Provides functionalities to download and manage in a simple way geodata from the BDTRE database developed by the Piedmont geoportal.
What is the BDTRE (Base Dati Territoriale di Riferimento degli Enti)? From the website https://www.geoportale.piemonte.it/cms/bdtre/bdtre-2: “The Territorial Reference Database of the Bodies (BDTRE) is the geographical database of the Piedmontese territory promoted by the Piedmont Region, with the contents of a technical cartography, structured according to the - Technical rules for the definition of the content specifications of the geotopographic databases - nationally and primarily aimed at supporting the planning, governance and protection of the territory”.
From the following link: https://www.geoportale.piemonte.it/cms/bdtre/modalita-di-pubblicazione-e-fruizione it is possible to access to the different ways of using the database that in previous years of the 2021 it was possible to download by single municipality or by designing a polygonal area of limited size. Starting in 2021, they have begun to offer the possibility of downloading in an aggregate way, but still with time-consuming limitations.
The purpose of this work is to give the possibility to download the data available on the platform through the R programming language in order to reduce the time it would take through the platform and then make the data available already in an organized mode.
From the BDTRE it is possible to download different geodata for each municipality which are organized in different folders: - AMM: it contains shp of the municipal boundaries both as polygon and multiline and a punctual one for the municipal offices; - GEOFOTO: point shp with network vertices; - IDRO: contains the shp with hydrographic data; - IMM: contains multipolygonal shps of the surface of the buildings in the municipality; - IND: contains both punctual and linear shps regarding street classification and house numbers; - ORO: contains shp regarding the orography of the territory; - PERT: contains shp regarding the division of appurtenances between buildings and between public and private land; - SERV: contains shp regarding service infrastructures such as low and high voltage electricity networks; - TOPO: contains data on toponymy; - VEG: contains shp regarding agricultural, wooded and other types of natural areas. - VIAB: contains information about road infrastructure, including roads and railways;
On the basis of the selections made by the user, the final function of the program returns in a single shp for all the territory downloaded the same categories within the previously mentioned folders.
The work is also available as Jupyter notebook at the following link: https://github.com/Magio94/Download_BDTRE/blob/main/Download%20BDTRE.ipynb
You can install the package from Github (first, you need to install the devtools package):
install_github("Magio94/bdtre.download")The National Institute of Statistics (ISTAT) entrusts each municipality with an identification number, the same for the province and for the regions. The BDTRE uses these numbers at the municipal level to download the data according to the one selected.
For example for the BDTRE of the 2021: http://www.datigeo-piem-download.it/static/regp01/BDTRE2021_VECTOR/BDTRE_DATABASE_GEOTOPOGRAFICO_2021-LIMI_COMUNI_10_GAIMSDWL- YOU CAN INSERT HERE THE NUMBER YOU NEED -EPSG32632-SHP.zip
To automatically download the data for each municipality, the identification numbers must first be downloaded. ISTAT offers a permanent link in csv format that can be read directly in R. The following function downloads the table and extracts the information for the Piedmont region only.
Filter the data frame by province codes Using this fucntion the user can decide to store the municipality codes by province or for all the region. This will return a dataframe to filter the other function by downloading the selection made here from the BDTRE database.
The user can select the municipalities by province putting as input ‘001’ (Torino), ‘002’ (Vercelli), ‘003’ (Novara), ‘004’ (Cuneo), ‘005’ (Asti), ‘006’ (Alessandria), ‘096’ (Biella), ‘103’ (Verbano) or ‘All’ to save the municipality codes for all the region
Here you find the result for one selection:
library(bdtre.download)
## how use the get_municipality_codes function
Biella_province <- get_municipality_codes("096")
print(Biella_province)
#> Cod_Prov Cod_Mun Name_Mun
#> 1035 096 096001 Ailoche
#> 1036 096 096002 Andorno Micca
#> 1037 096 096003 Benna
#> 1038 096 096004 Biella
#> 1039 096 096005 Bioglio
#> 1040 096 096006 Borriana
#> 1041 096 096007 Brusnengo
#> 1042 096 096008 Callabiana
#> 1043 096 096009 Camandona
#> 1044 096 096010 Camburzano
#> 1045 096 096012 Candelo
#> 1046 096 096013 Caprile
#> 1047 096 096014 Casapinta
#> 1048 096 096015 Castelletto Cervo
#> 1049 096 096016 Cavaglià
#> 1050 096 096018 Cerrione
#> 1051 096 096019 Coggiola
#> 1052 096 096020 Cossato
#> 1053 096 096021 Crevacuore
#> 1054 096 096023 Curino
#> 1055 096 096024 Donato
#> 1056 096 096025 Dorzano
#> 1057 096 096026 Gaglianico
#> 1058 096 096027 Gifflenga
#> 1059 096 096028 Graglia
#> 1060 096 096030 Magnano
#> 1061 096 096031 Massazza
#> 1062 096 096032 Masserano
#> 1063 096 096033 Mezzana Mortigliengo
#> 1064 096 096034 Miagliano
#> 1065 096 096035 Mongrando
#> 1066 096 096037 Mottalciata
#> 1067 096 096038 Muzzano
#> 1068 096 096039 Netro
#> 1069 096 096040 Occhieppo Inferiore
#> 1070 096 096041 Occhieppo Superiore
#> 1071 096 096042 Pettinengo
#> 1072 096 096043 Piatto
#> 1073 096 096044 Piedicavallo
#> 1074 096 096046 Pollone
#> 1075 096 096047 Ponderano
#> 1076 096 096048 Portula
#> 1077 096 096049 Pralungo
#> 1078 096 096050 Pray
#> 1079 096 096053 Ronco Biellese
#> 1080 096 096054 Roppolo
#> 1081 096 096055 Rosazza
#> 1082 096 096056 Sagliano Micca
#> 1083 096 096057 Sala Biellese
#> 1084 096 096058 Salussola
#> 1085 096 096059 Sandigliano
#> 1086 096 096063 Sordevolo
#> 1087 096 096064 Sostegno
#> 1088 096 096065 Strona
#> 1089 096 096066 Tavigliano
#> 1090 096 096067 Ternengo
#> 1091 096 096068 Tollegno
#> 1092 096 096069 Torrazzo
#> 1093 096 096071 Valdengo
#> 1094 096 096072 Vallanzengo
#> 1095 096 096074 Valle San Nicolao
#> 1096 096 096075 Veglio
#> 1097 096 096076 Verrone
#> 1098 096 096077 Vigliano Biellese
#> 1099 096 096078 Villa del Bosco
#> 1100 096 096079 Villanova Biellese
#> 1101 096 096080 Viverone
#> 1102 096 096081 Zimone
#> 1103 096 096082 Zubiena
#> 1104 096 096083 Zumaglia
#> 1105 096 096085 Lessona
#> 1106 096 096086 Campiglia Cervo
#> 1107 096 096087 Quaregna Cerreto
#> 1108 096 096088 ValdilanaThe program based on the number of the municipality stored in the variable made by the function get_municipality_codes will download the corresponding data. It is possible either to use the codes of the list pre-set by province or to build your own list with the desired municipalities by making another filter.
The program is built to create subfolders starting from the position where the code is made run one. It starts from the creation of a folder called “Downloaded” and the program does not create a new folder in case you want to download other data for other provinces or for a list selected by the user since each time it checks if the same folder name exists.
It also creates an additional sub-folder for each municipality.
In the following example we are just downloading a province:
library(bdtre.download)
## download from the database the data from the desired municipalities by province
download_municipality(Biella_province)
#> [1] "The \"Downloaded\" folder already existed"
#> Warning in deparse(substitute(municipality_number), " folder already existed"):
#> NA introdotti per coercizione
#> Warning in deparse(substitute(municipality_number), " folder already existed"):
#> 'cutoff' non valido per 'deparse', si utilizza il valore predefinito
#> [1] "The Biella_province"
#> [1] "Downloaded 1 municipalities of 74"
#> [1] "Downloaded 2 municipalities of 74"
#> [1] "Downloaded 3 municipalities of 74"
#> [1] "Downloaded 4 municipalities of 74"
#> [1] "Downloaded 5 municipalities of 74"
#> [1] "Downloaded 6 municipalities of 74"
#> [1] "Downloaded 7 municipalities of 74"
#> [1] "Downloaded 8 municipalities of 74"
#> [1] "Downloaded 9 municipalities of 74"
#> [1] "Downloaded 10 municipalities of 74"
#> [1] "Downloaded 11 municipalities of 74"
#> [1] "Downloaded 12 municipalities of 74"
#> [1] "Downloaded 13 municipalities of 74"
#> [1] "Downloaded 14 municipalities of 74"
#> [1] "Downloaded 15 municipalities of 74"
#> [1] "Downloaded 16 municipalities of 74"
#> [1] "Downloaded 17 municipalities of 74"
#> [1] "Downloaded 18 municipalities of 74"
#> [1] "Downloaded 19 municipalities of 74"
#> [1] "Downloaded 20 municipalities of 74"
#> [1] "Downloaded 21 municipalities of 74"
#> [1] "Downloaded 22 municipalities of 74"
#> [1] "Downloaded 23 municipalities of 74"
#> [1] "Downloaded 24 municipalities of 74"
#> [1] "Downloaded 25 municipalities of 74"
#> [1] "Downloaded 26 municipalities of 74"
#> [1] "Downloaded 27 municipalities of 74"
#> [1] "Downloaded 28 municipalities of 74"
#> [1] "Downloaded 29 municipalities of 74"
#> [1] "Downloaded 30 municipalities of 74"
#> [1] "Downloaded 31 municipalities of 74"
#> [1] "Downloaded 32 municipalities of 74"
#> [1] "Downloaded 33 municipalities of 74"
#> [1] "Downloaded 34 municipalities of 74"
#> [1] "Downloaded 35 municipalities of 74"
#> [1] "Downloaded 36 municipalities of 74"
#> [1] "Downloaded 37 municipalities of 74"
#> [1] "Downloaded 38 municipalities of 74"
#> [1] "Downloaded 39 municipalities of 74"
#> [1] "Downloaded 40 municipalities of 74"
#> [1] "Downloaded 41 municipalities of 74"
#> [1] "Downloaded 42 municipalities of 74"
#> [1] "Downloaded 43 municipalities of 74"
#> [1] "Downloaded 44 municipalities of 74"
#> [1] "Downloaded 45 municipalities of 74"
#> [1] "Downloaded 46 municipalities of 74"
#> [1] "Downloaded 47 municipalities of 74"
#> [1] "Downloaded 48 municipalities of 74"
#> [1] "Downloaded 49 municipalities of 74"
#> [1] "Downloaded 50 municipalities of 74"
#> [1] "Downloaded 51 municipalities of 74"
#> [1] "Downloaded 52 municipalities of 74"
#> [1] "Downloaded 53 municipalities of 74"
#> [1] "Downloaded 54 municipalities of 74"
#> [1] "Downloaded 55 municipalities of 74"
#> [1] "Downloaded 56 municipalities of 74"
#> [1] "Downloaded 57 municipalities of 74"
#> [1] "Downloaded 58 municipalities of 74"
#> [1] "Downloaded 59 municipalities of 74"
#> [1] "Downloaded 60 municipalities of 74"
#> [1] "Downloaded 61 municipalities of 74"
#> [1] "Downloaded 62 municipalities of 74"
#> [1] "Downloaded 63 municipalities of 74"
#> [1] "Downloaded 64 municipalities of 74"
#> [1] "Downloaded 65 municipalities of 74"
#> [1] "Downloaded 66 municipalities of 74"
#> [1] "Downloaded 67 municipalities of 74"
#> [1] "Downloaded 68 municipalities of 74"
#> [1] "Downloaded 69 municipalities of 74"
#> [1] "Downloaded 70 municipalities of 74"
#> [1] "Downloaded 71 municipalities of 74"
#> [1] "Downloaded 72 municipalities of 74"
#> [1] "Downloaded 73 municipalities of 74"
#> [1] "Downloaded 74 municipalities of 74"The user can also using the following function download just the interested municipalities in case he/she knows the number codes by inserting them inside a vector. This function helps the user to produce a data frame with the same structure produced by the get_municipality_codes function, but just for interested municipalities and you can pass it inside the function download_municipality as we did in the example before fo the Biella province.
library(bdtre.download)
# create a vector to select the desired municipalities and pass them in the fucntion
user_list <- c('003016', '005008', '006004', '002035')
user_selection <- download_selected_mun(user_list)
print(user_selection)
#> Cod_Mun
#> 1 003016
#> 2 005008
#> 3 006004
#> 4 002035Example of how the function work by finding all the path relative to one selected shp for all the municipalities downloaded
library(bdtre.download)
selection_path('limi_comuni_piem')
#> [1] "Downloaded/Biella_province/096001/AMM/limi_comuni_piem_2021.shp"
#> [2] "Downloaded/Biella_province/096002/AMM/limi_comuni_piem_2021.shp"
#> [3] "Downloaded/Biella_province/096003/AMM/limi_comuni_piem_2021.shp"
#> [4] "Downloaded/Biella_province/096004/AMM/limi_comuni_piem_2021.shp"
#> [5] "Downloaded/Biella_province/096005/AMM/limi_comuni_piem_2021.shp"
#> [6] "Downloaded/Biella_province/096006/AMM/limi_comuni_piem_2021.shp"
#> [7] "Downloaded/Biella_province/096007/AMM/limi_comuni_piem_2021.shp"
#> [8] "Downloaded/Biella_province/096008/AMM/limi_comuni_piem_2021.shp"
#> [9] "Downloaded/Biella_province/096009/AMM/limi_comuni_piem_2021.shp"
#> [10] "Downloaded/Biella_province/096010/AMM/limi_comuni_piem_2021.shp"
#> [11] "Downloaded/Biella_province/096012/AMM/limi_comuni_piem_2021.shp"
#> [12] "Downloaded/Biella_province/096013/AMM/limi_comuni_piem_2021.shp"
#> [13] "Downloaded/Biella_province/096014/AMM/limi_comuni_piem_2021.shp"
#> [14] "Downloaded/Biella_province/096015/AMM/limi_comuni_piem_2021.shp"
#> [15] "Downloaded/Biella_province/096016/AMM/limi_comuni_piem_2021.shp"
#> [16] "Downloaded/Biella_province/096018/AMM/limi_comuni_piem_2021.shp"
#> [17] "Downloaded/Biella_province/096019/AMM/limi_comuni_piem_2021.shp"
#> [18] "Downloaded/Biella_province/096020/AMM/limi_comuni_piem_2021.shp"
#> [19] "Downloaded/Biella_province/096021/AMM/limi_comuni_piem_2021.shp"
#> [20] "Downloaded/Biella_province/096023/AMM/limi_comuni_piem_2021.shp"
#> [21] "Downloaded/Biella_province/096024/AMM/limi_comuni_piem_2021.shp"
#> [22] "Downloaded/Biella_province/096025/AMM/limi_comuni_piem_2021.shp"
#> [23] "Downloaded/Biella_province/096026/AMM/limi_comuni_piem_2021.shp"
#> [24] "Downloaded/Biella_province/096027/AMM/limi_comuni_piem_2021.shp"
#> [25] "Downloaded/Biella_province/096028/AMM/limi_comuni_piem_2021.shp"
#> [26] "Downloaded/Biella_province/096030/AMM/limi_comuni_piem_2021.shp"
#> [27] "Downloaded/Biella_province/096031/AMM/limi_comuni_piem_2021.shp"
#> [28] "Downloaded/Biella_province/096032/AMM/limi_comuni_piem_2021.shp"
#> [29] "Downloaded/Biella_province/096033/AMM/limi_comuni_piem_2021.shp"
#> [30] "Downloaded/Biella_province/096034/AMM/limi_comuni_piem_2021.shp"
#> [31] "Downloaded/Biella_province/096035/AMM/limi_comuni_piem_2021.shp"
#> [32] "Downloaded/Biella_province/096037/AMM/limi_comuni_piem_2021.shp"
#> [33] "Downloaded/Biella_province/096038/AMM/limi_comuni_piem_2021.shp"
#> [34] "Downloaded/Biella_province/096039/AMM/limi_comuni_piem_2021.shp"
#> [35] "Downloaded/Biella_province/096040/AMM/limi_comuni_piem_2021.shp"
#> [36] "Downloaded/Biella_province/096041/AMM/limi_comuni_piem_2021.shp"
#> [37] "Downloaded/Biella_province/096042/AMM/limi_comuni_piem_2021.shp"
#> [38] "Downloaded/Biella_province/096043/AMM/limi_comuni_piem_2021.shp"
#> [39] "Downloaded/Biella_province/096044/AMM/limi_comuni_piem_2021.shp"
#> [40] "Downloaded/Biella_province/096046/AMM/limi_comuni_piem_2021.shp"
#> [41] "Downloaded/Biella_province/096047/AMM/limi_comuni_piem_2021.shp"
#> [42] "Downloaded/Biella_province/096048/AMM/limi_comuni_piem_2021.shp"
#> [43] "Downloaded/Biella_province/096049/AMM/limi_comuni_piem_2021.shp"
#> [44] "Downloaded/Biella_province/096050/AMM/limi_comuni_piem_2021.shp"
#> [45] "Downloaded/Biella_province/096053/AMM/limi_comuni_piem_2021.shp"
#> [46] "Downloaded/Biella_province/096054/AMM/limi_comuni_piem_2021.shp"
#> [47] "Downloaded/Biella_province/096055/AMM/limi_comuni_piem_2021.shp"
#> [48] "Downloaded/Biella_province/096056/AMM/limi_comuni_piem_2021.shp"
#> [49] "Downloaded/Biella_province/096057/AMM/limi_comuni_piem_2021.shp"
#> [50] "Downloaded/Biella_province/096058/AMM/limi_comuni_piem_2021.shp"
#> [51] "Downloaded/Biella_province/096059/AMM/limi_comuni_piem_2021.shp"
#> [52] "Downloaded/Biella_province/096063/AMM/limi_comuni_piem_2021.shp"
#> [53] "Downloaded/Biella_province/096064/AMM/limi_comuni_piem_2021.shp"
#> [54] "Downloaded/Biella_province/096065/AMM/limi_comuni_piem_2021.shp"
#> [55] "Downloaded/Biella_province/096066/AMM/limi_comuni_piem_2021.shp"
#> [56] "Downloaded/Biella_province/096067/AMM/limi_comuni_piem_2021.shp"
#> [57] "Downloaded/Biella_province/096068/AMM/limi_comuni_piem_2021.shp"
#> [58] "Downloaded/Biella_province/096069/AMM/limi_comuni_piem_2021.shp"
#> [59] "Downloaded/Biella_province/096071/AMM/limi_comuni_piem_2021.shp"
#> [60] "Downloaded/Biella_province/096072/AMM/limi_comuni_piem_2021.shp"
#> [61] "Downloaded/Biella_province/096074/AMM/limi_comuni_piem_2021.shp"
#> [62] "Downloaded/Biella_province/096075/AMM/limi_comuni_piem_2021.shp"
#> [63] "Downloaded/Biella_province/096076/AMM/limi_comuni_piem_2021.shp"
#> [64] "Downloaded/Biella_province/096077/AMM/limi_comuni_piem_2021.shp"
#> [65] "Downloaded/Biella_province/096078/AMM/limi_comuni_piem_2021.shp"
#> [66] "Downloaded/Biella_province/096079/AMM/limi_comuni_piem_2021.shp"
#> [67] "Downloaded/Biella_province/096080/AMM/limi_comuni_piem_2021.shp"
#> [68] "Downloaded/Biella_province/096081/AMM/limi_comuni_piem_2021.shp"
#> [69] "Downloaded/Biella_province/096082/AMM/limi_comuni_piem_2021.shp"
#> [70] "Downloaded/Biella_province/096083/AMM/limi_comuni_piem_2021.shp"
#> [71] "Downloaded/Biella_province/096085/AMM/limi_comuni_piem_2021.shp"
#> [72] "Downloaded/Biella_province/096086/AMM/limi_comuni_piem_2021.shp"
#> [73] "Downloaded/Biella_province/096087/AMM/limi_comuni_piem_2021.shp"
#> [74] "Downloaded/Biella_province/096088/AMM/limi_comuni_piem_2021.shp"
#> [75] "Downloaded/user_selection/001001/AMM/limi_comuni_piem_2021.shp"The user can insert the argument inside the merging_shp between the different choices in the list:
selection_list <- c(‘lim_com’, ‘limi_comuni_piem’, ‘sed_amm’, ‘ab_cda_vert’, ‘el_idr_vert’, ‘nd_idr’, ‘af_acq’, ‘dre_sup’, ‘ghi_nv’, ‘invaso_vert’, ‘sp_acq’, ‘aatt’, ‘attr_sp’, ‘cr_edf’, ‘cs_edi’, ‘edi_min’, ‘ele_cp’, ‘un_vol’, ‘argine’, ‘diga’, ‘edifc’, ‘galler’, ‘man_tr’, ‘mn_arr’, ‘mn_int’, ‘mn_ind’, ‘mn_mau’, ‘mu_sos’, ‘ponte’, ‘tralic’, ‘acc_int’, ‘acc_pc_civico_tp_str’, ‘es_amm’, ‘tp_str’, ‘cv_liv_class’, ‘f_nter’, ‘pt_quo’, ‘a_tras’, ‘alveo’, ‘alveo_a’, ‘pe_uins’, ‘cv_aes’, ‘cv_dis’, ‘loc_sg’, ‘scr_cr’, ‘ar_vrd’, ‘bosco’, ‘cl_agr’, ‘for_pc’, ‘ps_inc’, ‘a_pveg’, ‘albero’, ‘fil_al’, ‘for_pc’, ‘ac_vei’, ‘ar_vms’, ‘el_str_tp_str’, ‘el_vms’, ‘gz_str’, ‘gz_vms’, ‘iz_str’, ‘tr_str’, ‘ac_cic’, ‘ac_ped’, ‘el_fer’, ‘gz_fer’, ‘sd_fer’, ‘nd_ele’, ‘tr_ele’, ‘v_rete’)
In the example streets shp was chosen:
library(bdtre.download)
## Example of merging one category from the downloaded data
nc_merge <- merging_shp('el_str_tp_str')The following plot show the result of the merging made by the previous function.
###
Calculate indicators for each municipalities¶
The function is an example of what can be achieved with the calculated data. In this case, the function is used to calculate the urbanization index based on the municipalities of interest. To obtain these data, a list was first created from which the program reads the shp files that indicate the urbanization elements for each municipality of interest.
Once the total urbanized area has been added, the percentage of urbanization on the total surface is calculated. The latter is obtained from the polygonal shp with the boundaries of the municipality.
library(bdtre.download)
## basic example code
data_frame_data <- percent_urbanized(Biella_province)
#> [1] "The percent of urbanized area for Ailoche is 1.70657466667157%"
#> [1] "The percent of urbanized area for Andorno Micca is 6.12606618398486%"
#> [1] "The percent of urbanized area for Benna is 7.66995922110783%"
#> [1] "The percent of urbanized area for Biella is 19.4253223170418%"
#> [1] "The percent of urbanized area for Bioglio is 2.72217651623219%"
#> [1] "The percent of urbanized area for Borriana is 6.60616979081811%"
#> [1] "The percent of urbanized area for Brusnengo is 8.5056452590561%"
#> [1] "The percent of urbanized area for Callabiana is 2.66182459097635%"
#> [1] "The percent of urbanized area for Camandona is 2.92921951889391%"
#> [1] "The percent of urbanized area for Camburzano is 9.56130382748247%"
#> [1] "The percent of urbanized area for Candelo is 12.2347839000446%"
#> [1] "The percent of urbanized area for Caprile is 1.4807446816855%"
#> [1] "The percent of urbanized area for Casapinta is 4.59017430548949%"
#> [1] "The percent of urbanized area for Castelletto Cervo is 5.16420971848516%"
#> [1] "The percent of urbanized area for Cavaglià is 13.5999620040174%"
#> [1] "The percent of urbanized area for Cerrione is 6.98688053477176%"
#> [1] "The percent of urbanized area for Coggiola is 2.59172466937795%"
#> [1] "The percent of urbanized area for Cossato is 14.7508235730712%"
#> [1] "The percent of urbanized area for Crevacuore is 6.3875926587011%"
#> [1] "The percent of urbanized area for Curino is 2.28120265032899%"
#> [1] "The percent of urbanized area for Donato is 4.37279893188028%"
#> [1] "The percent of urbanized area for Dorzano is 8.79919251656597%"
#> [1] "The percent of urbanized area for Gaglianico is 33.3333576739764%"
#> [1] "The percent of urbanized area for Gifflenga is 7.93233479815402%"
#> [1] "The percent of urbanized area for Graglia is 3.82683672515582%"
#> [1] "The percent of urbanized area for Magnano is 9.08999467374012%"
#> [1] "The percent of urbanized area for Massazza is 8.48038528284979%"
#> [1] "The percent of urbanized area for Masserano is 6.47343069420142%"
#> [1] "The percent of urbanized area for Mezzana Mortigliengo is 5.3570877194403%"
#> [1] "The percent of urbanized area for Miagliano is 21.537315759224%"
#> [1] "The percent of urbanized area for Mongrando is 8.46383695919024%"
#> [1] "The percent of urbanized area for Mottalciata is 6.44349367204103%"
#> [1] "The percent of urbanized area for Muzzano is 4.52234704324447%"
#> [1] "The percent of urbanized area for Netro is 4.68506896771995%"
#> [1] "The percent of urbanized area for Occhieppo Inferiore is 21.6426331147748%"
#> [1] "The percent of urbanized area for Occhieppo Superiore is 14.2136302734596%"
#> [1] "The percent of urbanized area for Pettinengo is 3.51676940048166%"
#> [1] "The percent of urbanized area for Piatto is 6.0608777755172%"
#> [1] "The percent of urbanized area for Piedicavallo is 0.964422017022706%"
#> [1] "The percent of urbanized area for Pollone is 4.43620583932738%"
#> [1] "The percent of urbanized area for Ponderano is 18.1418498283302%"
#> [1] "The percent of urbanized area for Portula is 3.80141770309145%"
#> [1] "The percent of urbanized area for Pralungo is 7.96150156487356%"
#> [1] "The percent of urbanized area for Pray is 9.27882387045533%"
#> [1] "The percent of urbanized area for Ronco Biellese is 10.4561156557266%"
#> [1] "The percent of urbanized area for Roppolo is 5.20788260154426%"
#> [1] "The percent of urbanized area for Rosazza is 1.4769718045374%"
#> [1] "The percent of urbanized area for Sagliano Micca is 3.8144334326504%"
#> [1] "The percent of urbanized area for Sala Biellese is 4.05875479400834%"
#> [1] "The percent of urbanized area for Salussola is 4.41993440119389%"
#> [1] "The percent of urbanized area for Sandigliano is 14.8805072948843%"
#> [1] "The percent of urbanized area for Sordevolo is 3.93059244898629%"
#> [1] "The percent of urbanized area for Sostegno is 2.03944675624581%"
#> [1] "The percent of urbanized area for Strona is 10.2524793831257%"
#> [1] "The percent of urbanized area for Tavigliano is 2.90201007818445%"
#> [1] "The percent of urbanized area for Ternengo is 5.09070489583609%"
#> [1] "The percent of urbanized area for Tollegno is 17.0479890064246%"
#> [1] "The percent of urbanized area for Torrazzo is 3.44017689666682%"
#> [1] "The percent of urbanized area for Valdengo is 14.6426165255179%"
#> [1] "The percent of urbanized area for Vallanzengo is 1.7363070243213%"
#> [1] "The percent of urbanized area for Valle San Nicolao is 2.84678923055367%"
#> [1] "The percent of urbanized area for Veglio is 4.05470871849549%"
#> [1] "The percent of urbanized area for Verrone is 17.2140461081047%"
#> [1] "The percent of urbanized area for Vigliano Biellese is 31.2799928856476%"
#> [1] "The percent of urbanized area for Villa del Bosco is 4.71563973835272%"
#> [1] "The percent of urbanized area for Villanova Biellese is 3.24830581382082%"
#> [1] "The percent of urbanized area for Viverone is 6.34266400964284%"
#> [1] "The percent of urbanized area for Zimone is 7.07203684328434%"
#> [1] "The percent of urbanized area for Zubiena is 4.34031515482173%"
#> [1] "The percent of urbanized area for Zumaglia is 9.12745993921803%"
#> [1] "The percent of urbanized area for Lessona is 8.73925179708345%"
#> [1] "The percent of urbanized area for Campiglia Cervo is 2.25879975075999%"
#> [1] "The percent of urbanized area for Quaregna Cerreto is 13.8873288992232%"
#> [1] "The percent of urbanized area for Valdilana is 6.15155334390232%"The user can also perform the same calculation for specific municipalities already downloaded, but as input, there must be a variable composed in the same way as the dataframe obtained by the get_municipality_codes function. To do this, you need to filter the list obtained from the same function for the istat code of the municipalities on which you want to make the calculation. Below is an example of how to do it:
library(bdtre.download)
# get the data fram of the province where the municiplaity is
mun_code <- get_municipality_codes('001')
# filter just the municipality
selected_mun_urban <- mun_code[which(mun_code$Cod_Mun == '001001'), ]
# download the desired municipality
user_selection <- download_selected_mun("001001")
download_municipality(user_selection)
#> [1] "The \"Downloaded\" folder already existed"
#> Warning in deparse(substitute(municipality_number), " folder already existed"):
#> NA introdotti per coercizione
#> Warning in deparse(substitute(municipality_number), " folder already existed"):
#> 'cutoff' non valido per 'deparse', si utilizza il valore predefinito
#> [1] "The user_selection"
#> [1] "Downloaded 1 municipalities of 1"
# fit the variable inside the percent_urbanized function
data_frame_data2 <- percent_urbanized(selected_mun_urban)
#> [1] "The percent of urbanized area for Agliè is 8.56397139937146%"At the end in the following plot it is possible to see an example of what can be produced with the percent_urbanized function. The map shows the level of urbanization for each municipality of the chosen province.
#>
#> Caricamento pacchetto: 'dplyr'
#> I seguenti oggetti sono mascherati da 'package:stats':
#>
#> filter, lag
#> I seguenti oggetti sono mascherati da 'package:base':
#>
#> intersect, setdiff, setequal, union
