Rapideye (2008 -> ) Not just another high resolution satellite sensor. 5 satellites RapidEye constellation. 5 million km² daily collection capacity

Transcription

1 Rapideye (2008 -> ) Not just another high resolution satellite sensor 5 satellites RapidEye constellation 5 million km² daily collection capacity Price: $1.40 / sq km ($2.50 rectified) Orbit:

2 5 identical satellites: Tachys (rapid) Mati (eye) Choma (earth) Choros (space) Trochia (orbit)

3 First commercial satellites to image the Red-edge band (measures variances in vegetation) Products - Two types: Level 1A radiometric and sensor correction Level 3A radiometric, sensor, geometric correction Price: $1.40 / sq km ($2.50 rectified) Launch:

4 RapidEye 1-5 (Germany) Resolution: 5 m Collected at 6.5m 12-bit data Bands: Blue ( nm) Green ( nm) Red ( nm) Red Edge ( nm) Near IR ( nm) Altitude: 630 km Push Broom Revisit time: Off-nadir 1 day Nadir 5.5 days Swath width of 77 km Launched August 29, 2008 Images at 11:00am local

5 5 spectral bands multispectral imagery includes the Red Edge (RE)

6 Designed/launched 2008 by Rapideye AG Munich/Berlin,Germany Implemented by MacDonald Dettwiler (MDA) Richmond, BC Satellites built by Surrey Satellite Technology Ltd (UK) World leader in building small satellites (ex-u. Surrey) 1 cubic metre (150kg) Data downloaded to receiving stations, Svalbard, Norway Rapideye acquired 2011 by Iunctus -> Blackbridge, Lethbridge, AB (LA) Planet Labs, CA acquires Blackbridge and RapidEye

7 Sept : Iunctus Geomatics Corp. of Lethbridge, Alberta, Canada s exclusive distributor of French Spot optical satellite data, purchased Germany-based RapidEye for ~13 million euros ($19m) includes 5 satellites Ryan Johnson, President

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9 The red portion is where chlorophyll strongly absorbs light and the NIR is where the leaf cell structure produces a strong reflection (green line in Fig. 1). Variations in both the chlorophyll content and the leaf structure are often reflected in the Red Edge band. Studies have suggested that this band is able to provide additional information to identify plant types, nutrition and health status, and characterize plant cover and abundance, among other features.

10 Agriculture and Vegetation : red edge provides extra contrast

11 Red and NIR alone show a slim difference between grassland and crops

12 Increased separation of vegetation types, e.g. grassland versus crops

13 Ju, C-H., Y-C. Tian, X. Yao, W-X. Cao, Y. Zhu, and D. Hannaway Estimating leaf chlorophyll content using red edge parameters. Pedosphere 20(5): Jiang, J-B., Y-H. Chen, and W-J. Huang Using the distance between hyperspectral red edge position and yellow edge position to identify wheat yellow rust disease. Spectroscopy and Spectral Analysis 30(6): Darvishzadeh, R., C.A. Atzberger, A.K. Skidmore, and A.A. Abkar Leaf area index derivation from hyperspectral vegetation indices and the red edge position. International Journal of Remote Sensing 30(23): Marx, A Detection and classification of bark beetle infestation in pure norway spruce stands with multi-temporal RapidEye imagery and data mining techniques. Photogrammetrie Fernerkundung Geoinformation 4: Eitel, J.U.H., D.S. Long, P.E. Gessler, and A.M.S. Smith Using in-situ measurements to evaluate the new RapidEye satellite series for prediction of wheat nitrogen status. International Journal of Remote Sensing 28(18):

14 Search: Valemount / Robson 53, -120

15 Rapideye Mt. Revelstoke Nat. Park

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19 Rapideye data at UNBC ( ) Prince George (unrectified) GEOG457 lab Mt. Revelstoke National Park Mt. Robson Provincial Park (Berg Lake) Andrei Icefield, Coast Mountains Lyngen, Norway (70 degrees north)

20 Rapideye Data possibilities Potential to fuse Landsat 8 with Rapideye Multispectral OLI - including Mid-IR Higher-res. Rapideye - including Red Edge / NIR Use of Principal Components Analysis to merge multiple datasets

21 The constellation is adding ~ 1 billion km 2 /year of imagery into their archives. This corresponds to about seven times the Earth's land surface/year. Subsequently, potential AOIs (Areas of Interest) are not only covered once, but with a high temporal resolution. Figure summarizes the imaging frequency of archived data.

22 Sept. 30, 2013: RapidEye announced that its North American agricultural imaging campaign has been completed successfully. The ran monthly from May 15, 2013 through September 14, 2013, generating more than 16 million km 2 of cloud-free imagery over 3 million km 2 spanning twenty-eight US states and 3 Canadian provinces. Time series, South Dakota

23 RapidEye image of Alaska, USA, collected in September 11, 2012

24 Nilandhe Atoll, Maldives

25 Channel Islands, UK

26 Sarek Nationalpark, Sweden

27 Las Vegas

28 Auckland

29 RapidEye image of Alaska, USA, collected in September 11, 2012 Rio de Janeiro

30 Price: $1.40 / sq km

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32 Rapideye National mosaic

33 Nov. 20, 2013: BlackBridge AG has provided ESA ( European Space Agency) with a substantial time series of RapidEye imagery to support the Sentinel-2 preparatory project. The aim was to collect imagery at the same time frequency Sentinel-2 will, as well as support the R&D activities relevant to the Sentinel-2 mission (e.g. agriculture, wetlands, coastal, food security and forest monitoring). RapidEye imagery was selected by ESA because of its spatial resolution and revisit capabilities. Sentinel-2 is freely downloadable - from ESA and earthexplorer

34 Sensors with red edge band(s) Rapideye 2008 Worldview Worldview Sentinel-2 (4) 2015

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36 Sentinel-2 Multi-Spectral Instrument (MSI) 13 bands

37 Sentinel-2 is the first optical Earth observation mission of its kind to include three bands in the red edge', which provide key information on the state of vegetation 6 July 2015 acquired near Toulouse, France, the satellite's multispectral instrument was able to discriminate between two types of crops: sunflower (in orange) and maize (in yellow),

38 Porirua, New Zealand Sentinel-2 downloaded from EarthExplorer