class: center, middle, inverse, title-slide # Instrumentos de Análisis Urbanos II ## Maestría en Economía Urbana ### ### Universidad Torcuato Di Tella ### 01/08/2023 --- layout: true <div class="my-footer"><span>Instrumentos de Análisis Urbanos II - <a href="https://tuqmano.github.io/geo_utdt/">https://tuqmano.github.io/geo_utdt/</a></span></div> <style>.xe__progress-bar__container { top:0; opacity: 1; position:absolute; right:0; left: 0; } .xe__progress-bar { height: 0.25em; background-color: #fdbd15; width: calc(var(--slide-current) / var(--slide-total) * 100%); } .remark-visible .xe__progress-bar { animation: xe__progress-bar__wipe 200ms forwards; animation-timing-function: cubic-bezier(.86,0,.07,1); } @keyframes xe__progress-bar__wipe { 0% { width: calc(var(--slide-previous) / var(--slide-total) * 100%); } 100% { width: calc(var(--slide-current) / var(--slide-total) * 100%); } }</style> --- class: inverse, center, middle ## Domar los Datos III ### `geo` --- class: inverse ## <svg viewBox="0 0 448 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#fdbd15;" xmlns="http://www.w3.org/2000/svg"> <path d="M448 360V24c0-13.3-10.7-24-24-24H96C43 0 0 43 0 96v320c0 53 43 96 96 96h328c13.3 0 24-10.7 24-24v-16c0-7.5-3.5-14.3-8.9-18.7-4.2-15.4-4.2-59.3 0-74.7 5.4-4.3 8.9-11.1 8.9-18.6zM128 134c0-3.3 2.7-6 6-6h212c3.3 0 6 2.7 6 6v20c0 3.3-2.7 6-6 6H134c-3.3 0-6-2.7-6-6v-20zm0 64c0-3.3 2.7-6 6-6h212c3.3 0 6 2.7 6 6v20c0 3.3-2.7 6-6 6H134c-3.3 0-6-2.7-6-6v-20zm253.4 250H96c-17.7 0-32-14.3-32-32 0-17.6 14.4-32 32-32h285.4c-1.9 17.1-1.9 46.9 0 64z"></path></svg> Referencias * R - Spatial: <https://www.r-spatial.org/> * [Geocomputation with R](https://geocompr.robinlovelace.net/), Robin Lovelace, Jakub Nowosad, Jannes Muenchow (2019) * [Spatial Data Science](https://r-spatial.org/book/), Edzer Pebesma y Roger Bivand (2023) --- class: inverse, middle # _useR 2021_: Pebesma * Video: https://youtu.be/O8V4QJ13Gjc * Slides: https://edzer.github.io/UseR2021/#1 --- ## Universo _geo_ (desde `R`) <img src="https://r-spatial.org/book/images/sf_deps.png" width="80%" /> Fuente: [_Spatial Data Science_](https://r-spatial.org/book/) --- ### Geometrías <img src="sesion6_files/figure-html/unnamed-chunk-2-1.png" width="60%" /> Fuente: [_Spatial Data Science_](https://r-spatial.org/book/03-Geometries.html) (ver detalle) --- ### Operaciones - [Spatial Data Science](https://r-spatial.org/book/03-Geometries.html#sec-opgeom) #### INPUTS -- * `predicates`: una consulta lógica para determinar si una propiedad es `TRUE` - `is.empty()` -- * `measures`: una cantidad (e.g. un valor númerico con una unidad de medida determinada) - `area()` -- * `transformations`: generación de nuevas geometrías - `centroid()` --- ### Operaciones - [Spatial Data Science](https://r-spatial.org/book/03-Geometries.html#sec-opgeom) #### SOBRE QUE OPERAN -- * `unary`: una única _geometry_ * `binary`: pares de _geometry_ * `n-ary`: conjunto de _geometries_ <https://r-spatial.org/book/03-Geometries.html#sec-opgeom> --- ### Proyecciones <img src="sesion6_files/figure-html/unnamed-chunk-3-1.png" width="60%" /> Fuente: Pebezma - useR (2021) --- ### Proyecciones <img src="sesion6_files/figure-html/unnamed-chunk-4-1.png" width="60%" /> Fuente: Pebezma - useR (2021) --- class: inverse, middle # Hoja de ruta 1. `{sf}` / _RSpatial_ -- 2. `{geoAr}` -- 3. `{rmapshaper}` --- background-image: url(https://user-images.githubusercontent.com/520851/34887433-ce1d130e-f7c6-11e7-83fc-d60ad4fae6bd.gif) background-position: 95% 5% background-size: 10% ### Datos Espaciales Simplificados <img src="https://user-images.githubusercontent.com/520851/50280460-e35c1880-044c-11e9-9ed7-cc46754e49db.jpg" width="80%" /> --- background-image: url(https://user-images.githubusercontent.com/520851/34887433-ce1d130e-f7c6-11e7-83fc-d60ad4fae6bd.gif) background-position: 95% 5% background-size: 10% ## _Simple Features_ <img src="https://r-spatial.org/book/images/sf_obj.png" width="80%" /> [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M326.612 185.391c59.747 59.809 58.927 155.698.36 214.59-.11.12-.24.25-.36.37l-67.2 67.2c-59.27 59.27-155.699 59.262-214.96 0-59.27-59.26-59.27-155.7 0-214.96l37.106-37.106c9.84-9.84 26.786-3.3 27.294 10.606.648 17.722 3.826 35.527 9.69 52.721 1.986 5.822.567 12.262-3.783 16.612l-13.087 13.087c-28.026 28.026-28.905 73.66-1.155 101.96 28.024 28.579 74.086 28.749 102.325.51l67.2-67.19c28.191-28.191 28.073-73.757 0-101.83-3.701-3.694-7.429-6.564-10.341-8.569a16.037 16.037 0 0 1-6.947-12.606c-.396-10.567 3.348-21.456 11.698-29.806l21.054-21.055c5.521-5.521 14.182-6.199 20.584-1.731a152.482 152.482 0 0 1 20.522 17.197zM467.547 44.449c-59.261-59.262-155.69-59.27-214.96 0l-67.2 67.2c-.12.12-.25.25-.36.37-58.566 58.892-59.387 154.781.36 214.59a152.454 152.454 0 0 0 20.521 17.196c6.402 4.468 15.064 3.789 20.584-1.731l21.054-21.055c8.35-8.35 12.094-19.239 11.698-29.806a16.037 16.037 0 0 0-6.947-12.606c-2.912-2.005-6.64-4.875-10.341-8.569-28.073-28.073-28.191-73.639 0-101.83l67.2-67.19c28.239-28.239 74.3-28.069 102.325.51 27.75 28.3 26.872 73.934-1.155 101.96l-13.087 13.087c-4.35 4.35-5.769 10.79-3.783 16.612 5.864 17.194 9.042 34.999 9.69 52.721.509 13.906 17.454 20.446 27.294 10.606l37.106-37.106c59.271-59.259 59.271-155.699.001-214.959z"></path></svg>`{sf}`](https://r-spatial.github.io/sf/) --- class: inverse, center, middle background-image: url(../figs/geoAr.png) background-size: contain --- background-image: url(https://github.com/PoliticaArgentina/data_warehouse/raw/master/hex/geoAr.png) background-position: 95% 5% background-size: 10% ## Geometrías Argentinas ### Diccionario - [show_arg_codes()](https://politicaargentina.github.io/geoAr/index.html) -- ```r library(geoAr) show_arg_codes() ## # A tibble: 26 x 5 ## id codprov codprov_censo codprov_iso name_iso ## <chr> <chr> <chr> <chr> <chr> ## 1 ARGENTINA " " " " AR Argentina ## 2 CABA "01" "02" AR-C Ciudad Autónoma de Buenos Air~ ## 3 BUENOS AIRES "02" "06" AR-B Buenos Aires ## 4 CATAMARCA "03" "10" AR-K Catamarca ## 5 CORDOBA "04" "14" AR-X Córdoba ## 6 CORRIENTES "05" "18" AR-W Corrientes ## 7 CHACO "06" "22" AR-H Chaco ## 8 CHUBUT "07" "26" AR-U Chubut ## 9 ENTRE RIOS "08" "30" AR-E Entre Ríos ## 10 FORMOSA "09" "34" AR-P Formosa ## # i 16 more rows ``` --- background-image: url(https://github.com/PoliticaArgentina/data_warehouse/raw/master/hex/geoAr.png) background-position: 95% 5% background-size: 10% ## Geometrías Argentinas ### Diccionario (**departamentos**) - [show_arg_codes()](https://politicaargentina.github.io/geoAr/index.html) -- ```r library(geoAr) show_arg_codes(nivel = "departamentos") ## # A tibble: 527 x 6 ## id codprov coddepto codprov_censo coddepto_censo nomdepto_censo ## <chr> <chr> <chr> <chr> <chr> <chr> ## 1 ARGENTINA " " " " " " " " " " ## 2 CABA "01" "001" "02" "001" "COMUNA 01" ## 3 CABA "01" "002" "02" "002" "COMUNA 02" ## 4 CABA "01" "003" "02" "003" "COMUNA 03" ## 5 CABA "01" "004" "02" "004" "COMUNA 04" ## 6 CABA "01" "005" "02" "005" "COMUNA 05" ## 7 CABA "01" "006" "02" "006" "COMUNA 06" ## 8 CABA "01" "007" "02" "007" "COMUNA 07" ## 9 CABA "01" "008" "02" "008" "COMUNA 08" ## 10 CABA "01" "009" "02" "009" "COMUNA 09" ## # i 517 more rows ``` --- background-image: url(https://github.com/PoliticaArgentina/data_warehouse/raw/master/hex/geoAr.png) background-position: 95% 5% background-size: 10% ## Geometrías Argentinas ### Obtener poligonos - [get_geo()](https://politicaargentina.github.io/geoAr/index.html) -- ```r get_geo(geo = "TUCUMAN") ## Simple feature collection with 17 features and 2 fields ## Geometry type: MULTIPOLYGON ## Dimension: XY ## Bounding box: xmin: -66.18101 ymin: -28.01575 xmax: -64.48315 ymax: -26.06037 ## Geodetic CRS: WGS 84 ## # A tibble: 17 x 3 ## codprov_censo coddepto_censo geometry ## * <chr> <chr> <MULTIPOLYGON [°]> ## 1 90 007 (((-64.49919 -26.23353, -64.49857 -26.26325, -6~ ## 2 90 014 (((-65.13782 -26.74975, -65.10095 -26.75771, -6~ ## 3 90 021 (((-65.94729 -27.08444, -65.93885 -27.0989, -65~ ## 4 90 028 (((-65.62733 -26.87134, -65.62598 -26.84177, -6~ ## 5 90 035 (((-65.47532 -27.53838, -65.43503 -27.5425, -65~ ## 6 90 042 (((-65.51768 -27.54528, -65.53685 -27.62278, -6~ ## 7 90 049 (((-65.51348 -27.62978, -65.52091 -27.66553, -6~ ## 8 90 056 (((-65.12933 -27.02488, -65.12589 -27.01659, -6~ ## 9 90 063 (((-65.43583 -26.83751, -65.38124 -26.84196, -6~ ## 10 90 070 (((-65.86853 -26.99852, -65.85796 -27.01388, -6~ ## 11 90 077 (((-65.93481 -27.39544, -65.89887 -27.3702, -65~ ## 12 90 084 (((-65.16293 -26.82289, -65.18562 -26.86204, -6~ ## 13 90 091 (((-65.33499 -27.20478, -65.33462 -27.21948, -6~ ## 14 90 098 (((-66.08361 -26.23547, -66.06621 -26.23792, -6~ ## 15 90 105 (((-65.70111 -26.52317, -65.65078 -26.5263, -65~ ## 16 90 112 (((-65.52483 -26.09667, -65.4682 -26.09253, -65~ ## 17 90 119 (((-65.27025 -26.84087, -65.28587 -26.83549, -6~ ``` --- background-image: url(https://github.com/PoliticaArgentina/data_warehouse/raw/master/hex/geoAr.png) background-position: 95% 5% background-size: 10% ## Geometrías Argentinas **raw** ### Obtener poligonos - [get_geo()](https://politicaargentina.github.io/geoAr/index.html) -- ```r (TUCUMAN <- get_geo(geo = "TUCUMAN", * simplified = FALSE)) ## Simple feature collection with 17 features and 2 fields ## Geometry type: MULTIPOLYGON ## Dimension: XY ## Bounding box: xmin: -66.18101 ymin: -28.01579 xmax: -64.48315 ymax: -26.05908 ## Geodetic CRS: WGS 84 ## # A tibble: 17 x 3 ## codprov_censo coddepto_censo geometry ## * <chr> <chr> <MULTIPOLYGON [°]> ## 1 90 007 (((-64.49901 -26.21797, -64.49802 -26.21785, -6~ ## 2 90 014 (((-65.15839 -26.75995, -65.15823 -26.75983, -6~ ## 3 90 021 (((-65.97171 -27.06826, -65.96785 -27.07572, -6~ ## 4 90 028 (((-65.63634 -26.89105, -65.63651 -26.88802, -6~ ## 5 90 035 (((-65.51768 -27.54528, -65.51643 -27.54505, -6~ ## 6 90 042 (((-65.69166 -27.53619, -65.69142 -27.53633, -6~ ## 7 90 049 (((-65.56105 -27.61559, -65.56011 -27.61536, -6~ ## 8 90 056 (((-65.24617 -26.99868, -65.22815 -27.00267, -6~ ## 9 90 063 (((-65.43325 -26.81063, -65.43241 -26.81151, -6~ ## 10 90 070 (((-65.92069 -26.98053, -65.9161 -26.98135, -65~ ## 11 90 077 (((-65.9636 -27.40235, -65.96164 -27.40343, -65~ ## 12 90 084 (((-65.1627 -26.79866, -65.16266 -26.79888, -65~ ## 13 90 091 (((-65.35637 -27.18297, -65.35391 -27.18319, -6~ ## 14 90 098 (((-66.10172 -26.21991, -66.08361 -26.23547, -6~ ## 15 90 105 (((-65.71564 -26.51466, -65.71181 -26.51591, -6~ ## 16 90 112 (((-65.54407 -26.09089, -65.54315 -26.09155, -6~ ## 17 90 119 (((-65.25443 -26.78508, -65.25646 -26.78906, -6~ ``` --- background-image: url(https://github.com/PoliticaArgentina/data_warehouse/raw/master/hex/geoAr.png) background-position: 95% 5% background-size: 10% ## Geometrías Argentinas ### Aumentar data - [add_geo_codes()](https://politicaargentina.github.io/geoAr/index.html) ```r add_geo_codes(TUCUMAN) ## Simple feature collection with 17 features and 8 fields ## Geometry type: MULTIPOLYGON ## Dimension: XY ## Bounding box: xmin: -66.18101 ymin: -28.01579 xmax: -64.48315 ymax: -26.05908 ## Geodetic CRS: WGS 84 ## # A tibble: 17 x 9 ## codprov_censo coddepto_censo codprov coddepto nomdepto_censo name_prov ## <chr> <chr> <chr> <chr> <chr> <chr> ## 1 90 007 23 013 BURRUYACU TUCUMAN ## 2 90 014 23 012 CRUZ ALTA TUCUMAN ## 3 90 021 23 005 CHICLIGASTA TUCUMAN ## 4 90 028 23 003 FAMAILLA TUCUMAN ## 5 90 035 23 009 GRANEROS TUCUMAN ## 6 90 042 23 007 JUAN B. ALBERDI TUCUMAN ## 7 90 049 23 008 LA COCHA TUCUMAN ## 8 90 056 23 011 LEALES TUCUMAN ## 9 90 063 23 002 LULES TUCUMAN ## 10 90 070 23 004 MONTEROS TUCUMAN ## 11 90 077 23 006 RIO CHICO TUCUMAN ## 12 90 084 23 001 CAPITAL TUCUMAN ## 13 90 091 23 010 SIMOCA TUCUMAN ## 14 90 098 23 017 TAFI DEL VALLE TUCUMAN ## 15 90 105 23 016 TAFI VIEJO TUCUMAN ## 16 90 112 23 014 TRANCAS TUCUMAN ## 17 90 119 23 015 YERBA BUENA TUCUMAN ## # i 3 more variables: codprov_iso <chr>, name_iso <chr>, ## # geometry <MULTIPOLYGON [°]> ``` --- class: center, inverse, middle # Bonus ## [`{rmapshaper}`](https://github.com/ateucher/rmapshaper)