Pasture Genetics_ Better Established Pastures and Forage Crops
Connection to the Larger Landscape?Pasture assessment " Pastures from Space/ Pasture Watch " light...
Transcript of Connection to the Larger Landscape?Pasture assessment " Pastures from Space/ Pasture Watch " light...
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Remote Sensing Tools in Grasslands: Connection to the Larger Landscape?
Anne Smith Agriculture and Agri-Food Canada
Lethbridge Research and Development Centre Transboundary Grasslands Partnership Workshop
December 4th, 2018 Lethbridge, Alberta
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Landsat 5 TM True Colour Composite July 6, 1991
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Landsat 5 TM True Colour Composite July 6, 1991
Year Cost Processing time
1991 $4500 1 week++ 2018 $0 1 hour
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LANDSAT 8
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Remote Sensing MODIS
PLANET LABS FLOCKS/DOVES
RADARSAT CONSETLLATION MISSION
RAPIDEYE
SENTINEL QUICKBIRD
SPOT
Update ~2000 EO ~684
2014
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Remote Sensing ! the acquisition of data about a physical object without touching it
Passive Active
e.g. MODIS , Landsat Sentinel-2, SPOT, RapidEye, Planet Labs Doves….. airborne and drone cameras
e.g. Radarsat-2, TerraSAR, Sentinel-1
airborne and drone sensors.
**RADARSAT Constellation
Mission February 2019
http://www.seos-project.eu leadertechnic.com 5
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Remote Sensing Tools for Grassland Monitoring
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Three broad categories of remote sensing research in grasslands: ! Mapping grassland
spatial extent and changes over time,
! Estimating productivity
! Mapping invasive plant species
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MAPPING SPATIAL EXTENT
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! Alberta Native Prairie Baseline (~1993) ! Alberta Grassland Vegetation Inventory (2006-2014)
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! Agriculture Financial Services Corporation grassland mask
Mapping Grassland Spatial Extent
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Image courtesy of Barry Adams, Alberta Environment and Sustainable Resource Development
" Colour infrared digital airborne imagery 0.5 m " Polygon-based, 5.0 ha for upland site types
and 1.0 ha for wetland site types. " 335,366 polygons in 1204 townships (110
townships remaining) " Accuracy estimated at >90% " > 8 years to compile (2006-2014)
" Comprehensive biophysical, anthropogenic and land use inventory
Mapping Grassland Spatial Extent
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Mapping Grassland Spatial Extent
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NEWELL TEST SITE RADARSAT-2 PAULI-RGB
July 21, 2009
PAKOWKI TEST SITE RADARSAT-2 PAULI-RGB
July 03, 2009
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Mapping Grassland Spatial Extent
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Ground data (collated from a variety of databases)
Remote sensing image (optical or radar)
Signatures
Classification
Land cover map
Training samples Validation samples
“Windshield surveys” Crop insurance Irrigation district Native Prairie Baseline
AGRASID Hydrology Township fabric
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Mapping Grassland Spatial Extent
! FQ4 fine quad-pol images (HH, VH, HV and VH)
! Multiple dates ! Yamaguchi decomposition ! July/August provide best
results (overall classification 81-82%; GVI polygons correctly identified 81-84% )
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Mapping Grassland Spatial Extent
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Mapping Grassland Spatial Extent
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Landsat TM image acquired in July 2011, R:band 4, G:band 3, B: band 2
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To investigate the potential to use satellite remote sensing products to update the grassland vegetation inventory: – Wholesale change (native
grassland to cropping) – Partial change (oil, gas,
transportation infrastructure)
Provide a tool for directing ground-based surveys
Mapping Grassland Spatial Extent
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5185 Upland-Grassland polygons covering 14 site types Method development database:
74 native grassland polygons 152 cropped polygons
Method validation data: 34 native grassland polygons in both 2006 and 2011 26 native grassland polygons converted to cropping systems between 2006 and 2011
Mapping Grassland Spatial Extent
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! Landsat imagery (6 bands BGR, NIR, 2MIR)
– functional vegetation indices (Greenness/photosynthesis; vegetation/landscape water content; senescent vegetation)
! Hybrid change detection – Update changed areas only – 2006, 2011, 2013
GVI polygons overlaid on July 6, 2006 Landsat TM5 False Colour Composite Image
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Mapping Grassland Spatial Extent
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Native grasslands converted to croplands Native grasslands
v
Edit polygon
Field validate
July August
Results- July and August change detection map
Mapping Grassland Spatial Extent
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July 2006-2013
19 Results-Change detection 2006-2011 and 2006-2013
July 2006-2011 Native grasslands converted to croplands Native grasslands
Mapping Grassland Spatial Extent
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Updated GVI
2007 SPOT Image 2006 GVI
Database Record Add/edit/delete
Slides courtesy of Barry Adams AESRD 20
Mapping Grassland Spatial Extent
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ESTIMATING ANNUAL PRODUCTIVITY OF GRASSLANDS
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! Point 1 ! Point 2
Introduction
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Estimating Annual Productivity of Grasslands ! Canada initial testing 1980s ! African, North American and Australian savannahs
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" Rangeview " MODIS – 250 m, daily coverage " Difference from average
State of Arizona, 2001 versus 2003, February 17 and May 8 23
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! Point 1 ! Point 2
Introduction
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Estimating Annual Productivity of Grasslands
Pasture assessment
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" Pastures from Space/ Pasture Watch " light use efficiency model " integrates MODIS satellite imagery, 250 m, 10 day composites and climate data
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Estimating Annual Productivity of Grasslands
! Empirical relationships – Landsat (multiple scenes) – 16 day repeat cycle – 30 m spatial resolution
! Simple modelling – Moderate Resolution Imaging Spectrometer – Daily coverage – 250 m spatial resolution
! Validation data?
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! Rangeland Reference Area Monitoring Program
– Alberta Environment and Sustainable Resource Development
– 5-20 years of clipping data – Spatially discrete
Estimating Annual Productivity of Grasslands
Caveat: • Measure potential
production • Scale
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Y= 4522.23X - 460.13, R² = 0.68
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Community Types R2 (2008) R2 (2009) R2 (2008+2009)
NDVI MTVI1 MTVI2 NDVI MTVI1 MTVI2 NDVI MTVI1 MTVI2 Foothills rough fescue (FRF) 0.54 0.68 0.65 0.86 0.95 0.95 0.67 0.76 0.73 Needle-and –thread (NT) 0.65 0.67 0.69 0.70 0.63 0.64 0.66 0.66 0.67 Northern wheatgrass (NW) 0.54 0.46 0.50 0.91 0.92 0.90 0.58 0.53 0.55
Cages
Estimating Annual Productivity of Grasslands
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LANDSAT DATA LANDSAT DATA
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fAPAR=(1.21*NDVI)-0.04 PAR=(0.5*average daily solar
radiation (MJ m-2 day-1))
APAR (MJ m-2 day-1) =fAPAR*PAR
APARu (MJ m-2 day-1) = APAR*MI*TI
GT (kg ha-1 day-1) = APARu*LUE*10 where GT is total (above ground and below ground) grass growth
10 is a factor to convert NPPT to kg ha-1.
MODIS IMAGERY TI=temperature stress index calculated from weather data and optimal values derived from literature (0-1) MI = moisture stress index derived from AGRASID soil information and Nix (1981) (0-1)
AGA (kg ha-1 day-1) = GT * root-shoot ratio where AGA is above ground grass growth
AAG(kg/ha annum) = sumjan-dec(AGA*10) where AAG is annual above ground grass growth
Estimating Annual Productivity of Grasslands
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APAR
Estimating Annual Productivity of Grasslands
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Temp. Index
Moist. Index
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Estimating Annual Productivity of Grasslands
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Estimating Annual Productivity of Grasslands
Considerations ! Multiples spatial resolutions ! Size of sampling units (MODIS pixel
versus clipping) ! Timing of field clipping ! Model integrated over time versus clipping
is from a single time period ! Carryover from different years (influences
NDVI itself, masks green vegetation)
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MAPPING NOXIOUS WEEDS
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Mapping Noxious Weeds in Grasslands
# Noxious weeds # Reduce productivity and biodiversity # Compete for water resources # Toxic to livestock # Economic impacts (loss of production and cost of control)
# Quantitative surveys of invasive species occurrence on the Prairie grasslands are rare due to the cost and accessibility
# Remote sensing shows promise
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! Extent of coverage • 5 million acres in 15 states and 6 Canadian
provinces • Manitoba alone 340,000 acres • river banks, pastures, and native grasslands
! Economic Impacts • $130 million annually in North Dakota, South
Dakota, Montana, and Wyoming • $19 million annually in Manitoba • control, loss of forage, loss of livestock
! Control • biological (insects and sheep) • herbicides
! Mapping ! by people spraying or releasing insects for
biocontrol ! remote sensing
Control by Aphthona sp.
Mapping Leafy Spurge in Grasslands
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! Remote sensing – Coverage of large and inaccessible
areas – Lower cost – Distinct yellow bracts – Unique spectral signature – Success in the USA
! No wide adopted
– Considerations ! Density, Patch size
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Mapping Leafy Spurge in Grasslands
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Mixed-Tuned Matched Filter ! Only requires end-member for target of choice ! Provides presence or absence
AISA imagery
Mapping Leafy Spurge in Grasslands
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Site 1c Site 1c Site 1c
AISA Simulated WorldView 2 Simulated Quickbird
! >30% ground cover of flowering leafy spurge can be detected
! <30% detection depends on proximity to higher density patches
! potential to use high spatial resolution satellites
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Ground cover of yellow flowers (%)Yes No
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Fixed-wing, larger areas, 30 mins. Multi-rotor, up and down, 12-15 mins.
Draganfly Commander
DJI Inspire 1 Precision Hawk
eBee
Mapping Leafy Spurge in Grasslands
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Mapping Leafy Spurge in Grasslands
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! 9 sampling areas ! Transects (3) ! Quadrats (19)
! Photograph (% total & flowering leafy spurge
! Visual density (L, M, H) ! Stem count
Mapping Leafy Spurge in Grasslands
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Site Collection date
Flight height (m)
Scenes Spatial resolution (cm)
Covering area(m2)
Site1 9 am, July 30, 2016
15 1 0.65 507 30 1 1.26 1905 45 1 1.88 4242 60 1 2.54 7742 75 1 3.15 11907 90 1 3.77 17055 105 1 4.41 23338 120 1 5.07 30846
Mapping Leafy Spurge in Grasslands
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Mapped leafy spurge cover versus ground measured leafy
spurge cover
Mapped leafy spurge cover versus ground measured
flowering leafy spurge cover
Mapped leafy spurge cover versus ground measured
flowering leafy spurge density
Mapping Leafy Spurge in Grasslands
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# UAV Images ! Image acquired on June 28, 2015 ! Flight height 100-110 m ! Spatial resolution: 3.2 cm
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Leafy spurge mapped using Mixed Tune Matched Filter Classification
Leafy spurge
Mapping Leafy Spurge in Grasslands
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Leafy spurge
Original classification map Classification map with tree and shrub mask applied
Mapping Leafy Spurge in Grasslands
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Ground samples
1. Transect: 11 2. Quadrats: 110 (High, Medium, Low density leafy spurge and no leafy spurge) 3. Stems of leafy spurge and flowering leafy spurge were recorded with each quadrat
Mapping Leafy Spurge in Grasslands
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Leafy spurge
Overall classification 70% Producer Accuracy 67% User Accuracy 88%
# Reconcile spatial resolution of image <4 cm) with global position system accuracy (>1 m)
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Remote Sensing in Grasslands
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! Potential applications of remote sensing – Mapping grassland spatial extent and changes over
time – Estimating productivity – Mapping invasive plant species – Others????
Remote sensing offers the potential to
map broader landscapes
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