Advantages of ISP(contd) air-photo interpretation information was synthesised in a readil usable format (really a non-digital Geographic Information System/GIS provided a means of placing field survey data in a geographic context; ie addressed spatial extension problem the basic concept of aPl as the means of spatial extension is still used in soi geological, and vegetation surveys
Advantages of ISP (cont’d) …. air-photo interpretation information was synthesised in a readily usable format (really a non-digital Geographic Information System/GIS) provided a means of placing field survey data in a geographic context; ie addressed spatial extension problem the basic concept of API as the means of spatial extension is still used in soil, geological, and vegetation surveys!
Limitations of Integrated Survey 1. Subjective(not explicit), lack of repeatability 2. Poor predictive capability(assumption of covariance often invalid); descriptive 3. Primary survey data lost; data classified 4. Land units/elements not mapped 5. Single general purpose landscape classification 6. Not dynamic; what about change/flux? 7. No climate inputs -meso scale topo scale
Limitations of Integrated Survey: 1. Subjective (not explicit), lack of repeatability 2. Poor predictive capability (assumption of covariance often invalid); descriptive 3. Primary survey data lost; data classified 4. Land units/elements not mapped 5. Single general purpose landscape classification 6. Not dynamic; what about change/flux? 7. No climate inputs - meso scale - topo scale
The ' Parametric Paradigm' 1. Select key environmental determinants that drive system response 2. Generate spatially distributed data-sets for each parameter 3. Apply quantitative data analysis rejects notion of a single classification for, in effect, problem-specific classifications parameter-specific survey and spatial extension required
The ‘Parametric Paradigm’ 1. Select key environmental determinants that ‘drive’ system response 2. Generate spatially distributed data-sets for each parameter 3. Apply quantitative data analysis rejects notion of a single classification for, in effect, problem-specific classifications parameter-specific survey and spatial extension required
Therefore, a modelling approach is required y=f(X1X2,X3,…X) y is system response Xs are driving variables determinants predictors Therefore, if have spatial estimates of x can make a spatial prediction of y anywhere in the land Therefore, need Geographic Information System(GIs use computer to spatially extend survey data use computer to store and analyse data realistic alternative to APl and integrated survey
Therefore, a modelling approach is required y = f (X1 , X2 , X3 , … , Xn) y is system response Xs are driving variables determinants predictors Therefore, if have spatial estimates of Xs , can make a spatial prediction of y anywhere in the land Therefore, need Geographic Information System (GIS) use computer to spatially extend survey data use computer to store and analyse data realistic alternative to API and integrated survey
GiS tools to handle landscape wide, spatial data Digital Elevation Models and derived gridded estimates of terrain attributes Interpolated Climate Surfaces Digitized thematic maps, eg. geology Satellite-based (and aeroplane- based digital sensors, eg. Landsat, TM, SPOT. hyperspectral scanners
GIS tools to handle landscapewide, spatial data Digital Elevation Models and derived gridded estimates of terrain attributes Interpolated Climate Surfaces Digitized thematic maps, eg. geology Satellite-based (and aeroplane-based) digital sensors, eg. Landsat, TM, SPOT, hyperspectral scanners