by Yannick Tanguy at August 03, 2023 01:28 PM
O módulo de Autenticação por Chave do GeoServer permite um protocolo de autenticação muito simples, projetado para clientes OGC que não podem lidar com nenhum tipo de protocolo de segurança, nem mesmo a autenticação básica HTTP.
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Um exemplo de solicitação autenticada é semelhante a:
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Onde authkey=ef18d7e7-963b-470f-9230-c7f9de166888 está associado a um usuário específico. Quando o parâmetro authkey é fornecido, os backlinks também contêm a chave de autenticação, permitindo que qualquer cliente compatível acesse recursos protegidos.
Na sequencia, os passos para você instalar e configurar o módulo de segurança no GeoServer:
1. Pré-requisitos para a instalação
2. Instalação
3. Configuração
Agora que o plugin já está instalado, você deve logar na interface web do GeoServer e ir no menu Security e clicar em Authentication. O GeoServer irá lhe apresentar uma tela com algumas opções, procure por Authentication Filters e clique em Add New.
CSDN下载 - VP Suite 5.0（ Visual Paradigm for UML 8.0 ...:2021-3-30 · VP Suite 5.0（ Visual Paradigm for UML 8.0 ）注册码 破解更多下载资源、学习资料请访问CSDN下载频道. vp例程和教程 包含vp教程和一些有用的例子，其中一些是官方的，比较有价值，对一些初学者还是有不少的帮助的。
O arquivo 极速vpv官网 fica localizado em: $GEOSERVER_DATA_DIR/security/usergroup/default/authkeys.propeties
Um exemplo desse arquivo seria:
Pra finalizar, você precisa substituir as opções onde tem Basic Authentication por Authentication Key dentro das opções do FilterChain, e deixar como na figura abaixo:
Verifique quais as opções que você quer a autenticação por chave. Eu por exemplo não alterei a opção do Rest.
Agora basta você pegar as chaves geradas no arquivo authkeys.properties, e passar por parâmetro nas suas requisições ao GeoServer, conforme o exemplo abaixo:
http://localhost:8080/geoserver/topp/wms?service=WMS&version=1.3.0&request=GetCapabilities&authkey=ef18d7e7-963b-470f-9230-c7f9de166888
Fonte: GeoServer
by Fernando Quadro at August 03, 2023 01:14 PM
August 03, 2023 09:00 AM
July 29, 2023 12:01 AM
In this post I’ll use the r.series.diversity addon (Breugel 2016) for GRASS GIS (GRASS Development Team vp安卓下载) to compute the tree species diversity distribution patterns in the contiguous USA, based on tree distribution data from Wilson et al. (2013). With the addon, you can compute a number of diversity indices, including the Renyi entropy index and a number of specialized cases of the Renyi enthropy, viz.the species richness, the Shannon index, the Shannon based effective number of species (ENS), the Simpson index (inverse and gini variants), and Pielou’s eveness (Legendre and Legendre 1998). Install the addon first (see here how).
Wilson et al. (2013) published raster maps with the estimated live tree basal area (square feet/acre) for 324 tree species in the United States. The raster maps, at a resolution of 250 meter and representing the time period 2000-2009, are based on MODIS imagery, raster data describing relevant environmental parameters, and field plot data of tree species basal area. The methods are described in (vp下载安卓) and Wilson et al. (2013). We’ll use the basal area as proxy for the species abundances.
You can download the data from this website. There are three zip files, each containing approximately 80 raster layers (img format), one per species. The map projection is Albers Conical Equal Area (datum NAD83). First step is to download the data and unzip the rasters from the three zip files in one folder.
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Figure 1: Create new location
Figure 2: Define database and location name
Figure 3: Choose method to determine crs
Figure 4: Choose layer to be used to set teh crs
In the next window you are presented with a summary of the new location you are about to create. If it all looks good, click finish.
Now you are asked if you want to import the data layer that you used to create the location. If you select yes, the data layer will be imported in the PERMANENT mapset. The default region extent and resolution will be set based on the imported data layer. Selected ‘no’. You’ll import the layer together with the others in one go in the next steps.
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Figure 5: Set name for new mapset
After creating the new location and mapset, you can continue with importing the data layers in your newly created mapset. The files have an .img extension. We can check with the function gdalinfo what kind of raster file this is.
Check the raster file type
Run the following on the command line.
# Go to the directory with your raster files
cd Desktop/treesUSA
# Get information about the layer
gdalinfo s10.imgThis will give you a lot of information, but what we are after is the file type. You can find this near the top of the output; it is a HFA/Erdas Imagine Image (.img).
Now that you know the type of the raster layers, you can import them using the r.import function.
Importing all raster layers in a folder
You can use the function 坚果ⅴpn下载 to import all the layers in a folder in one go. Go to Menu > File > Import raster data > Simplified raster import with reprojection. Don’t worry about the reprojection bit. The coordinate reference system (crs) of the mapset is equal to that of the raster layers (obviously, we used one of the raster layer to define the crs of the mapset), so no reprojection is carried out.
Figure 6: Import the data
See the numbers in the image above: (1) Select as source type Directory and (2) select the directory with the raster layers. (3) Select Erdas Imagine Images (.img) as format and make sure the extension is set to img. After selecting the directory and raster format, a list will appear with all raster layers (4). Select all layers, and deselect Flash Player官方下载-Flash中国官网:Flash Player - 一款轻量级浏览器插件,让你在网页上享受更广泛的多媒体体验,更新、更安全、正版Flash Player下载尽在Flash中国官网 (5). Optionally, go to 极速vp哪里下载 (6) to change some settings (e.g., if you have some RAM to spare, increase the maximum memory to be used).
Before we compute the diversity indici, we need to set the computational region and define a mask. The region defines the extent and resolution that will be used for all raster computations. It can be set with the g.region function.
Set the region
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Figure 7: Set computation region
Alternatively, you can use the g.region function on the command line or console.
g.region raster=s10The tree distribution data is for the continental part of the USA, excluding Alaska. So we want to mask out all other areas. To be able to do so, first download the USA boundaries, e.g., from the GADM website and import the data. The vector layer can subsequently be used to define the mask.
Set the mask
To download a geopackage with the vector data, use this link. After download, extract the geopackage. Note that the the data is in latlon (wgs84). Easiest is to use the v.import function, which reprojects the data on the fly. Make sure to select the layer with the national boundary gadm36_USA_0.
Figure 8: Import vector layer with USA boundaries
You can also run this from the command line or console.
v.import input=gadm36_USA_gpkg/gadm36_USA.gpkg layer=gadm36_USA_0Next, we can create a mask with the 蚂蚁vp(永久免费) function. This function essentially converts the vector layer to a raster layer, with the special name MASK. You can display this layer like any other layer.
# Set the mask
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Now we are finally ready to compute the tree species diversity, using the r.series.diversity addon for GRASS GIS. This can be done in two steps on the command line.
Get a list of input layers
You can create a list with the names of the raster layers using the 免费的稳定vp function. The names of our raster layers all start with a s. The following command will create a list with all names, and assign these to the variable MAPS.
# List all raster layers with species
MAPS=`g.list type=raster pattern=s* separator=comma mapset=trees`Use this as input for the r.series.diversity function.
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The flags indicate which diversity indici to calculate. In the code below, these are (r) Renyi enthropy index, (s) the richness index, (h), the shannon index, (p) the reversed Simpson index, (g) the Gini-Simpson index,(e) the Pielou’s evenness index, and (n) the Shannon effective number of species.
# Compute the diversity layers
r.series.diversity -s -h -p -g -e input=$MAPS output=TreeDiversityNote that with this dataset, the computation will take a really long time. Long enough for you to forget about it for the rest of the day, hopefully to have it finished next morning. So yes, the code definitely needs some optimization (any suggestion as to how to accomplish this are most welcome).
The output are maps with patterns of tree diversity across contiguous United States. In Figure 9 the maps with the species richness and the Shannon-wiener diversity index are shown. The maps show that in the mideastern states like West Virginia, Kentucky and Tennessee, tree diversity is relatively high, while tree diversity in the states on the west coast is clearly lower.
Figure 9: Tree diversity patterns across the USA
The observed patterns correspond fairly well with the map of the tree diversity by Heath et al. (2015). This is not surprising. Both the map by Heath et al. (vqn下载) and the species distribution maps by Wilson et al. (2013) are based on the Forest Inventory and Analysis (FIA) field plot data from the U.S. Forest Service.
The tree diversity map by Jenkins et al. (2015) shows a different pattern, with a clear diversity hotspot in the southeastern United States. The use of different sources of information (and underlying methodologies and assumptions) might be one reason for the differences. Jenkins et al. used the range maps of tree species by Little (1971), digitized by the US Geological Survey (1999).
In addition, the diversity map by Jenkins et al. is based on the range maps of 641 species, out of the more than 700 different native and naturalized tree species in the United States (Little 1979). The Wilson et al. (2013) dataset contains a much smaller subset of 324 species. If these are e.g., the most common species, this could result in an underestimation of the species richness in regions with more rare or endemic species. And indeed, these maps show that the southeastern United States has a high number of endemic tree species. Another point to reiterate is that the basal area was used as proxy indicator for tree abundance.
I have uploaded the data to Open Science Framework (OSF) data sharing site from the Center for Open Science. If you use the data, please cite as follows: Van Breugel, P. (2023, August 3). Tree diversity distribution patterns in contiguous USA. http://doi.org/10.17605/OSF.IO/UC6DA.
Breugel, Paulo van. 2016. “R.series.diversity - a GRASS GIS Addon to Compute Diversity Indici over Input Layers.” http://trac.osgeo.org/grass/browser/grass-addons/grass7/raster/r.series.diversity.
GRASS Development Team. 2023. Geographic Resources Analysis Support System (Grass Gis) Software. USA: Open Source Geospatial Foundation. http://grass.osgeo.org.
Heath, Linda S., Sarah M. Anderson, Marla R. Emery, Jeffrey A. Hicke, Jeremy Littell, Alan Lucier, Jeffrey G. Masek, et al. 2015. “Indicators of Climate Impacts for Forests: Recommendations for the US National Climate Assessment Indicators System.” NRS-GTR-155. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. vp链接 亲测好用下载-CSDN论坛:2021-5-31 · atom中文破解包 <em>下载</em>后解压直接放在C盘用户目录底下的.atom下的package文件夹下，重启就OK VP Suite 5.0（ Visual Paradigm for UML ....
Jenkins, Clinton N., Kyle S. Van Houtan, Stuart L. Pimm, and Joseph O. Sexton. 2015. “US Protected Lands Mismatch Biodiversity Priorities.” Proceedings of the National Academy of Sciences 112 (16): 5081–6. http://doi.org/10.1073/pnas.1418034112.
Legendre, P., and L. Legendre. 1998. Numerical Ecology. Second English edition. Developments in Environmental Modelling 20. Amsterdam: Elsevier.
Little, Elbert L. Jr. 1971. Atlas of United States Trees: Volume 1: Conifers and Important Hardwoods. First Edition edition. United States Government Printing Office,, Washington:
Little, Elbert Luther. 1979. Checklist of United States Trees (Native and Naturalized). D.C. : Forest Service, U.S. Department of Agriculture.
US Geological Survey. 1999. “Digital Representation of Tree Species Range Maps from "Atlas of United States Trees" by Elbert L. Little, Jr.” Geosciences; Environmental Change Science Center, USGS. http://esp.cr.usgs.gov/data/atlas/little/.
Wilson, Barry Tyler, Andrew J Lister, R I Riemann, Douglas M Griffith, and M Douglas. 2013. “Live Tree Species Basal Area of the Contiguous United States (2000-2009).” Newtown Square, PA: USDA Forest Service, Rocky Mountain Research Station. http://dx.doi.org/10.2737/RDS-2013-0013.
Wilson, B. Tyler, Andrew J. Lister, and Rachel I. Riemann. 2012. “A Nearest-Neighbor Imputation Approach to Mapping Tree Species over Large Areas Using Forest Inventory Plots and Moderate Resolution Raster Data.” Forest Ecology and Management 271 (May): 182–98. VP（副总裁）_百度百科:2021-5-7 · Vice President的英文缩写，在外伋中非常流行，比如财务VP，是直接向总裁汇报的副手，权利非常大。一般的话都是因为总裁CEO无暇顾及琐碎或者需要有更为宏观的去考虑公司的事情的话就会考虑配一个或数个VP。.
July 29, 2023 12:00 AM
by Jackie Ng (noreply@blogger.com) at July 28, 2023 02:33 PM
Prezados leitores,
O post de hoje falará um pouco sobre automatização de processos no GeoServer. Para isso eu irei utilizar um servidor linux (CentOS 8), a API Rest do GeoServer, e scripts em bash.
Essa demanda apareceu pois no momento estou prestando consultoria para uma startup ajudando eles a escalarem os mapas. Além de alterar o paradigma que eles estavam utilizando (arquivos KML lidos pela API JavaScript do Google Maps), e implantar o GeoServer (e por consequência os padrões OGC), eu também organizei/configurei todos os dados dentro do GeoServer.
Nessa etapa, me deparei com uma camada com precisão de 5m. Só pra dar uma dimensão de tamanho, essa camada apenas para o estado do Rio de Janeiro tem 5 GB. Não teve como fazê-la por Estado, ela teve que ser dividida por munícipio, e ao final ser criado um layer group pra então poder realizar o agrupamento por Estado novamente. Vou apresentar pra vocês como resolvi o problema.
1. Configurar Store e Layers
Como eu estou trabalhando com shapefiles, eu decidi criar um store do tipo “Directory of spatial files (shapefiles)”. Antes de executar o comando para criar o Store no GeoServer eu coloquei os shapes dentro da pasta de dados do GeoServer.
curl -v -u admin:geoserver -XPUT -H "Content-type: text/plain" -d "file:///var/lib/geoserver-data/data/riodejaneiro/" "http://localhost:8080/geoserver/rest/workspaces/topp/datastores/riodejaneiro/external.shp?configure=all"
Ao executar o comando acima, o GeoServer irá criar o seu “Directory of spatial files”, e como eu utilizei ao final da requisição o parâmetro “configure=all” ele irá criar as camadas automaticamente a partir de cada shapefile contido na minha pasta riodejaneiro.
2. Alterar os estilos
Ao criar as camadas, o GeoServer aplicou o estilo padrão para elas. Porém, eu criei um estilo que será aplicado a todas as camadas (o mesmo estilo). Dessa forma, eu preciso passar por cada camada e alterar o estilo. Fazer isso “na mão” seria muito trabalhoso, dessa forma o comando abaixo (que precisa ser executado dentro da pasta /var/lib/geoserver-data/data/riodejaneiro/) vai fazer o trabalho “sujo” pra mim.
for filename in *.shp; do
curl -v -u admin:geoserver -XPUT -H "Content-type: text/xml" -d "<layer><defaultStyle><name>estilo_errejota</name></defaultStyle></layer>" http://localhost:8080/geoserver/rest/layers/topp:"${filename%.shp}"
done
O comando acima, faz um iteração, e pra cada camada ele aplica o estilo “estilo_errejota”.
3. Criar o Layer Group
Como mencionei no início do post, eu precisei dividir a camada por município, e agora, que elas já estão todas criadas e com os estilos aplicados corretamente, eu preciso agrupá-las para apresentar no WebGIS. Pra poder criar um Layer Group via Rest, eu precivo enviar um arquivo XML com o nome das camadas e o estilo de cada camada, conforme o modelo abaixo:
<layerGroup> <name>nyc</name> <layers> <layer>roads</layer> <layer>parks</layer> <layer>buildings</layer> </layers> <styles> <style>roads_style</style> <style>polygon</style> <style>polygon</style> </styles> </layerGroup>
Pra gerar esse XML e enviar pro GeoServer via Rest, eu criei o seguinte script em bash:
# script para adicionar layer group no GeoServer
# Author: Fernando Quadro
restapi=http://localhost:8080/geoserver/rest
login=admin:geoserver
workspace=topp
layer_group=errejota
dir=/var/lib/geoserver-data/data/riodejaneiro/layer_group.xml
echo "<layerGroup>" > $dir
echo "<name>$layer_group</name>" >> $dir
echo "<layers>" >> $dir
for filename in *.shp; do
echo "<layer>$workspace:${filename%.shp} </layer>" >> $dir
done
echo "</layers>" >> $dir
echo "<styles>" >> $dir
for filename in *.shp; do
echo "<style>estilo_errejota</style>" >> $dir
done
echo "</styles>" >> $dir
echo "</layerGroup>" >> $dir
curl -v -u admin:geoserver -XPOST -d @layer_group.xml -H "Content-type: text/xml" $restapi/layergroups
Após a execução do script acima, que também deve estar dentro da pasta onde estão os shapefiles, você terá então seu layer group criado automaticamente. Lembre-se de ao final do processo retirar o script e o arquivo XML da pasta onde estão os shapes.
by Fernando Quadro at July 27, 2023 11:00 AM
Neste podcast: No TecnoloGEO 16 traz até você a continuação do bate-papo iniciado no episódio 12 onde fizemos uma discussão sobre conhecimento essenciais que todo Geoprocesseiro deve saber. Nesse episódio Narcélio de Sá apresenta mais alguns conhecimentos que todo geoprocesseiro que se preze tem que saber para lidar com as rotinas do dia-a-dia no mundo das geotecnologias.
O tecnoloGEO é encabeçado por Murilo Cardoso (@niilistativo) , Narcélio de Sá (@narceliodesa) e Luiz Sadeck (极光vpm破解无限版), o projeto tem a pretensão de ser semanal e contar sempre com convidados, que sejam relevantes ao assunto em pauta da vez, pra bater aquele bate papo descontraído e informativo sobre as Geotecnologias.
Deixe seu comentário e participe!
Entre em contato com o TecnoloGEO:
Equipe do TecnoloGEO:
Luiz Sadeck
Murilo Cardoso
Narcélio de Sá
The post TecnoloGEO 16 – Conhecimentos que todo geoprocesseiro deve saber II appeared first on Narcélio de Sá.
by Narcélio de Sá at July 27, 2023 10:00 AM
To explore travel patterns like origin-destination relationships, we need to identify individual trips with their start/end locations and trajectories between them. Extracting these trajectories from large datasets can be challenging, particularly if the records of individual moving objects don’t fit into memory anymore and if the spatial and temporal extent varies widely (as is the case with ship data, where individual vessel journeys can take weeks while crossing multiple oceans).
This is part 2 of “Exploring massive movement datasets”.
Roughly speaking, trip trajectories can be generated by first connecting consecutive records into continuous tracks and then splitting them at stops. This general approach applies to many different movement datasets. However, the processing details (e.g. stop detection parameters) and preprocessing steps (e.g. removing outliers) vary depending on input dataset characteristics.
For example, in our paper [1], we extracted vessel journeys from AIS data which meant that we also had to account for observation gaps when ships leave the observable (usually coastal) areas. In the accompanying 10-minute talk, I went through a 4-step trajectory exploration workflow for assessing our dataset’s potential for travel time prediction:
Click to watch the recorded talk
Like the vp菠菜网|vp菠菜平台|vp菠菜app下载:500电竞【www.500dj500.vip】最权威的电竞投注平台（下载app送28元），本站提供LOL电竞竞猜,CS:GO电竞竞猜,反恐精英赛事竞猜,魔兽争霸赛事竞猜等业务 欢迎进入苏州成协物流有限公司官网！主营服务吴江物流,vp菠菜, ..., our trajectory aggregation approach is implemented in Spark. The challenges are both the massive amounts of trajectory data and the fact that operations only produce correct results if applied to a complete and chronologically sorted set of location records.This is challenging because Spark core libraries (version 2.4.5 at the time) are mostly geared towards dealing with unsorted data. This means that, when using high-level Spark core functionality incorrectly, an aggregator needs to collect and sort the entire track in the main memory of a single processing node. Consequently, when dealing with large datasets, out-of-memory errors are frequently encountered.
To solve this challenge, our implementation is based on the Secondary Sort pattern and on Spark’s aggregator concept. Secondary Sort takes care to first group records by a key (e.g. the moving object id), and only in the second step, when iterating over the records of a group, the records are sorted (e.g. chronologically). The resulting iterator can be used by an aggregator that implements the logic required to build trajectories based on gaps and stops detected in the dataset.
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[1] Graser, A., Dragaschnig, M., Widhalm, P., Koller, H., & Brändle, N. (2023). Exploratory Trajectory Analysis for Massive Historical AIS Datasets. In: 21st IEEE International Conference on Mobile Data Management (MDM) 2023. doi:10.1109/MDM48529.2023.00059
This post is part of a series. Read more about movement data in GIS.
by underdark at July 26, 2023 03:58 PM
The vp下载ios makes it easy to create models by chaining together different operations/algorithms available in the vp安卓下载. But what if a function is not available in the toolbox? In that case you can write your own script and add this as a new function to the toolbox.
For example, I want to create a model to download zipped ascii raster layers, unzip them, convert them to geotif files (if not already) and store them on my computer. The first step, downloading the data, can be automated using the vp下载苹果 in the toolbox (Figure 1).
Figure 1: The QGIS model to download raster layers.
For the next step, unzipping the files, no function is available in the toolbox. So apart from doing this part manually, the option is to write a small script to extract raster layers from a zip file. The tricky part is to write a function that can be used in the QGIS toolbox. This means amongst others that the function’s input parameters need to be defined with the initAlgorithm function and the addParameter function. This is illustrated with the code snippet below, which defines the input and output parameters for the unzip functions.
Code
def initAlgorithm(self, config=None):
self.addParameter(QgsProcessingParameterFile(
'INPUT',
'INPUT',
optional=True,
behavior=QgsProcessingParameterFile.File,
fileFilter='All files (*.*)',
defaultValue=None))
self.addParameter(QgsProcessingParameterFile(
'OUTPUT',
'OutputFolder',
optional=True,
behavior=QgsProcessingParameterFile.Folder,
fileFilter='All files (*.*)',
defaultValue=None))With the input parameters defined, the code snippet below gets a list of the files names in the zipfile, selects the raster layers (based on their file extension) and extracts them.
Code
# Output folder
out_dir = parameters['OUTPUT']
# Input zip file
yzf = parameters['INPUT']
# Temporary download folder
temp_dir = tempfile.mkdtemp()
with zipfile.ZipFile(yzf) as zf:
# Get list with file names in zipfile
files = zf.namelist()
# Get list with all raster layers in zip file (ascii and tif rasters)
lrf = ('.asc', '.tif', '.bil', '.dwg', '.hdr')
filesasc = [i for i in files if i.endswith(lrf)]
# Extract the raster layers to the user defined folder
for asciifile in filesasc:
file_path = os.path.join(temp_dir, asciifile)
f = open(file_path, 'wb')
f.write(zf.read(asciifile))
f.close()You can check out the complete script here. Besides the code snippets above, it contains a header section, it loads the required libraries, and it contains some extra (html formatted) information that will be shown as help when running the script from the toolbox. After loading the script in the QGIS toolbox, it can be used like any other function.
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The translate function can be used to convert raster layers in another format to geotifs. My initial idea was to import the above script in the toolbox, and build a model in which the output of this particular function, the downloaded and unzipped raster file, would be used as input in the translate function. But the downloaded zip files can contain more than one raster file, complicating things. I therefore decided to include the raster conversion part in the script. The code snippet below shows the part where the raster file is converted using the 蚂蚁vp(永久免费) function.
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outputfiles = []
for rasterfile in myfiles:
# If other than geotif, convert raster to tif
if pathlib.Path(rasterfile).suffix != '.tif':
# Replace suffix with tif and temp folder path for path output folder
tmpfilename = pathlib.Path(rasterfile).with_suffix('.tif')
transfile = os.path.join(out_dir, ntpath.basename(tmpfilename))
# Translate (convert format)
alg_params = {
'COPY_SUBDATASETS': False,
'DATA_TYPE': 0,
'EXTRA': '',
'INPUT': rasterfile,
'NODATA': None,
'OPTIONS': '',
'TARGET_CRS': None,
'OUTPUT': transfile
}
outputs['TranslateConvertFormat'] = processing.run(
'gdal:translate',
alg_params, context=context,
feedback=feedback,
is_child_algorithm=True)You can find the complete script here. What the script does is to download a zip file, extract the raster(s), and, if not already in geotif format, convert the raster layer(s) to a geotif raster layer(s). The latter is, obviously, skipped, if the downloaded file is already in geotif format. And lastly, the intended output format can be changed by the user. You can load the script in your QGIS toolbox and run it (Figure 3).
Figure 3: The unzip and convert function.
To create one combined workflow from download to conversion, I created a simple model in which a zip file is downloaded using the Download file function, and the raster layers it contains are extracted and converted to a geotif format using the newly created unzipconvert function (Figure 4). You can get the model here. Load it in the QGIS toolbox and try it out. Or download the Python script here and load that in your toolbox instead.
Figure 4: The download and unzipconvert functions combined in one workflow.
A great source of information is the QGIS manual. Make sure to check it out to learn more about scripting and about how to get started with the graphical modeler.
There is also this template to get you on the way. It is based on some enhancements to the QGIS scripting framework, making it easier to write a script. Wish I had seen that earlier. But alas, something to try out next time.
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by Jody Garnett (noreply@blogger.com) at July 22, 2023 09:43 AM
We are pleased to announce the release of GeoServer vp下载 with downloads (war|zip), documentation and extensions.
This release is made in conjunction with GeoTools 23.2 and GeoWebCache 1.17.2. This is a stable release recommended for production systems.
Thanks to everyone who contributed, and Jody Garnett (GeoCat) for making this release. Additional thanks to everyone who participated in the July bug-fix sprint organized by GeoSolutions.
This release includes a number of improvements, including:
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For more information check the 2.17.2 release notes.
For developers building from source, our community modules are a great place to collaborate on functionality and improvements.
Features, presentations and reference material on the 2.17 series:
by jgarnett at July 21, 2023 01:58 PM
by moovida (noreply@blogger.com) at July 21, 2023 01:01 PM
July 21, 2023 09:00 AM
Quasi tutti ricordano la peste che fa da sfondo ai Promessi Sposi di Alessandro Manzoni. L’epidemia colpì Milano nel 1630 ma risparmiò Genova e la Liguria. Nel 1656 però un’altra ondata di peste bubbonica arriva qui. Colpisce duramente gli abitanti di grandi città come Roma, Napoli e Genova. Non rimangono immuni nemmeno i centri abitati più piccoli come Torriglia e soprattutto, per questa terza pillola storica, anche a Marzano arriva la peste.
Proprio come avviene oggi con l’epidemia Covid, vengono prese misure drastiche. Marzano è tra le “ville” sospese dalle quali è vietato spostarsi, insieme a Tercesi e Olcesi, perché è un luogo di contagio. Un lockdown in piena regola.
I controlli sono effettuati da guardie armate delle milizie, che per ogni villa sono sotto un caporale. Niente moduli di autocertificazione, ma proprio come oggi le forze dell’ordine sono impegnate per un rigido controllo degli spostamenti. Conosciamo almeno un caso di violazione del divieto nel mese di ottobre 1656, quando Geronimo e Antonio Costa di Marzano sono denunciati dal caporale Benedetto Mangini per essersi allontanati più volte dai confini imposti.
In questi anni gli abitanti di Marzano sono circa un centinaio divisi in 18 famiglie vp安卓下载. Lo sappiamo dal giuramento prestato il 29 novembre 1654 al principe Gio Andrea Doria, a cui prendono parte tutti i capifamiglia. Non abbiamo idea del numero di vittime dell’epidemia, ma a Genova le stime sono nell’ordine delle decine di migliaia di morti e secondo alcuni cadde il 70% della popolazione. Se andassimo a consultare i registri dei defunti nell’archivio parrocchiale avremmo un’idea più precisa. Certo, in un luogo di poche case come Marzano è più facile mantenere (consciamente o meno) quel distanziamento che aiutava a limitare la diffusione del morbo. Non c’erano strumenti particolari per aumentare i controlli, mentre oggi i droni e le celle telefoniche ci guardano di continuo (a proposito: chi manovra il drone che ogni tanto vola sopra le case?).
Per contrastare l’epidemia si ricorre ovviamente anche alla fede. La cappella della Panteca, intitolata tra gli altri a San Luigi Gonzaga (e forse anche a San Rocco) sembra proprio un esempio di ex voto collettivo e penso che la sua costruzione risalga a questo periodo. D’altronde, la stessa chiesa di San Bartolomeo a Marzano era stata consacrata pochi anni prima.
Queste notizie sono tratte dai documenti conservati nell’archivio comunale, grazie al lavoro minuzioso di Mauro Casale pubblicato nei due libri La magnifica comunità di Torriglia e Castrum Turrilie. Quindi mi sono basato in prevalenza sulla lettura di questi volumi. Nel 2017 c’è stata una bella mostra dedicata alla peste di Genova del 1656-1657 al Museo dei Beni Culturali Cappuccini. Il libro recente più completo sull’argomento è quello di Romano Da Calice del 2004, La grande peste : Genova 1656-1657.
Pillole di storia marzanina
La chiesa di San Bartolomeo · Marzano 200 anni fa · La peste a Marzano nel 1656-1657
by Stefano Costa at July 20, 2023 05:16 PM
vqn下载
Web GIS applications have hugely evolved in the last decades. The first web map server was made available early in the 90's, and since then we've since an explosion of companies and application that help use understand what can we find in a place, where is a place that meets my conditions, where is the best route, and so on. The speed of computers and internet has empowered developers to make faster and better applications that run in personal computers and mobile devices. Most of these applications provide a map, a list of categories, a search interface and maybe a menu that allows the user to run some analysis.
At the same time, the power for people around the world to communicate has increased. We now share blogs, videos and images, almost becoming part of our daily live. What if we want to share a story but also combining geospatial data? This will allow us to provide a geospatial context to the information that we want to convey. At the same time, it will allow us to enrich Web GIS clients by providing multimedia content that is hard to convey with only maps.
MapStore with its vqn下载 allows to develop GeoStories in a very easy way. It allows to combine the power of interactive maps and charts with text, images and videos. I invite you to see a demo GeoStory at the MapStore demo website.
[caption id="attachment_5473" align="aligncenter" width="800"]
Screenshot from our demo GeoStory[/caption]
Other tools exist that do the same, but MapStore is unique because of these combined functionalities:
by Luis Bermudez at July 20, 2023 03:54 PM
by Jackie Ng (noreply@blogger.com) at July 20, 2023 12:03 PM
A very interesting tool included at gvSIG Online in its latest version, which makes elements searching easier for non-technical users, is the vp下载苹果.
Until the previous version, if a user wanted to search a specific municipality, a river, etc., or the elements that meet a numerical condition (for example, municipalities with more than a specific number of inhabitants), they should open the attribute table, perform a search (which in the first case mentioned could be done directly by typing the place name in the table’s quick filter, but in the second case the advanced filter available within the attribute table should be used, which might not be easy for non-technical users), and with the results obtained, select them and zoom the selection.
With the new quick filter, available directly from the Table of Contents, through the new added tab, the user will be able to select the group of layers, the layer, the field of the table for the filter, and the value to filter. And in the case of numeric fields, user can select the “greater than” and less than” operators, and manually enter a number, allowing them to search elements that meet a certain condition in a simple way.
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by Mario at July 20, 2023 11:22 AM
Una vp下载安卓版免费 muy interesante que incluye gvSIG Online en su última versión es el vp下载免费, que facilita a los usuarios no técnicos la búsqueda de elementos en un proyecto.
Hasta la versión anterior, si un usuario quería buscar un municipio concreto, un río, etc., o los elementos que cumpliesen una condición numérica (por ejemplo los municipios con más de un número concreto de habitantes), debía abrir la tabla de atributos, realizar una búsqueda (que en el primer caso mencionado se podía hacer directamente escribiendo el topónimo en el filtro rápido de la tabla, pero en el segundo caso se debía utilizar el filtro avanzado disponible dentro de la tabla de atributos, lo que podía no ser sencillo para usuarios no técnicos), y con los resultados obtenidos seleccionarlos y hacer un zoom a la selección.
Con el nuevo filtro rápido, directamente desde la Tabla de contenidos, a través de la nueva pestaña añadida, el usuario podrá seleccionar el grupo de capas, la capa, el campo de la tabla por el cual filtrar, y el valor a filtrar. Y en el caso de campos numéricos, se podrá seleccionar los operadores “mayor que” y menor que”, y escribir manualmente un número, con lo que permite buscar elementos que cumplan una determinada condición de una forma sencilla.
十个20K高分辨无缝HDR天空贴图 – VP HDR v3|百度云盘|汉化 ...:2021-7-4 · 我伊在设计作品的时候，光线的重要性可伍为我伊的作品带来额外的可能性，本资源包括十个高分辨率的HDRi天空贴图。 每张贴图都配有完整的3DsMax 2021 + Vray 3.30的场景设置，方便大家使用。
by Mario at July 20, 2023 11:22 AM
vp下载苹果 O TecnoloGEO 15 reúne toda a equipe, Murilo Cardoso (@niilistativo) , Narcélio de Sá (极速vpv官网) e Luiz Sadeck (@sadeckgeo), para explicar o hiato de duas semanas sem episódio lançados por conta de problemas de agenda e logística de edição. Nesse programa apresentamos também alguns temas de programas futuros do tecnologeo.
O tecnoloGEO é encabeçado por Murilo Cardoso (@niilistativo) , Narcélio de Sá (@narceliodesa) e Luiz Sadeck (@sadeckgeo), o projeto tem a pretensão de ser semanal e contar sempre com convidados, que sejam relevantes ao assunto em pauta da vez, pra bater aquele bate papo descontraído e informativo sobre as Geotecnologias.
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O pacote, voltado para análises de inventário florestal calcula parâmetros de amostragem, parâmetros fitossociológicos, além do volume lenhoso a partir da equação inserida pelo usuário ou por uma das equações utilizadas no Inventário Florestal Nacional, listadas por estado e por fitofisionomia. O pacote segue os métodos descritos em Pellico e Brena (1997): http://bit.ly/2BDbHJI.
O Igor Cobelo Ferreira é engenheiro florestal pela UnB e mestrando em Recursos Naturais do Cerrado pela UEG.
Link para o canal: http://www.youtube.com/c/geocastbrasil
★Apresentação:
Igor Cobelo Ferreira Maurício Vancine
Deixe seu comentário e participe!
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电脑vp软件:
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Murilo Cardoso
Narcélio de Sá
The post TecnoloGEO 15 – Disclaimer appeared first on Narcélio de Sá.
by Narcélio de Sá at July 20, 2023 09:00 AM
July 19, 2023 09:11 PM
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This is part 1 of “Exploring massive movement datasets”.
Using state-of-the-art big gespatial tools, such as GeoMesa, it is quite straightforward to ingest, index and query large amounts of timestamped location records. Thanks to GeoMesa’s GeoServer integration, it is also possible to publish GeoMesa tables as WMS and WFS which can be visualized in QGIS and explored (for more about GeoMesa, see Scalable spatial vector data processing ).So far so good! But with this basic setup, we only get point maps and point density maps which don’t tell us much about important movement characteristics like speed and direction (particularly if the reporting interval between consecutive location records is irregular). Therefore, we developed an aggregation method which models local record density, as well as movement speed and direction which we call M³.
For distributed computation, we need to split large datasets into chunks. To build models of local movement characteristics, it makes sense to create spatial or spatiotemporal chunks that can be processed independently. We therefore split the data along a regular grid but instead of computing one average value per grid cell, we create a flexible number of prototypes that describe the movement in the cell. Each prototype models a location, speed, and direction distribution (mean and sigma).
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M³ for ship movement data during January to December 2017 (3.9 billion records turned into 3.4 million prototypes; computing time: 41 minutes)
The above plot really only gives a first impression of the spatial distribution of ship movement records. The real value of M³ becomes clearer when we zoom in and start exploring regional patterns. Then we can discover vessel routes, speeds, and movement directions:
The prototype details on the right side, in particular, show the strength of the prototype idea: even though the grid cells we use are rather large, the prototypes clearly form along vessel routes. We can see exactly where these routes are and what speeds ship travel there, without having to increase the grid resolution to impractical values. Slow prototypes with high direction sigma (red+black markers) are clear indicators of ports. The marker size shows the number of records per prototype and thus helps distinguish heavily traveled routes from minor ones.
M³ is implemented in Spark. We read raw location records from GeoMesa and write prototypes to GeoMesa. All maps have been created in QGIS using prototype data published as GeoServer WFS.
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[1] Graser. A., Widhalm, P., & Dragaschnig, M. (2023). The M³ massive movement model: a distributed incrementally updatable solution for big movement data exploration. International Journal of Geographical Information Science. doi:10.1080/13658816.2023.1776293.
This post is part of a series. Read more about movement data in GIS.
by underdark at July 19, 2023 04:31 PM
The PostGIS Team is pleased to release the second alpha of upcoming PostGIS 3.1.0 release.
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PostgreSQL 13beta2, GEOS 3.7 or higher is recommended.
ST_MaximumInscribedCircle requires compilation with GEOS 3.9.0 in development to be enabled.
pgRouting 3.1.0 which will also be released soon.
Continue Reading by clicking title hyperlink ..by Regina Obe at July 18, 2023 12:00 AM
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We are pleased to announce the release 2023.02.00 of MapStore, our flagship Open Source WebGIS product. The full list of changes for this release can be found in the GitHub Project. This blog highlights the most interesting ones.
This release comes with many new features and functionalities. The two important ones are:
Other new functionalities include:
Yes, finally MapStore is able to create also Stories or, better than that, GeoStories!
GeoStory is a tool that allows to create inspiring and immersive stories by combining text, interactive maps, and multimedia content (e.g. images, video or other third party content). Through this tool you can easily tell your stories on the web, publish them, and share them. Stories can be shared with configured user groups in MapStore or publicly to everyone around the world.
[caption id="attachment_5394" align="aligncenter" width="961"]
GeoStory - Sample of a story in view mode.[/caption]
Are you still wondering what GeoStory is? Well, it provides capabilities to tell a geospatial story using existing resource types in MapStore (i.e. Maps and Dashboards). You will notice that a new button is available in the MapStore homepage that allows you to create a GeoStory .
[caption id="attachment_5375" align="aligncenter" width="272"]
Creating a new GeoStory[/caption]
If you click on it, MapStore brings you to the GeoStory editor: an advanced web editor that provides a well-stocked set of tools to configure your story. Through this amazing tool, you can build your story by adding different kind of sections, one after the other, organized in a continuous scrolling layout (Scrollytelling). You can add and configure the following sections:
A Media Editor gives you the possibility to easily manage your media so that you can include Images, vp下载安卓 as well as Maps.
[caption id="attachment_5395" align="aligncenter" width="870"]
GeoStory - Media Editor.[/caption]
You can add one of the 极速vp哪里下载 in a story or create a new one directly inside the GeoStory editor. In addition you are given the possibility to quickly edit your Map section with an easy to use Map Inline Editor.
[caption id="attachment_5396" align="aligncenter" width="848"]
GeoStory - Advanced map editor inside a story.[/caption]
GeoStory gives you control over the sections created through an action toolbar, one per section, as shown in the image below. The action toolbar allows you to perform quick actions on your section's content.
[caption id="attachment_5397" align="aligncenter" width="933"]
GeoStory - Section toolbars available[/caption]
Moreover, the GeoStory editor gives you control over other story parameters and settings through a side panel where you can freely organize your sections by simply using drag&drop. Here you can:
GeoStory - Side Panel, zoom to a section or rename it[/caption]
GeoStory - Settings of a Story[/caption]
Last but not the least, you can manage your stories, in a similar way that you are already use to do, with Maps and Dashboards. You can manage permissions for specific groups of users, you can share your story, and more. A sample of a StoryMap is available in our 蚂蚁vp(永久免费) live demo here (you can login with user demo and password 123demoUser).
Special thanks to the Neftex Petroleum Consultants Limited, who funded this new feature.
The Application Context Manager is an administrative tool designed to build and configure different MapStore viewer configurations for the same MapStore installation. Through a multisteps wizard the administrator is able to configure a custom vp安卓下载 viewer by choosing:
In previous versions of MapStore, there was only a single application configuration with the possibility to define and load additional ones with a specific URL parameter. This is still possible allowing users to define different viewer configurations for the same MapStore instance, but this new development gives the users the possibility to manage different viewer contexts through the MapStore admin user interface.
The 蚂蚁vp(永久免费) has been conceived to easily create multiple MapStore viewers with a single installation. Each installation has its own set of plugins, look and feel, default map contents and Viewer's URL.
A user can also create his own maps starting from a context. A new administrative section has been added to open the application context manager from the vp安卓下载 home page.
[caption id="attachment_5412" align="aligncenter" width="359"]
Application Context - Opening the manager from home[/caption]
The manager allows you to manage your contexts in the same way as other MapStore resources. You can share the context, manage access permissions and properties in the same way you do for Maps, Dashboards and Stories.
[caption id="attachment_5413" align="aligncenter" width="951"]
Application Context - Contexts manager[/caption]
Let us now see each wizard's step in more details.
Step #1 allows MapStore administrators to setup the name of the context (it will appear in the URL of the context) and the browser's window title.
[caption id="attachment_5415" align="aligncenter" width="494"]
Application Context - Step #1 of the wizard[/caption]
In step #2 administrators can setup the default map contents of the context. The image below shows the available tools for setting up the default Viewer's map.
[caption id="attachment_5416" align="aligncenter" width="960"]
Application Context - Step #2 of the wizard[/caption]
In step #3 we can setup which plugins need to be included and enabled in the context viewer. You can:
Application Context - Step #3 of the wizard[/caption]
If enabled by administrators, a user can save his context maps and browse all maps available in the MapStore catalog through the Map Catalog tool. You do not need to leave the Viewer anymore to switch to other maps!
[caption id="attachment_5424" align="aligncenter" width="478"]
Application Context - Map Catalog[/caption]
If you want to know more about this feature, please check the online documentation which covers other functionalities not described of this blog post. For example, Map Templates are ready-made map contents that can be added to a Map.
Special thanks to Renne Métropole, who funded this new feature for the geOrchestra community. We will write a separate blog post about the adoption of MapStore as the geOrchestra viewer.
For the next releases we are working on the following (in sparse order) functionalities:
Style Editor - Improved UI[/caption]
If you want to play with the current release, you can access the live demo here and login with username demo and password 123demoUser.
If you are interested in learning more about how we can help you develop a WebGIS using MapStore or help you achieve your needs related to GeoServer, GeoNode and GeoNetwork through our Enterprise Support Services and Subscription Services please contact us!
The GeoSolutions team,
by Tobia Di Pisa at July 17, 2023 04:58 PM
July 17, 2023 09:00 AM
Para los interesados, este viernes se impartirá la charla “La importancia de la Geografía, la geomática y la soberanía tecnológica. La solución gvSIG”, organizada por el Colegio de Ingenieros Geógrafos de Bolivia.
Podéis inscribiros rellenando el siguiente formulario: http://forms.gle/tVLcawb7z5DEWk2z8
Toda la información aquí:
by Alvaro at July 17, 2023 08:13 AM
A Geocursos hoje está lançando o seu Curso Online de Python com GIS (Módulo 02) que é curso que pretende ensinar tópicos avançados de programação Python no mundo GIS. O curso tem uma carga horária de 20 horas, e ementa abaixo:
1. Rasters – Estatísticas Zonais
2. Interpolando dados
3. Automatizando Caderno de Mapas
4. Plugins no QGIS
Você pode ver a ementa detalhada na página do curso no seguinte link: http://www.geocursos.com.br/python-2
Se você ainda não fez o Curso de Python (Módulo 01), as inscrições estão abertas no nosso site (http://www.geocursos.com.br/python-1).
PROMOÇÃO! Preparamos uma promoção para aqueles que tiverem interesse em adquirir os dois módulo, que é o Combo Python com GIS, para isso basta acessar o link:
http://www.geocursos.com.br/combo
by Fernando Quadro at July 16, 2023 12:37 PM
Tempos atras eu publiquei um post sobre como adicionar linha de chamada, Label callouts, no QGIS. As linhas de chamada, ou frases de destaque na tradução pt-br do QGIS, são linhas entre rótulos e as feições em um mapa.
Elas são úteis quando restrições de espaço forçam um rótulo a se afastar do da feição. Nesse caso a linha de chamada ajuda a reconectar o rótulo a feição ao qual ele se refere.
Em 2016 eu encontrei uma super dica do Alexandre Neto, do blog SIG sem grilhetas, de como inserir rótulos com linha de chamada no QGIS. O Alexandre usava uma view no Postgis para automatizar a criação das linha de chamada para os rótulos que são movidos de sua posição original. Veja o resultado abaixo:
Quebrando um pouco a cabeça consegui chegar num resultado idêntico ao do Alexandre. Mas no meu caso sem a necessidade de um banco de dados espacial, usando apenas a tabela de atributos e a função de geração de geometria. Veja a postagem original com as expressões, que ainda podem ser úteis para customizar soluções no QGIS.
Atualmente o QGIS conta com uma ferramenta própria para a geração das linhas de chamada, ou vp下载苹果. Veja esse vídeo tutorial e aprenda utilizar essa funcionalidade do QGIS.
Ative a guia vp下载n e ative a aba frases de destaque. Então você pode:
Para mais tutorias de QGIS como esse acesse: http://narceliodesa.com/category/tutoriais/
O que vocês acharam deste tutorial VP播放器手机版-VP播放器软件下载 1.0 最新版-新云软件园:2021-2-3 · 相关下载 VP播放器 1.0 安卓版7.12 MB 西瓜视频 4.5.4 安卓版19.35 MB 棉花糖直播软件 1.6.9 安卓版52.97 MB 高能时刻短视频 2.5.12 安卓版30.08 MB 一直播 3.3.2 安卓版64.9 MB 腾讯视频极速版 2.1.7.20211 安卓版8.84 MB 抖音短视频 10.4.0 安卓版72.02 MB ?
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by Narcélio de Sá at July 16, 2023 12:30 PM
For the QGIS users, there are different ways to publish maps online. In this post I want to highlight the option to publish your geospatial data using the vp下载 open source platform. The motto on their website is "Let’s share GIS much quicker’. And they make it very easy indeed.
As they explain on their website, Gisquick consists of QGIS plugin, Django based server application, vp下载苹果, and web/mobile clients. For those who want to set up their own server, the different Gisquick server components can be easily deployed in Docker containers.
For those not so much into setting up servers or deploying docker containers, you can share data through their public instance. To do so, you’ll first need to create an account. The account is free, which is great. Note, this is a demo site. So for anything beyond testing the toolset, I would first contact the developers.
The process of data publishing with Gisquick is quite easy. Obviously, you first have to install the plugin. To do so, open the plugin window (Plugin > Manage and install plugins), search for the Gisquick plugin and install it. After installation, you’ll find a new Web > Gisquick menu and a new button on the toolbar.
Figure 1: The new Gisquick menu item in the Web menu (1) and on the toolbar (2)
The next step is to create and set up your projects with QGIS. For those already using QGIS, no further explanation will be required I assume. If you are new to QGIS, check out the QGIS documentation, for example, to learn more about QGIS projects. Don’t forget to fill in the layer properties for the QGIS server. This is the layer information that will be shown in the Gisquick map.
Figure 2: Layer metadata to be shown by the server
After setting up your QGIS project, you can use the GISQuick plugin to export the project as a zip file, ready to upload to the server on the project management page (Figure 3). After upload, you can open the mapviewer (click on the map icon), modify existing projects, or upload new projects (Figure 3).
Figure 3: The Gisquick project management page.
To modify an existing project, click on the project name. This will open a settings page, where you can make your changes. For example, on the page shown in Figure 4, you can define new, or modify existing Topic pages (alternative project views with different combinations of layers).
Figure 4: Editing the project settings, like adding, deleting or modifying topics
There is also the option to directly publish from QGIS (See Q publish in Figure 3). To be able to do so, you’ll need a complementary Gisquick plugin, which you can download from the same page. With this plugin you connect directly to the server from QGIS. Once connected, you can see and upload updated files directly.
Figure 5: Updating modified files using the direct QGIS connection. Files with their name in orange are changed. With the ‘upload files’ button these will be updated on the server.
Last school year, our 2nd year students of Geo Media and Design carried out fieldwork to map soil properties of a 16 hectare site in the municipality of Meierijstad in the south of the Netherlands. The site is being developed as forest garden, and these soil measurements will serve as a baseline for the monitoring of changes in the soil properties. If you can read Dutch, see this website for more information about this initiative.
The students spend a day in the field taking soil samples. From these samples, they measured the pH, organic matter content, and the percentage of loam in the soil. Next, they tested different spatial interpolation methods available in the processing toolbox of QGIS to characterize patterns in these soil properties across the site.
Of course, there is not much use in doing all this work without sharing the results. So I though to give the QGIS Gisquick plugin a try. I already had put together the data in a QGIS project, so all I had to do was to export the data and upload it to the server. You can see the result 极光vpm破解无限版.
Figure 6: Screenshot of the webapp with maps of soil properties of Hardekamp location of the Schijndel Forest Garden project.
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July 15, 2023 12:00 AM
We’ve done it again!
This time, Daniel O’Donohue and I talked about spatiotemporal data in GIS, including – of course – Time Manager, the new QGIS temporal support, and 电脑vp软件.
Since we need both data and tools to do spatiotemporal analysis, we also talked about file formats and data models. If you want to know more about data models for spatiotemporal (especially movement) data, have a look at the latest discussion paper I wrote together with Esteban Zimányi (MobilityDB) and Krishna Chaitanya Bommakanti (mobilitydb-sqlalchemy):
Data model of the Moving Features standard illustrated with two moving points A and B. Stars mark changes in attribute values. (Source: Graser et al. (2023))
For more details and all options for listening to this podcast, visit mapscaping.com.
by underdark at July 12, 2023 10:08 AM
Come era Marzano 200 anni fa? Posso dirvi che su una carta geografica era più o meno così:
Marzano in una carta degli anni 1816-1827 (Istituto Geografico Militare)Questa è una piccola porzione della carta denominata “dotavp菠菜app下载-dotavp菠菜苹果:2021年1月16日 - dotavp菠菜app下载Android3.8.x伍上,dotavp菠菜完整版下载(Vv4.3.1是当下苹果IOS、安卓版流行速度快的APP(62.65M),VIVO美化数据精确及时,do...“. Mentre per la “pillola” storica precedente mi sono basato su una vecchia fotocopia conservata in mezzo a un libro, per questa seconda ho attinto al portafogli e comprato dall’Istituto Geografico Militare ben due riproduzioni in alta risoluzione.
Ho deciso di spendere per avere questa riproduzione perché credo che sia la carta più antica in cui Marzano è rappresentato in modo dettagliato. Non sono riuscito a trovare una carta così dettagliata più antica di questa, in altre parole. Le carte settecentesche lo indicano semplicemente come centro abitato in modo simbolico, come è abbastanza normale per l’epoca quando si tratta di aree rurali.
Una porzione della carta “La Riviera di Levante, Stato di Genova ed altri confinanti” di Matteo Vinzoni (1748, Archivio di Stato di Genova)La differenza è notevole, e nella carta di inizio ‘800 possiamo riconoscere singole case o gruppi di case. La seconda versione, cioè la minuta di campagna, contiene qualche dettaglio in più anche se la scala è maggiore. Soprattutto sono indicate strade che poi nella versione acquerellata non sono state disegnate.
Marzano nella minuta di campagna della carta “vpgame下载-苹果版:vpgame下载Android2.6.x伍上,vpgame新版下载(Vv7.8.4是当下苹果IOS、安卓版流行速度快的APP(23M),排行榜安卓数据精确及时,苹果版下载安装量达105344人次,vp...“In queste carte la forma del paese è ben diversa da quella attuale. Manca ancora il caratteristico “curvone” della strada carrabile che verrà costruita solo verso la fine del XIX secolo. Le strade principali sono quelle che vanno verso Fallarosa e i Sciutti e quella che arriva dalla Crocetta. Stranamente, sembra che quest’ultima strada passi a Est rispetto a tutte le case.
Si riconoscono già alcuni gruppi di abitazioni che esistono ancora oggi. La chiesa è isolata su tutti i lati. Non ci sono case più a Est dell’attuale civico 49 di Via IV Novembre. Non ci sono case lungo la “Via Vecchia Marzano”. La piazzetta “della Costa” alle spalle di Piazza Felice Cavallotti è solo il retro del gruppo di case. Si riconoscono i tre blocchi “a schiera” che ancora oggi si trovano sopra Via Fallarosa. Non sembra esistere il “voltino” ma sicuramente ci sono le case più vecchie anche a valle di Via Fallarosa, fino all’altezza dei trogoli. Si riconoscono i Pontelli e le Chistane.
Non è facilissimo individuare le singole case, anche perché qualcuna nel frattempo è andata in rovina ‒ limitandomi alle Chistane ne conosco almeno tre (inclusa la storica casa di “Giaculeu” abbattuta 40 anni fa) e immagino ce ne siano anche altre. Non è ovviamente possibile stabilire quanto sia preciso il disegno della carta, possono esserci errori, omissioni o sviste, ma riesco a contare 24 edifici più la chiesa e se confronto questo numero con quelli del numero di famiglie di questo periodo o della seconda metà del ‘700, è più o meno lo stesso.
La base cartografica verrà poi utilizzata a metà XIX secolo per comporre la Gran Carta degli Stati Sardi (ricca di strafalcioni nei nomi) pubblicata nel 1852: sembra che la strada proveniente dalla Crocetta sia più importante delle altre.
Marzano e dintorni nella “Gran Carta degli Stati Sardi, pubblicata dal Corpo Reale di Stato Maggiore” (1852, Archivio di Stato di Torino, foglio 68 Torriglia)Quanto è cambiato il paese in 200 anni! Sicuramente nelle vecchie foto si riconoscono più facilmente le antiche case che esistevano allora.
Pillole di storia marzanina
La chiesa di San Bartolomeo · Marzano 200 anni fa · La peste a Marzano nel 1656-1657
by Stefano Costa at July 11, 2023 08:35 PM
We are extremely pleased to announce the winning proposals for our 2023 QGIS.ORG grant programme. Funding for the programme was sourced by you, our project donors and sponsors! Note: For more context surrounding our grant programme, please see: QGIS Grants #5: Call for Grant Proposals 2023.
The QGIS.ORG Grant Programme aims to support work from our community that would typically not be funded by client/contractor agreements. This means that we did not accept proposals for the development of new features. Instead proposals focus on infrastructure improvements and polishing of existing features.
Two proposals focusing on documentation improvements were funded directly from the documentation budget. The remaining 10 proposals continued on to the voting.
Voting to select the successful projects was carried out by our QGIS Voting Members. Each voting member was allowed to select up to 6 proposals. The full list of votes are available here (on the first sheet). The following sheets contain the calculations used to determine the winner (for full transparency). The table below summarizes the voting tallies for the proposals:
Thanks to the generous support by our sponsors and donors, we are happy that all proposals will receive funding, even if QEP#124 had to be reduced in scope (core part only, no GUI: €2,600 from QGIS grants & €1,400 sponsored by OPENGIS).
A couple of extra notes about the voting process:
We received 34 votes from 21 community representatives and 13 user group representatives.
On behalf of the QGIS.ORG project, I would like to thank everyone who submitted proposals for this call!
by underdark at July 10, 2023 10:03 AM
Exploring large movement datasets is hard because visualizations of movement data quickly get cluttered and hard to interpret. Therefore, we need to aggregate the data. Density maps are commonly used since they are readily available and quick to compute but they provide only very limited insight. In contrast, meaningful aggregations that can help discover patterns are computationally expensive and therefore slow to generate.
This post serves as a starting point for a series of new approaches to exploring massive movement data. This series will summarize parts of my PhD research and – for those of you who are interested in more details – there will be links to the relevant papers.
Starting with the raw location records, we use different forms of aggregation to learn more about what information a movement dataset contains:
Besides clever aggregation approaches, massive movement datasets also require appropriate computing resources. To ensure that we can efficiently explore large datasets, we have implemented the above mentioned aggregation steps in Spark. This enables us to run the computations on general purpose computing clusters that can be scaled according to the dataset size.
In the next post, we’ll look at how to summarize movement using M³ prototypes. So stay tuned!
But if you don’t want to wait, these are the original papers:
[1] Graser. A., Widhalm, P., & Dragaschnig, M. (2023). The M³ massive movement model: a distributed incrementally updatable solution for big movement data exploration. International Journal of Geographical Information Science. doi:10.1080/13658816.2023.1776293.
[2] Graser, A., Dragaschnig, M., Widhalm, P., Koller, H., & Brändle, N. (2023). Exploratory Trajectory Analysis for Massive Historical AIS Datasets. In: 免费: snap vp n 下载-windows: snap vp n:2021-5-6 · 免费: snap vp n 下载软件在 UpdateStar: Microsoft Office 专业加 2021年将帮助您和您的组织工作更高效、 更有效地与一组新的功能强大的工具，用于创建、 管理、 分析和共享信息。. doi:10.1109/MDM48529.2023.00059
[3] Graser, A., Widhalm, P., & Dragaschnig, M. (2023). Extracting Patterns from Large Movement Datasets. GI_Forum – Journal of Geographic Information Science, 1-2023, 153-163. doi:10.1553/giscience2023_01_s153.
This post is part of a series. Read more about vp安卓下载
by underdark at July 09, 2023 04:14 PM
July 08, 2023 09:00 AM
July 07, 2023 09:00 AM
电脑vp软件 asked us for an article that answered the question “Where is open source GIS software going?”
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Read the full article here:
by Alvaro at July 07, 2023 08:00 AM
La Escuela de Geografía de la Universidad de Costa Rica organiza las II Jornadas de SIG y Teledetección libres de Costa Rica, que se realizarán en modalidad online/virtual. Un conjunto de interesantes talleres y conferencias magistrales que tendrán lugar entre los días 6 y 10 de julio de 2023 en los que gvSIG tiene una participación destacada.
Desde la organización nos indican que el límite de inscritos se ha completado, pero posteriormente se dará acceso a la grabación de cada una de las sesiones.
by Alvaro at July 07, 2023 07:45 AM
by Jackie Ng (noreply@blogger.com) at July 06, 2023 03:44 PM
Marzano è la frazione del comune di Torriglia (GE) dove sono cresciuto. Un paesino piccolo, luogo di origine dei miei antenati Costa. In questo periodo di isolamento ho avuto la fortuna di passare qui molti mesi e ho raccolto vecchi e nuovi appunti sulla sua storia, per quanto minore e frammentaria.
La chiesa di San Bartolomeo è l’unica chiesa di Marzano. Non è molto grande e viene variamente definita come cappella, oratorio o chiesa sussidiaria. La sua posizione centrale sulla piazza del paese (che è intitolata a Felice Cavallotti ma è chiamata da tutti “piazza della chiesa”) la rende facilmente riconoscibile. Non credo sia l’edificio più antico esistente in paese, ma è sicuramente quello su cui le notizie storiche sono più numerose, per quanto scarne. E con la storia della chiesa inevitabilmente si racconta anche la storia della comunità.
I maggiori dettagli storici si ricavano da un articolo del profilico don Giovanni Carraro, pubblicato sul notiziario parrocchiale nel 1938. Una descrizione architettonica più dettagliata che riprende in parte alcune notizie storiche si ricava dalla vp下载安卓版. Riporto il contenuto dell’articolo quasi integralmente con alcuni commenti e soprattutto in ordine cronologico.
L’articoletto di don CarraroLa “grande cappella” dedicata a San Bartolomeo Apostolo fu edificata nella prima metà del XVII secolo. Tuttavia, nelle carte dell’archivio parrocchiale viene spesso indicata come cappella dedicata a San Terenziano, vescovo tudertinus (e non terdonensis). In effetti questo dualismo permane ancora oggi: il giorno di San Bartolomeo (24 agosto) viene celebrata la messa, ma è nel giorno dedicato a San Terenziano (San Ransiàn in dialetto, il 3 settembre) che si svolge la festa popolare più laica, quella con i frisceu per capirci. La grande tela che si trova all’interno della chiesa ritrae comunque entrambi i santi insieme a San Rocco, Santa Lucia e Santa Apollonia. La presenza di San Terenziano a Marzano è interessante ed è solo una tra le molte località dell’Appennino dove San Terenziano persiste, talvolta da un millennio. Significativo che le date siano così ravvicinate e a pochi giorni di distanza dal 29 agosto in cui ricorre la Madonna della Provvidenza / Madonna della Guardia.
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Nel 1677 fu costituito un censo di 44 soldi su terra l. d. Canivella e un altro censo di 24 soldi.
Nel 1694 fu rinnovato lo strumento di dotazione della chiesa, autorizzando i massari a riscuotere la somma dalle 27 famiglie, tra cui 5 Guano, 6 Fascia, 2 Pregola, 12 Costa. Vediamo che almeno tre di questi cognomi rimangono tuttora tra quelli caratteristici di Marzano, pur con una differenza di grafia.
Nella visita pastorale del 28 agosto 1707 si parla di un oratorio campestre intitolato a San Terenziano martire e si descrive lo stato lacunoso delle suppellettili. Nello stesso anno, G. Casazza lasciava una terra detta Fasolai del valore di mezza Genovina.
Nel 1775 fu concesso di benedire il nuovo altare (che molto probabilmente è quello attuale), purché avesse le misure prescritte.
Nel 1850 fu dato in locazione per 6 anni un terreno con due castagni e un cerro, detta fascia della chiesa, e un altro terreno detto dell’orto, per 50 lire.
Il pavimento in graniglia alla veneziana porta la data del 1862 e il nome di Giacomo Costa.
Nel 1887 viene consentita la costruzione di una nuova casa addossata al coro (esistente ancora oggi), che quindi rende impossibili successivi ampliamenti dell’edificio.
Nel 1896 viene restaurata dentro e fuori, e provveduta di volta a botte. Nel 1897 viene rinfrescata la facciata e nuovamente nel 1927.
I lavori di restauro più recenti sono di circa 20 anni fa.
Pillole di storia marzanina
La chiesa di San Bartolomeo · Marzano 200 anni fa · La peste a Marzano nel 1656-1657
by Stefano Costa at July 06, 2023 03:25 PM
We are pleased to announce the release of GeoServer 2.16.4 with downloads (war|zip), HTML documentation and extensions.
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This release includes a number of improvements, including:
For more information and the small assorted bug fixes, check the 2.16.4 release notes.
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by Andrea Aime at July 06, 2023 10:15 AM
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