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WEEK 1

1. DOWNLOAD DATA DIVA GIS

2. GROUP LAYER

3. LAYER PROPERTIES

4. VECTOR CLASSIFICATION (ADMIN MAP)

5. DISPLAY LABEL OF ADMIN MAP

6. CONNECT TO FOLDER

7. CREATE GEODATABASE

8. CONVERT VECTOR COORDINATE (WGS TO RSO)

9. CONVERT RASTER COORDINATE (ELEVATION) – PROJECT RASTER

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1. Insert MYS_adm1 data
2. Use the 'select' tool to select the Perlis district.
3. Use the 'select' tool to select landuse type ( landuse = 'bare land' ) AND ( landuse = 'agriculture land' ).
4. Area < 7 AND 'select' status as 'Freehold'.

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1. The raster data model presents geographical data that divides geographic space into a regular grid of cells or pixels. Each grid cell holds a value that reflects a specific attribute, such as elevation temperature, land use, or any other measurable or categorical data.

2. Five common vector/raster data measurements used in GIS applications.
> Distance
> Area
> Elevation
> Attribute value
> Slope and aspect

3. It is essential to assess the quality of geospatial data in order to assure its correctness and trustworthiness. There are several ways that may be used to evaluate the GIS data model offered by agencies. To begin, a visual inspection and cross-referencing method involves visually inspecting the data in GIS software and comparing it to trustworthy sources to find flaws such as misalignments or gaps. Second, attribute verification consists of verifying that attribute data is consistent and reliable and that it aligns appropriately with matching geographical characteristics. Third, topological validation entails executing tests to ensure spatial integrity and discovering problems in the geographic data such as gaps or overlaps. Fourth, coordinate accuracy evaluation entails comparing feature locations to authoritative reference or survey data to determine variances using statistical measures such as RMSE.

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WEEK 1 (LECT)

Homework

i.    DESCRIBE THE SKILLS REQUIRED TO BE AS GIS ANALYST.

The skills required to be a GIS analyst is to possess strong IT skills . This because the use of programming software such as Phyton is utilized. other than that they also have to be highly detail oriented and masterful in solving problems. working as a GIS also needed to be efficient in writing and communication.

ii.   EXPLAIN THE IMPORTANCE OF SPATIAL ANALYSIS IN REAL WORLD MODELING.

You can solve challenging location-based problems using spatial analysis, which also helps you better understand where and what is happening in your world. Not to mention that using spatial analysis to make decisions opens up new perspectives.

iii. WHY GIS IS ESSENTIAL TO HELP ON DECISION MAKING ON CLIMATE CHANGE FORECASTING?

GIS is crucial for decision-making in climate change forecasting because it is effective at monitoring environmental data analysis and promotes better planning by making it simple to view and track both current and historical data.

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WEEK 4 VECTOR OVERLAY ANALYSIS

i.  Insert all provided spatial data (land-use, road and elevation
ii.  Add column in landuse.shp and write as landuse_Perlis.
iii.  Use DISSOLVE tool to create a single polygon.
iv.  Use the single polygon of landuse as boundary and use EXTRACT BY MASK to select the DEM Perlis region only.
v.  Use CLIP tool for selecting the Perlis Road only.
vi.  Use BUFFER tool to delineate the zoning area of road in 100m and 200m. It should be in two different layer.
vii.  Use ERASE tool to eliminate the zone of 100m and to preserve area within range 100-200m.
viii.  Use INTERSECT tool to identify the landuse type within 100m for the centre of road and within 100-200m. Specify the landuse involved.
ix.  Create grid polygon by create new polygon. Open catalog pane and create new feature class/ shapefile. Save. Digitise big polygon cover the landuse. Then, use  to split into 4 different polygon. Add new column as Zone. Then fill in A, B, C,D.
x.  Split the landuse into 4 different area. Use SPLIT tool. Try to see what will happen to your data.
xi.  Use MERGE tool to combine all layers into single polygon.
xii.  Use RECLASSIFY to classify the DEM (elevation) into 3 classes: i) < 200m, ii) 200 – 300m and iii) >300m

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WEEK 3 TASK

1. Download example data https://tinyurl.com/tevtwrjy.
2. Add to TOC.
3. Import landuse data to your feature dataset.
4. Fix error (topology).

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Kriging Method

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NEW TASK

i. Use combine tool
ii. Combine file classDEM and ClassSlope
iii. Create as New Layer
iv) Count Pixel for elevation 3)20-30m and slope 4) 0.10-1 (add answer in your padlet) week 7
v) Count Pixel for elevation 1)<10m and slope 2) 0.1-0.5 AND elevation 4) >30m and slope 2) 0.1-0.5

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ASSIGNMENT

ASSIGNMENT: SLT 8 JAM (20%)

ASSIGNMENT

PLO: Numerical Skill

Your assignment must consist of four (4) pages and describe in detail for two (2) applications involved in your assignment. The assignment preparation should adhere to the following sections on each page:

i.         The following topic has been assigned to you in Excel: https://tinyurl.com/29v9s6c8

ii.         Introduction of the selected application

iii.         How statistical equations apply in the chosen application.

iv.         Show the equation and steps of calculation involved to verify the results.

v.         Declare the source as appendices (APA 7th Format). Cite the sources in the appendices (APA 7th Format).

The font size is 12-point Times New Roman. Attach the assignment to your padlet.

Please restrict access to my email account, ernieza@uitm.edu.myt to your padlet. Please restrict access to my email account, ernieza@uitm.edu.my. Submit by April 17, 2023.