GIS-Based Valuation of Ecosystem Services

A special issue of Geographies (ISSN 2673-7086).

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 6949

Special Issue Editor


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Guest Editor
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Interests: ecosystem services; geographical information systems; remote sensing; spatial modelling; land use and land cover change; urban planning
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Special Issue Information

Dear Colleagues,

Ecosystem services (ES) are the benefits provided to humans by the natural environment, such as clean air, natural pollination, drought regulation, food from agriculture, climate regulation, etc. This concept gradually deepens its influence on the development of environmental economic theory and practice. Providing information about ES for decision making is essential to preserve their supply and, consequently, their benefits to society. Making these services visible through the mapping of biophysical, social, and economic indicators enables understanding of potential trade-offs and the design of conservation strategies. Geographical information systems (GIS) can be used to spatially estimate the direct use value of ES and to map results. However, ES modeling requires extensive data acquisition, processing, and modeling skills, making the task of selecting which method to use arduous. In this Special Issue we aim to advance the state of the art in exploring available open data and GIS models which can be used for ES modeling and mapping. This Special Issue also aims to promote the importance of the ecosystem services concept for sustainability and human wellbeing.

Dr. Pedro Cabral
Guest Editor

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Keywords

  • ecosystem services
  • remote sensing
  • natural capital
  • economic valuation
  • tradeoffs
  • conservation planning

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Published Papers (2 papers)

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Research

22 pages, 19870 KiB  
Article
Conflicts of Interest and Emissions from Land Conversions: State of New Jersey as a Case Study
by Elena A. Mikhailova, Lili Lin, Zhenbang Hao, Hamdi A. Zurqani, Christopher J. Post, Mark A. Schlautman, Gregory C. Post and George B. Shepherd
Geographies 2022, 2(4), 669-690; https://doi.org/10.3390/geographies2040041 - 8 Nov 2022
Cited by 1 | Viewed by 2692
Abstract
Conflicts of interest (COI) are an integral part of human society, including their influence on greenhouse gas (GHG) emissions and climate change. Individuals or entities often have multiple interests ranging from financial benefits to reducing climate change-related risks, where choosing one interest may [...] Read more.
Conflicts of interest (COI) are an integral part of human society, including their influence on greenhouse gas (GHG) emissions and climate change. Individuals or entities often have multiple interests ranging from financial benefits to reducing climate change-related risks, where choosing one interest may negatively impact other interests and societal welfare. These types of COI require specific management strategies. This study examines COI from land-use decisions as an intersection of different perspectives on land use (e.g., land conservation versus land development), which can have various consequences regarding GHG emissions. This study uses the state of New Jersey (NJ) in the United States of America (USA) as a case study to demonstrate COI related to soil-based GHG emissions from land conversions between 2001 and 2016 which caused $722.2M (where M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions. These emissions are currently not accounted for in NJ’s total carbon footprint (CF), which can negatively impact the state’s ability to reach its carbon reduction goals. The state of NJ Statutes Annotated 26:2C-37 (2007): Global Warming Response Act (GWRA) (updated in 2019) set a statewide goal of reducing GHG emissions to 80 percent below 2006 levels by 2050. Remote sensing and soil data analysis allow temporal and quantitative assessment of the contribution of land cover conversions to NJ’s CF by soil carbon type, soil type, land cover type, and administrative units (state, counties), which helps document past, and estimate future related GHG emissions using a land cover change scenario to calculate the amount of GHG emissions if an area of land was to be developed. Decisions related to future land conversions involve potential COI within and outside state administrative structures, which could be managed by a conflict-of-interest policy. The site and time-specific disclosures of GHG emissions from land conversions can help governments manage these COI to mitigate climate change impacts and costs by assigning financial responsibility for specific CF contributions. Projected sea-level rise will impact 16 out of 21 NJ’s counties and it will likely reach coastal areas with densely populated urban areas throughout NJ. Low proportion of available public land limits opportunities for relocation. Increased climate-change-related damages in NJ and elsewhere will increase the number of climate litigation cases to alleviate costs associated with climate change. This litigation will further highlight the importance and intensity of different COI. Full article
(This article belongs to the Special Issue GIS-Based Valuation of Ecosystem Services)
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17 pages, 15534 KiB  
Article
Contribution of Land Cover Conversions to Connecticut (USA) Carbon Footprint
by Elena A. Mikhailova, Lili Lin, Zhenbang Hao, Hamdi A. Zurqani, Christopher J. Post, Mark A. Schlautman and Gregory C. Post
Geographies 2022, 2(2), 286-302; https://doi.org/10.3390/geographies2020020 - 31 May 2022
Cited by 1 | Viewed by 3482
Abstract
Greenhouse gas (GHG) emissions from landcover conversions contribute to the total carbon (C) footprint (CF), which is the sum of GHG emissions from various sources and events expressed as carbon dioxide (CO2) equivalent. Soil-based emissions from land conversions are often excluded [...] Read more.
Greenhouse gas (GHG) emissions from landcover conversions contribute to the total carbon (C) footprint (CF), which is the sum of GHG emissions from various sources and events expressed as carbon dioxide (CO2) equivalent. Soil-based emissions from land conversions are often excluded from the total CF, which can lead to underreporting the CF. This study uses the state of Connecticut (CT) as a case study to demonstrate the importance of soil-based emissions from land cover conversions to the state’s CF. The state of CT Public Act 08-98 (2008): Global Warming Solutions Act (GWSA) set a statutory requirement to cut GHG emissions 10 percent below 1990 levels by 2020 and 80 percent below 2001 levels by 2050 without considering soil-based emissions from land conversions. This omission results in underestimates of past and current emissions related to CT’s CF. In addition, not accounting for soil-based emissions from land conversions may increase the future size of CT’s CF. Remote sensing and soil data analysis provide an opportunity for rapid, quantitative, and temporal assessment of the contribution of land cover conversions to CT’s CF by soil type, land cover type, and administrative units (counties). Results are reported for soil organic carbon (SOC), soil inorganic carbon (SIC), and total soil carbon (TSC) based on C contents and monetary values of social costs of carbon. The state of CT experienced soil-based emissions from land cover conversions from 2001 to 2016 with $388.1M (where $ = USD, M = million = 106) worth of “realized” social costs of carbon dioxide (SC-CO2) emissions which should be accounted for in CT’s total CF. The current methodology could be used to optimize future land conversions to minimize the amount of soil GHG emissions by considering the soil C resources in different development scenarios. With an extensive, densely populated coastal area, CT will be directly affected by rising sea levels and other climate change impacts. Future research can focus on owner-specific CF contributions to address the responsibility for costs of GHG emissions as well as limiting the CF impact of land conversions. Full article
(This article belongs to the Special Issue GIS-Based Valuation of Ecosystem Services)
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