Abstract
Accelerated land use change is a current challenge for environmental management worldwide. 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 imageries. Using Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Imager (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 authorities and environmental practitioners should balance the economic benefits and ecological gains in different landscapes to achieve a sustainable development from local to regional scales.
Highlights
Landscape metrics refers to a simple quantitative index that can provide very denser landscape pattern evidence at the patch level, landscapelevel and class-area level, which is suitable for quantitative expression of the relationship between landscape pattern and ecological process [25]
Our findings showed that the overall spatial patterns of land use/land cover (LULC) were improved during the study period, especially from 2014 to 2019, with the conversion of farmland and unused land into woodland and grassland accounting for most of this improvement
The total ecosystem service values (ESV) in the study area was higher compared to the national average, despite the expansion of the built-up area, which was probably related to the existing of government policies that stimulating the enhancement of ecosystem services (ES) by providing a financial incentive
Summary
Anthropic pressure on human-induced landscapes is the main driver of land use/land cover (LULC) changes and its effects on ecosystem services (ES) [1,2] which is key to Remote Sens. The use of ES has been proposed to define important contributions of ecosystems to human well-being, representing a link between biodiversity conservation and development needs [3]. Land use changes can lead to strong or slight alterations in ecosystem components, structures, ecological processes and biodiversity patterns [3,7]. Studying the changes of landscape patterns on ES can effectively grasp the changing trend of regional ecological environment, rationally allocating land use activities to promote harmonious and sustainable development goals for human and nature [9,10]
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