Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI). Issue 1 (31st December 2022)
- Record Type:
- Journal Article
- Title:
- Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI). Issue 1 (31st December 2022)
- Main Title:
- Ecological quality assessment and monitoring using a time-series remote sensing-based ecological index (ts-RSEI)
- Authors:
- Sun, Chao
Li, Jialin
Liu, Yongchao
Cao, Luodan
Zheng, Jiahao
Yang, Zhenjie
Ye, Junwei
Li, Yue - Abstract:
- ABSTRACT: Ecological quality assessment is fundamental to revealing changes in ecological environments before the development of effective ecological conservation policies. The complex ecological environment can be assessed more reliably when multiple remote sensing indices are integrated, such as in the use of the prevalent Remote Sensing-based Ecological Index (RSEI). However, for effective ecological quality assessment, the requirement of acquisition time consistency for images has become an outstanding issue for broadening the application of the RSEI. In this study, we adjusted the RSEI to the Continuous Change Detection and Classification (CCDC) algorithm that predicts synthetic images instead of real images. Based on this algorithm, we mapped time-series RSEI (ts-RSEI), which provide comparable results for tracing the dynamics of ecological quality at any time. Our major findings are as follows: (1) The RSEI is very sensitive to the timespan of the image acquisition dates, with the Mean Absolute Difference (MAD) of 0.111 (19.2%) when the interval between dates exceeds one month. (2) The ts-RSEI from synthetic images is comparable to the RSEI from real images, with the MAD of 0.075 (10.5%), which is superior to that of two real images with the timespan of half-a-month. (3) For Hangzhou, the ecological quality was maintained for almost the past 35 years (the ts-RSEI changed from 0.679 to 0.705). However, special attention should be paid to the spatial polarizationABSTRACT: Ecological quality assessment is fundamental to revealing changes in ecological environments before the development of effective ecological conservation policies. The complex ecological environment can be assessed more reliably when multiple remote sensing indices are integrated, such as in the use of the prevalent Remote Sensing-based Ecological Index (RSEI). However, for effective ecological quality assessment, the requirement of acquisition time consistency for images has become an outstanding issue for broadening the application of the RSEI. In this study, we adjusted the RSEI to the Continuous Change Detection and Classification (CCDC) algorithm that predicts synthetic images instead of real images. Based on this algorithm, we mapped time-series RSEI (ts-RSEI), which provide comparable results for tracing the dynamics of ecological quality at any time. Our major findings are as follows: (1) The RSEI is very sensitive to the timespan of the image acquisition dates, with the Mean Absolute Difference (MAD) of 0.111 (19.2%) when the interval between dates exceeds one month. (2) The ts-RSEI from synthetic images is comparable to the RSEI from real images, with the MAD of 0.075 (10.5%), which is superior to that of two real images with the timespan of half-a-month. (3) For Hangzhou, the ecological quality was maintained for almost the past 35 years (the ts-RSEI changed from 0.679 to 0.705). However, special attention should be paid to the spatial polarization between natural ("better") and human-dominated ("worse") environments. The high temporal consistency and the capability of any- time mapping of the ts-RSEI are expected to be of value to policy makers and authorities in implementing effective ecological conservation measures. … (more)
- Is Part Of:
- GIScience & remote sensing. Volume 59:Issue 1(2022)
- Journal:
- GIScience & remote sensing
- Issue:
- Volume 59:Issue 1(2022)
- Issue Display:
- Volume 59, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 59
- Issue:
- 1
- Issue Sort Value:
- 2022-0059-0001-0000
- Page Start:
- 1793
- Page End:
- 1816
- Publication Date:
- 2022-12-31
- Subjects:
- Remote sensing -- ecological quality assessment -- Time-series -- RSEI -- CCDC -- Hangzhou
Geodesy -- Periodicals
Cartography -- Periodicals
Aerial photogrammetry -- Periodicals
Remote sensing -- Periodicals
526.05 - Journal URLs:
- http://bellwether.metapress.com/content/120751/ ↗
http://www.ingentaselect.com/vl=7363692/cl=16/nw=1/rpsv/cw/bell/15481603/contp1.htm ↗
http://www.tandfonline.com/toc/tgrs20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/15481603.2022.2138010 ↗
- Languages:
- English
- ISSNs:
- 1548-1603
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4179.386000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24151.xml