GIS Final Spring 25

remote sensing

the acquisition of info about an object or phenomenon without making physical contact with it

how remote sensing works

satellite sensors based on reflected energy

photogrammetry

the sci of measuring geometry and mapping

endlap

overlap of sequential photos along a flightline (65%)

sidelap

overlap of adjacent flightlines (25%)

types of aerial photos

vertical, oblique

vertical aerial photo

photos taken straight down

oblique aerial photo

photos taken at an angle

low oblique aerial photo

photo shows ground surface only

high oblique aerial photo

photo shows surface and horizon

orthorectification

process of removing distortions caused by terrain variation and camera tilt

info needed for orthorectification

location of perspective center of camera orientation, (in)direct terrain height

photo interpretation

a process of converting images into info (rater or vector) by identifying positions and properties of features

minimum mapping unit (MMU)

defines the lower limit on what we consider significant and defines the are, length and/or width of the smallest important feature

types of satellite remote sensing

passive and active

passive remote sensing instrument

detect energy that is emitted from natural environment

active remote sensing instrument

emits energy and collects data based on the return signal

resolutions of remote sensing

spatial, spectral, temporal, radiometric

spatial resolution

ability to distinguish between two-closely spaced objects on an image

spectral resolution

ability to resolve spectral features (number of bands, band width, wavelength region)

temporal resolution

how often the sensor acquires data

radiometric

ability to discriminate very slight differences in the brightness of objects, sensitivity of detectors to small differences in electromag. energy

satellite systems

high-res, mid-res, coarse-reshi

high-res satellite

res is finer than 4m

ex on high-res satellites

WorldView, Dove constellation, Satellite Pour (French)

mid-res satellites

spatial res 5m to <100m

ex of mid-res satellites

SPOT-1 to 5, Landsat, Sentinel

coarse-res satellite

spatial res >250m

ex of coarse-res satellites

VIIRS and MODIS

primary uses of satellite images

create or update landcover, detect and monitor changes

types of remote sensing

solar-reflective, thermal, microwave, radar, lidar

types of satellite platform orbit

geostationary/ geosynchronous, polar/ near-polar, lagrange points

geosynchronous orbit

35,500km above earth where orbital speed=planet rotation

geostationary orbit

directly above equator “parked” above same place

polar/ near-polar orbit

2,000 km above earth and travels from pole to pole. passes same place at the exact same times

broad categories and overlapping classes of spatial models

cartographic, simple spatial, spatio-temporal

cartographic models

automating manual map analysis and processing, static and fixed

simple spatial models

applying math relationships to predict a continuous variable across space

spatio-temporal models

attempt to explicitly represent time-driven processes, dynamic in space and time

characteristics of cartographic model

suitability analysis, flowchart, rankings, weightings

suitability analysis

ranking land based on its utility for various purposes

rankings

assignment of relative importance within the same layer

types of rankings

discrete and continuous

weightings

assignment of relative importance of different criteria that influences the result

spatio-temporal model characteristics

x/y/time analysis, timescale relationships, needs explicit inputs

ways to describe spatial accuracy

positional, attribute, logical, completeness

positional accuracy

how close the locations of objects represented in a digital data set correspond to the true locations in real world

attribute accuracy

summarizes how different the attributes are from the true values

logical accuracy

reflects presence, absence, or freq of inconsistent data

completeness

how well data ser captures all features

lineage

sources, methods, timing and persons responsible for the development of a data set

precision

high consistency in closeness of answers even if wrong

accuracy

how close a measurement is to the true value

error matrix (confusion matrix)

accuracy of categorical data, summary of main characteristics of confusion among categories

producer’s accuracy

the off-diagonal elements in EACH COLUMN

overall accuracy

sum of diagonal/ total number of samples

user’s accuracy

off diagonal elements in EACH ROW

omission error

misclassification of producer’s accuracy

commission error

misclassification of error in user’s accuracy

find positional accuracy

GIS layer - true value