF) machine-learning algorithm. We proposed an equivalent monetary metric for estimating the ES values, which also could be used in the whole China. Results showed that agriculture farmland and unused land decreased their spatial distribution over time, with an observed increase on woodland, grassland, water bodies and built-up area. Our findings suggested that the patterns of landscape uniformity and connectivity improved, while the distribution of landscape types stabilized, while the landscape diversity had a slight improvement. The overall ES values increased (4.34%) under a benefit transfer approach, mainly concerning woodland and grassland. A sensitivity analysis showed the selected economic value (EV) was relevant and suitable for the study area associated with our ES for LULC changes. We suggested that changes in landscape patterns affected the ESV trends, while the increases on some LULC classes slightly improved the landscape diversity. Using an interdisciplinary approach, we recommend that local au-thorities and environmental practitioners should balance the economic benefits and ecological gains in different landscapes to achieve a sustainable development from local to regional scales.

Original languageEnglish
Article number851
Pages (from-to)1-21
Number of pages21
JournalRemote Sensing
Volume13
Issue number5
DOIs
Publication statusPublished - 1 Mar 2021

Keywords

  • Environmental monitoring
  • Image fusion
  • Landscape patterns
  • Remote sens-ing
  • Urban ecosystem services

UN Sustainable Development Goals (SDGs)

  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action

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