GIS MODELS AND MODELINGSHIVANGI SOMVANSHIASSISTANT PROFESSORAIES, AMITY UNIVERSITY (NOIDA)

WHAT IS A MODEL?• A model is a simplified representation of a

phenomenon or a system.• It help us to better understand a phenomenon or

a system by retaining the significant features and relationship of reality.

• Often used to identify locations that meet specific criteria.

• Can be used to infer an unknown quality or quantity using relationships with known or measurable quantities or qualities.

• Can be used to generate new data.• Can be used to predict the future.

CLASSIFICATION OF GIS MODELS1. DESCRIPTIVE OR PRESCRIPTIVE :A Descriptive model describes the existing condition of spatial data, and a prescriptive model offers a prediction of what the condition could be or should be.

2. STATIC OR DYNAMIC:A Dynamic model emphasizes the changes of spatial data and the interaction between variables, whereas a static model deals with the state of spatial data at a given time. Time is important to show the process of changes in the dynamic model. Many environmental models are best studied as dynamic models.

CLASSIFICATION OF GIS MODELS3. DEDUCTIVE OR INDUCTIVE:A deductive model represents the conclusion derived from a set of premises. Theses premises are often based on scientific theories or physical laws. An inductive model represents a conclusion derived from empirical data and observations.For example to assess the potential of landslide one can use a deductive model based on laws in physics or use an inductive model based on recorded data from past landslides.

MODELING PROCESS• FIRST STEP: Define the goal of the model

(Objective and purpose).

• SECOND STEP: Identify model variables. In the same step the modeler gathers the mathematical equations of the model and commands in the GIS to perform the computations.

• THIRD STEP: Implementation and the calibration of the model.

APPLICATION OF GIS MODELING IN NATURAL RESOURCES• Predicting future conditions• Predicting the impact of alternative management

actions.• Landuse planning• Site selection• Risk Assessment – Identify the area of possible

concern.

COMMONLY USED GIS MODELS1. BINARY MODEL

INDEX MODEL

REGRESSION MODELA regression model relates a dependent variable to a number of independent variables in an equation, which are then best use to predict or estimation.

With other tools you ask WHERE something is happening?

With Regression Analyses, you ask WHY something is happening.

What are the factors contributing to the higher than the expected values.

Regression analysis allows you to…

• Model, examine, and explore spatial relationships• Predict

Residuals are the difference between the observed and predicted values

EXAMPLE OF DEVELOPING REGRESSION MODEL FOR

MONITORING OF RIVER WATER QUALITY

Sampling Sites

Data Collection : 1. Sample and laboratory analysis data of water quality parameters2. Radiance value of all the sampling points in different bands and band combinations

CORRELATION

REGRESSION

REGRESSION MODEL• Y = a + bX1 + cX2 + dX3• a, b, c, d are constants • X1, X2, X3, - independent variables (in this case

they are B1, B3 and B4 radiance values)• Y = Dependent Variable (BOD)

• Rsquare value = 0.695 (i.e. 69.5% accurate BOD can be calculated using B1, B3 and B4 radiance values)

• Model is :BOD (Y) = 20.918 + (-0.034)B1 + (-2.160)B3 +

(-2.420)B4

BOD (Biochemical Oxygen Demand) MAP

THANK YOU