Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Spatiotemporal Analysis of Land Cover and the Effects on Ecosystem Service Values in Rupandehi, Nepal from 2005 to 2020

Bibliographic Data

ID22033850
AuthorsAman KC (Tribhuvan University), Nimisha Wagle (0000-0002-5921-0382, Government of Nepal), Tri Dev Acharya (0000-0003-0886-4201, University of California, Davis, corresponding author)
Year2021
Volume10
Issue10
Pages635
Publication date2021-09-23
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi10100635
OpenAlexW3199031908
LanguageEN
Citations received1
References cited55

Land cover (LC) is a crucial parameter for studying environmental phenomena. Cutting-edge technology such as remote sensing (RS) and cloud computing have made LC change mapping efficient. In this study, the LC of Rupandehi District of Nepal were mapped using Landsat imagery and Random Forest (RF) classifier from 2005 to 2020 using Google Earth Engine (GEE) platform. GEE eases the way in extracting, analyzing, and performing different operations for the earth’s observed data. Land cover classification, Centre of gravity (CoG), and their trajectories for all LC classes: agriculture, built-up, water, forest, and barren area were extracted with five-year intervals, along with their Ecosystem service values (ESV) to understand the load on the ecosystem. We also discussed the aspects and problems of the spatiotemporal analysis of developing regions. It was observed that the built-up areas had been increasing over the years and more centered in between the two major cities. Other agriculture, water, and forest classes had been subjected to fluctuations with barren land in the decreasing trend. This alteration in the area of the LC classes also resulted in varying ESVs for individual land cover and total values for the years. The accuracy for the RF classifier was under substantial agreement for such fragmented LCs. Using LC, CoG, and ESV, the paper discusses the need for spatiotemporal analysis studies in Nepal to overcome the current limitations and later expansion to other regions. Studies such as these help in implementing proper plans and strategies by district administration offices and local governmental bodies to stop the exploitation of resources

Agriculture · Ecosystem · Ecosystem services · Environmental resource management · Geography · Land cover · Land use · Machine learning · Physical geography · Random forest · Remote sensing · Computer Science · Environmental Science · Land Use and Ecosystem Services · Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture · Ecology · Geology

  • Dynamic Variation of Ecosystem Services Value under Land Use/Cover Change in the Black Soil Region of Northeastern China

    Open Access•Quanfeng Li, Lu Wang et al.•International Journal of…•2022

  • Stable classification with limited sample

    Open Access•Peng Gong, Han Liu et al.•Science Bulletin•2019

  • Development of a global land cover characteristics database and IGBP Discover from 1 km AVHRR data

    Thomas R Loveland, Bradley C Reed et al.•International Journal of Remote…•2000

  • Finer resolution observation and monitoring of global land cover

    Peng Gong, Jie Wang et al.•International Journal of Remote…•2013

  • High-resolution mapping of global surface water and its long-term changes

    Open Access•J-F Pekel, Andrew Cottam et al.•Nature•2016

  • Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery

    Hanqiu Xu•International Journal of Remote…•2006

  • Random Forests for land cover classification

    Open Access•Pall Oskar Gislason, Jon Atli Benediktsson et al.•Pattern Recognition Letters•2006

  • Global land cover classification at 1 km spatial resolution using a classification tree approach

    Matthew C Hansen, Ruth Defries et al.•International Journal of Remote…•2000

  • Challenges in using land use and land cover data for global change studies

    Open Access•Peter H Verburg, Kathleen Neumann et al.•Global Change Biology•2011

  • Modis Collection 5 global land cover

    Open Access•M A Friedl, Damien Sulla‐Menashe et al.•Remote Sensing of Environment•2010

  • High-Resolution Global Maps of 21st-Century Forest Cover Change

    Open Access•Matthew C Hansen, Peter Potapov et al.•Science•2013

  • Random Forests

    Open Access•Leo Breiman•Machine Learning•2001

  • The value of the world's ecosystem services and natural capital

    Open Access•R Costanza, Ralph C D’arge et al.•Nature•1997

  • Change in ecosystem service values in the San Antonio area, Texas

    Open Access•Urs P Kreuter, Heather Grace Harris et al.•Ecological Economics•2001

  • Relationship between urban construction land expansion and population/economic growth in Liaoning Province, China

    Open Access•Zeyang Li, Weixin Luan et al.•Land Use Policy•2020

Citations per year0.25
Citation span2022 - 2022 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae