Oleh : Dr. Taufik Hery Purwanto, M.Si. Fakultas Geografi UGM
Description: Using GIS to create descriptive models of the world --representations of reality as it exists. Analysis: Using GIS to answer a question or test an hypothesis. Often involves creating a new conceptual output layer, (or table or chart), the values of which are some transformation of the values in the descriptive input layer. --e.g. buffer or slope or aspect layers Prediction: Using GIS capabilities to create a predictive model of a real world process, that is, a model capable of reproducing processes and/or making predictions or projections as to how the world might appear. --e.g. flood models, fire spread models, urban growth models
Proses penanganan data spasial SIG
Dunia Nyata (The real world)
Akuisisi data spasial Gap antara Realita dengan Model
Source error
Basisdata spasial
Pengambilan Keputusan Use error
Process error
Perencanaan dan Managemen
Analisis dan Pemodelan Data spasial
Produk Geo-Informasi
Difference between analysis and modeling Analysis
Modeling
A static approach at one point in time
Multiple stages, perhaps representing different points in time
The search for patterns or anomalies, leading to new ideas
Implementing ideas and hypotheses
Manipulation of data to reveal what would otherwise be invisible invisible
Experimenting with policy options and scenarios
SourceLongley et al. (2005)
Spatial analysis is how we understand our world—mapping where things are, how they relate, what it all means, and what actions to take. From computational analysis of geographic patterns to finding optimum routes, site selection, and advanced predictive modeling, spatial analysis is at the very heart of geographic information system (GIS) technology. www.esri.com/products/arcgis-capabilities/spatial-analysis
Spatial analysis The process of examining the locations, attributes, and relationships of features in spatial data through overlay and other analytical techniques in order to address a question or gain useful knowledge. Spatial analysis extracts or creates new information from spatial data. GIS Dictionary, ESRI
Spatial analysis is a set of techniques for analyzing spatial data. (Goodchild)
GIS or Spatial analysis: application of operations or functions to spatial data to add value, support decisions, and reveal patterns. Geoprocessing (according to ESRI): GIS operation in which new data is derived from existing data. http://news.uk.msn.com/monks-protest-in-burma.aspx
Spatial analysis: Way in which we turn raw data into useful information – A set of techniques whose results are dependent on the locations of the objects being analyzed – Variety of methods – Powerful computers – Intelligent users Christine Erlien
More about spatial analysis… • Some methods are highly mathematical. • All effective spatial analysis requires an intelligent user, not just a powerful computer. • “Spatial analysis is best seen as a collaboration between the computer and the human, in which both play vital roles.” (Geographic Information Systems and Science, Wiley, 2001)
• Spatial analysis the crux of GIS because it includes all of the transformations, manipulations, and methods that can be applied to geographic data to add value to them, to support decisions, and to reveal patterns and anomalies that are not immediately obvious o Spatial analysis is the process by which we turn raw data into useful information, Examples: John Snow map of cholera
• Spatial analysis is the means of adding value to geographic data. • It turns data into information • Spatial analysis can reveal things that might otherwise be invisible. It can make what is implicit explicit.
Klasifikasi 5 kelas dg Natural of Breaks (jenks)
Peta choropleth Sawah Irigasi di DIY
Hot Spot Analysis (Getis-Ord Gi*)
Potensi Pengembangan Sawah Irigasi di DIY
Pada tahun 1854, Dr. John Snow menghadapi permasalahan bencana kolera yang terjadi di distrik Soho, London. Secara teori ada 2 kemungkinan penyebab penularan penyakit kolera disana, yaitu: 1. yang paling populer masyarakat disana percaya bahwa kolera disebabkan kontaminasi udara kotor dari areal bekas pekuburan kuno di pusat kota. 2. pendapat Dr. John Snow yang memperhatikan kemungkinan pemakaian air dari sumur-sumur yang ada di kota tersebut.
Kemudian Dr. John Snow menarik garis-garis hubungan antara korban dengan kedekatan ke lokasi pekuburan dan sumur.
Akhirnya, terungkap di atas peta sebuah pola yang sangat kuat menggambarkan hubungan antara korban dengan sumber air sumur yang diduga terkontaminasi. Setelah menutup sumur tersebut pasien berkurang drastis, setelah diteliti, ternyata saluran kotoran rumah yang ditanam 22 kaki telah bocor memasuki sumber air permukaan sedangkan sumur digali hanya selisih 6 kaki saja (28 kaki) menyebabkan air yang terambil adalah bagian yang terkontaminasi.
Density of cholera deaths using a 100 m kernel density function
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Define the problem Define the criteria Identify the data you need Plan the analysis Prepare the data for analysis Execute the analysis Examine and present the results
Understanding Where Where are my offices located? Where are my delivery trucks? Understanding where is about putting the world in context. This includes geocoding your data, putting it on a map, and symbolizing it in ways that can help you visualize and understand your data.
Measuring Size, Shape, and Distribution How long is the river? How tall is the building? How large are the coca fields? Measuring size and shape shows how large an object is or describes a feature in terms of its area, perimeter, length, height, and volume. It also helps to understand the distribution of multiple features.
Determining How Places Are Related Which rivers are within 10 miles of a pipeline? Have other crimes occurred at this location? Answering spatial questions often requires an understanding of spatial relationships such as proximity, coincidence, intersection, overlap, visibility, and accessibility.
Finding the Best Locations and Paths Whether you're looking for the best route to travel, the best corridor to build a pipeline, or the best location to site a new store, spatial analysis helps you make more informed decisions about the best locations and paths.
Detecting and Quantifying Patterns Where are clusters of high expenditures on electronic goods? Where are the hot spots of cancer deaths? Detecting and quantifying patterns in data can be used to find hot spots and outliers, find natural data clusters, and analyze changes in patterns over time.
Making Predictions How will a forest fire spread based on vegetation and wind? How will store size and travel distance attract or detract customers? Spatial analysis lets you use powerful modeling techniques to make predictions and better understand our world.
Recognizing which generic GIS analytic capability (or combination) can be used to solve your problem
GIS is also valuable because it is not one tool but a system containing hundreds of tools in a single environment. GIS also is valuable because it is an interdisciplinary toolkit. It is used to analyze social zones on a campus, the locations of hazardous chemicals or fiber optic cables, and species of plants in the gardens on that same campus. Globally, this same toolkit can be applied to subjects as diverse as urban planning, epidemiology, demography, wildlife management, and seismology. GIS is also valuable because it helps communicate complex ideas because it uses the powerful medium of the , which for centuries has helped to explain connections.
map
Joseph J. Kerski, Ph.D,GISP, Esri, 2015
• Where is GURGAON ?
• What are the soil characteristics there ? • What is the land use pattern in Gurgaon District ? • Which is the main economic activity in Gurgaon District ?
• What are the trends in rural and urban employment pattern in Gurgaon District ? • Where would be a better location for opening a restaurant in Gurgaon District ?
• Which is the shortest route to reach Gurgaon from New Delhi railway station?
Almost everything that happens or exists occurs ‘somewhere’. Knowing ‘where’ it happened or existed is critically important. All human activities require knowledge about the Earth, thus geographic location is very important.
1. Search (thematic search, search by region) 2. Location analysis (buffer, corridor, overlay) 3. Terrain analysis (slope/aspect, drainage network)
4. Flow analysis (connectivity, shortest path) 5. Distribution (nearest neighbor, proximity, change detection)
6. Spatial analysis/statistics (pattern, centrality, similarity, topology)
7. Measurements (distance, perimeter, shape, adjacency, direction)
1. Data Retrieval 2. Map Generalization 3. Map Abstractions 4. Map Sheet Manipulation 5. Buffer Generation 6. Polgygon Overlay And Dissolve 7. Grid Cell Analysis 8. Measurement 9. Digital Terrain Analysis 10. Output Techniques
1. Measurements 2. Layer statistics 3. Queries 4. Buffering (vector); Proximity (raster) 5. Filtering (raster) 6. Map overlay (layer on layer selections) 7. Transformations 8. Reclassification 9. Network analysis 10. Spatial interpolation 11. Grid (raster) analysis 12. Surface analysis 13. Analytic modeling
Copyright C. Schweik 2011 (Some material adapted from Heywood et al 1998; Theobald, 1999 )
the objects of study in a GIS application Geographic phenomena
Real world
Computer representations
Aplication computing
Visualitations
Simulation world
Analisis SIG dapat dinyatakan dengan fungsi-fungsi analisis spasial dan attribut yang dilakukan, serta kemampuan memberi jawaban-jawaban atau solusi yang diberikan terhadap pertanyaan-pertanyaan yang diajukan. Hasilnya yang berupa informasi baru disajikan dalam bentuk tabel , diagram, peta, atau kombinasinya.
A. GIS-based analysis 1. 2. 3. 4. 5. 6.
What is at......? Where is it.....? How has it changed........? What is the pattern ........ ? What if.......? Which is the best way ……..?
B. Manipulation Techniques (Analytic Functions and Data Processing Functions) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
Data retrieval Map generalization Map abstraction Map sheet manipulation Buffer generation Polygon overlay and dissolve Measurement Grid cell analysis Digital terrain analysis Output techniques
C. Manipulating Databases 1. 2. 3. 4. 5. 6. 7. 8. 9.
Create database Drop database Create table Drop table Insert Retrieve Update, edit Pack Index
1. Ada Apa di …. ? What is at …. ? (Condition) 2. Dimana … ? Where is it … ? (Location) 3. Apakah yang telah berubah … ? What has changed … ? (trend)
4. Pola … ? What is the pattern … ? (pattern) 5. Seandainya … ?
What if … ? (modeling) 6. Manakah jalan terbaik … ? Which is the best way … ? (routing) 7. Is there a general spatial pattern, and what are the anomalies?
1. Can you map that? (cartographic) -- e.g., delineating boundaries, area, elevation 2. Where is what? (cartographic) --e.g., indicating present land uses; eroded areas 3. Where has it changed? (temporal analysis) -- e.g., tracing historical land uses/changes for ancestral domain claim 4. What relationships exist? (spatial analysis) -- e.g., measuring elevation; distance; slope 5. Where is it best? (suitability analysis) -- e.g., identifying project site 6. What affects what?` (system models) -- e.g., improving water supply; rat infestation; erosion problems 7. What if…? (simulation) -- e.g., understanding impact of water impounding
Timur 10
11
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Selatan
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Tanya : Apa/Siapa yang berada pada lokasi P (5o Selatan, 11o Timur)
Jawab : Y
Tanya : Dimana objek X ? Jawab : 3o Selatan, 12o Timur
Linking features and attributes • Feature classes are tables that store spatial data • Each feature has a record in the table – Unique identifier links feature and attributes
FID = 4103 (Feature IDentifier)
Components of geographic data • Three general components to geographic information
Streets
Attributes
Geometry
Behavior Rules Streets and highways may not intersect
Timur 10
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Selatan
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Pengukuran :
• Panjang (jarak) = ((y2-y1)2 + (x2 – x1)2)½ • Lebar • Luas • Volume
• Kemiringan • Arah
Digital Elevation Model (DEM)
A tic is A reference or geographic control point for a coverage representing a known location on the earth's surface.
Euclidean distance in a GIS is the measure of a straight-line distance from pt A to B and is pretty simple.
In raster data model, the distance between two points can be calculated in the following ways: a. Euclidean distance method . A straight line is drawn joining the two points and a right angled triangle is created. The distance is then derived using the Pythagorean geometry.
b. Manhattan distance method : In this method, distance along the raster cell sides from one point to the other is taken. The following example illustrates the method.
Perimeter is calculated by counting the number of cells in each side that is making the boundary of the feature and then multiplying the count by resolution (cell size) of the raster grid. All the sides of the feature are then added. Area is calculated by counting the number of cells making a feature and multiplying the count by the area of an individual grid.
f the cell size of the raster is 10 m then the perimeter, P of the colored portion (abcd)
In vector data model, distance between two points is measured using the Euclidean distance method. Perimeter is calculated by adding the measurements of straight lines forming the feature. To calculate the area, the feature is subdivided into geometric shapes and then the areas of the geometric shapes are totaled.
B
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1. Bagaimana perubahan objek A, B, dan C dari tahun 1980 sampai 2000 A : Ukuran bertambah besar B : Ukuran mengecil dan berpindah C : Berubah bentuk
2. Perubahan apakah yang terjadi sejak tahun 1980 ? Perubahan ukuran pada A dan B Perubahan lokasi B Perubahan bentuk C
Penambahan D
MONITORING
"RDTR" = ‘Pertanian' AND "KET" = 'Permukiman'
X
Z
Z
Y X
Y Y
Z Z
X
Tanya : Apakah terdapat pola pada objek X ? Jawab : Ya, membentuk garis dari arah Barat laut ke Tenggara Tanya : Apakah ada hubungan antara X dan Y ?
Jawab : Ya, Y selalu dekat X Tanya : Apakah ada pola spasial lain ? Jawab : Ya, objek Z selalu dekat dengan batas daerah dan ukurannya makin besar ke arah Timur Laut
• 1855 Asiatic Cholera in London. – A water pump identified as the source.
• Cancer cluster to investigate health hazards. • Crime hotspots for planning police patrol routes. • Affects of weather in the US caused by unusual warming of Pacific ocean (El Nino).
Locations of water pumps and cholera deaths from John Snow's map (the Broad Street pump is the blue symbol at the center of the map)
Density of cholera deaths using a 100 m kernel density function
Analisis spasial minimarket di Kota Yogyakarta diselaraskan dengan pembatasan sesuai Peraturan WaliKota Yogyakarta Nomor 79 Tahun 2010 tentang Pembatasan Usaha Waralaba Minimarket di Kota Yogyakarta Bab V Pasal 6, yaitu: 1. Usaha waralaba minimarket berjarak paling dekat 400 (empat ratus) meter dari pasar tradisional. 2. Usaha waralaba minimarket hanya diperbolehkan di jalan-jalan tertentu yang terlampir pada Peraturan WaliKota tersebut (lokasi minimarket yang sesuai adalah berada pada jalan lokal sampai arteri sekunder dengan aksesibilitas yang lancar) 3. Jumlah usaha waralaba minimarket di setiap kecamatan dibatasi sesuai Peraturan WaliKota tersebut (6.000 jiwa, 1 minimarket)
4. Jarak Minimarket dari Konsumen (Jangkauan pelayanan minimarket sejauh 500 meter)
Kecendrungan spasial (spatial trends) pertumbuhan minimarket di Kota Yogyakarta tahun 2001 - 2010
• What is not a pattern? – Random, haphazard, chance, stray, accidental, unexpected. – Without definite direction, trend, rule, method, design, aim, purpose.
• What is a Pattern? – A frequent arrangement, configuration, composition, regularity. – A rule, law, method, design, description. – A major direction, trend, prediction.
• Search for spatial patterns. • Non-trivial search – as “automated” as possible. – Large search space of plausible hypothesis – Ex. Asiatic cholera : causes water, food, air, insects.
• Interesting, useful, and unexpected spatial patterns. – Useful in certain application domain • Ex. Shutting off identified water pump => saved human lives.
– May provide a new understanding of the world • Ex. Water pump – Cholera connection lead to the “germ” theory.
Kec. A
Kec. B
Operasi pada Overlay 1. Penyesuaian Koordinat (Georeferencing) 2. Proses Interseksi Geometrik raster vector 3. Kombinasi Data Attribut
Chrisman, 1997. Exploring Geographic Information Systems. New York: Wiley
Kecamatan Kec. A
Kec. B
Kec. A Subur Terjal Tdk. Ada Gerakan Massa
3
Kec. A Tidak Subur Terjal Tdk. Ada Gerakan Massa
4
Tanah Kec. A Subur Datar Tdk. Ada Gerakan Massa
1
Subur
Tidak Subur
Kec. A Tidak Subur Terjal Ada Gerakan Massa
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Kec. B Subur Datar Tdk. Ada Gerakan Massa
Kec. B Tidak Subur Terjal Ada Gerakan Massa
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Lereng
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Kec. B Subur Datar Ada Gerakan Massa
Kec. B Tidak Subur Datar Ada Gerakan Massa
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Datar
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Terjal Harga Tanah :
Bencana Tdk. ada gerakan massa Gerakan massa
1 2 3 4 5 6 7 8
Harga Tanah Mahal
Harga Tanah Murah
Penggunaan Lahan
Sumber Polusi
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2 1 x
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Zone Polusi
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Sumber Polusi Permukiman Zone 1-2-3 Km
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Dampak Polusi
Dampak Polusi Berat Dampak Polusi Ringan Tidak Terkena Dampak Polusi Ringan
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Tanya : Mana Route terbaik dari A ke C ? Jawab : A
D
C
http://www.yell.com/maps/
Analysis of 3D transportation networks is especially important for management of facilities such as hospitals and campuses. This video shows a number of 3D network analysis useful for facilities management. Interior space data provided by Penbay Solutions. http://video.arcgis.com/watch/2413/3d-network-analysis
This section describes the various analytic functions and data processing functions that can be performed on spatially automated data. Within this section, the actual function is described in a narrative outline and referenced to a pictorial representation of conceptually how each function is performed. No attempt is made to describe these functions in detail as different software systems approach the solution using alternative types of algorithms. Alternatively, emphasis is placed on defining the actual function which is being performed. It should be mentioned that these descriptions are meant to be representative and there will be examples left out.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
Data Retrieval Map Generalization Map Abstractions Map Sheet Manipulation Buffer Generation Polgygon Overlay And Dissolve Grid Cell Analysis - Network Analysis Measurement Digital Terrain Analysis Output Techniques
this series of techniques involves the basic extraction, query, and Boolean manipulation of information contained in organized geographic information system.
Dalam basis data SIG maka penelusuran data dapat dilakukan dengan dua cara penelusuran yaitu : • Penelusuran Data Attribut menghasilkan (posisi) Data Spasial
Data attribut (Teks)
Data Grafis
• Penelusuran (posisi) Data Spasial menghasilkan Data Attribut
Data Grafis
Data attribut (Teks)
Query Query is a logical question which is performed on the database to retrieve specific data. Queries are useful for checking the quality of the data and the results obtained. There are two types of queries that can be performed in GIS: 1. Aspatial or attribute queries: questions about the attributes of the feature. These do not include any spatial information. “Who owns the Star coffee shop?” is a simple query that does not involve analysis of any spatial component. Such queries could be performed by database software alone 2. Spatial queries: It involves selection of features based on location or other spatial information.
The Database : To better understand data and file concepts, learn the hierarchy and terms in this drawing.
A new conceptualisation for spatial information functions
The new working relationship between spatial databases and GIS
This series of generalization tools is most frequently used when map scales are changed.
Map abstraction is closely associated with map generalization but involves five different forms of technology.
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Nearest Neighbor “Thiessen” Polygon Interpolation
Spline Interpolation
Map sheet manipulation a series of techniques which manipulate the x,y coordinates for a given map sheet.
Affine transformations
Buffer generation involves the creation of new polygons from points, lines, and polygon features within the data bank. Specifically from a given point or series of points, circular as well as square buffers can be calculated.
Polygon overlay and dissolve techniques involve the compositing (integrating) or extracting (dis-integration) of multiple maps (two or more) in order to create a new data set.
Operasi pada Overlay 1. Penyesuaian Koordinat (Georeferencing) 2. Proses Interseksi Geometrik raster vector 3. Kombinasi Data Attribut
Chrisman, 1997. Exploring Geographic Information Systems. New York: Wiley
The four most common types of measurement tasks involve points, lines, and polygons and volumes.
Digital terrain analysis involves the computation of a variety of outputs from a digital elevation model (see Figure below). There are various forms of digital elevation models and therefore different forms of actual analysis that can be performed.
Figure below illustrates five examples of basic analytic activities that are performed using grid cell data. These techniques are similar to the types of map analysis that are performed in x,y coordinate data structure but have more generalized spatial resolution. It should be pointed out that the grid cell technique for map manipulation is typically much more efficient both in data storage as well as in the operation of the analytic tasks.
Raster Grid – but most common raster is composed of squares, called grid cells – grid cells are analogous to pixels in remote sensing images and computer graphics
Figure below illustrates the basic four output formats from a GIS system.
1. 2. 3. 4. 5. 6. 7. 8. 9.
Create database Drop database Create table Drop table Insert Retrieve Update, edit Pack Indexs
