Quantifying landscape‐level land‐use intensity patterns through radar‐based remote sensing. Issue 3 (16th January 2018)
- Record Type:
- Journal Article
- Title:
- Quantifying landscape‐level land‐use intensity patterns through radar‐based remote sensing. Issue 3 (16th January 2018)
- Main Title:
- Quantifying landscape‐level land‐use intensity patterns through radar‐based remote sensing
- Authors:
- Howison, Ruth A.
Piersma, Theunis
Kentie, Rosemarie
Hooijmeijer, Jos C. E. W.
Olff, Han - Editors:
- Pärt, Tomas
- Abstract:
- Abstract: The increasing availability of high resolution and high frequency, radar‐based remote sensing data (i.e. observations on land surface characteristics, insensitive to cloud interference), makes it possible to track land‐use intensity more precisely at the whole landscape scale. Here, we develop a new radar‐based remote sensing technique for large‐scale quantification of agricultural land‐use intensity across human‐dominated landscapes. We compare the respective abilities of Sentinel‐1 C‐band radar (C‐SAR, C‐band synthetic aperture radar) remote sensing data with the more traditional optical data, as MODIS enhanced vegetation indices (MODIS EVI), in capturing seasonality and the magnitude of land‐use intensity (quantity and frequency of biomass removal). Linking our novel radar‐based change detection algorithm to agricultural management activities on the ground, we quantify a whole landscape according to timing of mowing, a key grassland disturbance, thus capturing the dynamics of mowing regimes in grasslands. We found that the radar‐based proxy provides a rapid and reliable measure of land‐use intensity, reliably predicting plant community composition at the landscape scale. We tested this methodology using data on black‐tailed godwits ( Limosa limosa limosa ), a specialist breeder of lowland meadows which, over the last 50 years, has shown dramatic declines. During territory establishment, black‐tailed godwits preferentially used fields corresponding toAbstract: The increasing availability of high resolution and high frequency, radar‐based remote sensing data (i.e. observations on land surface characteristics, insensitive to cloud interference), makes it possible to track land‐use intensity more precisely at the whole landscape scale. Here, we develop a new radar‐based remote sensing technique for large‐scale quantification of agricultural land‐use intensity across human‐dominated landscapes. We compare the respective abilities of Sentinel‐1 C‐band radar (C‐SAR, C‐band synthetic aperture radar) remote sensing data with the more traditional optical data, as MODIS enhanced vegetation indices (MODIS EVI), in capturing seasonality and the magnitude of land‐use intensity (quantity and frequency of biomass removal). Linking our novel radar‐based change detection algorithm to agricultural management activities on the ground, we quantify a whole landscape according to timing of mowing, a key grassland disturbance, thus capturing the dynamics of mowing regimes in grasslands. We found that the radar‐based proxy provides a rapid and reliable measure of land‐use intensity, reliably predicting plant community composition at the landscape scale. We tested this methodology using data on black‐tailed godwits ( Limosa limosa limosa ), a specialist breeder of lowland meadows which, over the last 50 years, has shown dramatic declines. During territory establishment, black‐tailed godwits preferentially used fields corresponding to intermediate radar‐sensed land‐use intensities. However, the present‐day timing of mowing in these habitats was such that most godwit broods were less likely to be successful than broods in grasslands used at a lower intensity. Synthesis and applications . The newly developed radar‐based land‐use intensity quantification is a powerful tool that makes it possible for ecologists and land managers to include agricultural land‐use intensity measurements in population studies of the plants, insects, birds and mammals using these landscapes, at the spatial scale of entire populations. Applications of this tool include evaluating the effectiveness of European agri‐environment schemes aiming to increase biodiversity through decreased land‐use intensity or expanding the quantification of agricultural land‐use intensity to other geographic regions. Abstract : The newly developed radar‐based land‐use intensity quantification is a powerful tool that makes it possible for ecologists and land managers to include agricultural land‐use intensity measurements in population studies of the plants, insects, birds and mammals using these landscapes, at the spatial scale of entire populations. Applications of this tool include evaluating the effectiveness of European agri‐environment schemes aiming to increase biodiversity through decreased land‐use intensity or expanding the quantification of agricultural land‐use intensity to other geographic regions. … (more)
- Is Part Of:
- Journal of applied ecology. Volume 55:Issue 3(2018)
- Journal:
- Journal of applied ecology
- Issue:
- Volume 55:Issue 3(2018)
- Issue Display:
- Volume 55, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 55
- Issue:
- 3
- Issue Sort Value:
- 2018-0055-0003-0000
- Page Start:
- 1276
- Page End:
- 1287
- Publication Date:
- 2018-01-16
- Subjects:
- black‐tailed godwit -- change detection -- habitat preference -- land‐use intensity -- MODIS EVI -- mowing frequency -- radar -- remote sensing -- Sentinel C‐SAR -- temporal stability
Agriculture -- Periodicals
Biology, Economic -- Periodicals
Agricultural ecology -- Periodicals
Applied ecology -- Periodicals
577 - Journal URLs:
- http://besjournals.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)1365-2664/ ↗
http://onlinelibrary.wiley.com/ ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=jpe ↗ - DOI:
- 10.1111/1365-2664.13077 ↗
- Languages:
- English
- ISSNs:
- 0021-8901
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4942.500000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6363.xml