Remote Sensing

Vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including climate variability and extremes (IPCC, 2001)

The goal of vulnerability assessment: “is not to produce a score or rating of a particular community’s current or future vulnerability. Rather, the aim is to attain information on the nature of vulnerability and its components and determinates.” (Smit and Wandel, 2006)

Exposure Sensitivity Adaptive capacity Vulnerability Adaptation Change in mean annual temperature Change in annual variance of temperature Change in days of heat stress Change in days of cold stress Change in mean annual rainfall Change in mean annual soil moisture Elevation Land cover Vegetation cover Population density % educated population % employed Per capita community service

Analysis of change- PNG

1:4000 Stereo aerial photograph 1m spatial resolution laser scanner 1 m spatial resolution (bands 14,9,1 in RGB)

Aerial photographs -small area coverage -narrow spectral range (visible) -analogue -tilt, relief displacement errors (need to correct) Satellite images -large area coverage -broader spectral range -minimal tilt distortion -digital

Two main remote sensing systems Passive – reflectance measurements Active – transmit em radiation at specific wavelength and sample what is reflected back MODIS – Moderate Resolution Imaging Sensor Since spectral bands Resolution 1km, 500 m, 250 m Image swath 2330 km 1-2 day repeat cycle Landsat Landsat 1,2, Landsat 4,5 (6 failed) 1999 landsat 7 7 spectral bands 1(blue), 2(green), 3(red) 4(NIR), 5(SWIR), 6(thermal) 7(SWIR)

Multi-band scanning Spectral resolution (number of bands and bandwidth) Radiometric resolution (level of quantization of reflectance values)

SPOT VEGETATION Scale

What remote sensing? SPECTERRA: Airborne Digital Multi- Spectral Imagery SPOT VEGETATION SPOT HVIR (hi-res) Landsat TM Canopy photography

What Scale? DMSI: 0.5m SPOT HVIR (hi-res): 10m Landsat TM: 25m SPOT VEGETATION: 1000m Canopy photography: Camera dependent

DMSI Scale 0.5m

Landsat Scale 25m

The Yalgorup Dataset Quality DMSI in 2007, 2008 and 2010 Canopy assessments in 2008 Pixel matched & with bidirectional reflectance distribution function (SPECTERRA) “Like value” linear based callibration of yearly scenes as per CSIRO’s Firby and Campbell method (i.e. same as Landmonitor) Scaled and cropped to normalised range 12BIT to 8BIT for Grey Level Covariance Matrix and Vegetation indices

The Yalgorup dataset cont… Correlation of field data and in-canopy indices based (USDA canopy assessments by Paul Barber) Modelling of best correlating indices across 12 trees, then all 80 trees in site