There is an increasing need for conservation and connection with nature in cities. In this sense, geospatial analysis plays an important role in the effective management of our natural resources. In this tutorial we are going to represent the distribution of tree species in the streets of San Francisco by color and we will add some interaction through widgets, which will allow us to explore the map by selecting targered filters of interest. In this example, filters are applied by specie and date of planting.
Understanding the urban areas has important implications in a wide range of geospatial analysis, for example, to inform decision-makers in sectors such as urban planning. In this example we are creating a tileset in which each building in Madrid is represented by a polygon and each of them is assigned a graduated color from the lowest to the highest value of the gross floor area. This visualisation allows us to represent at a glance how the surface area in Madrid is distributed.
Understanding & analyzing spatial data is critical to the future of your business. CARTO 3 Location Intelligence platform allows organizations to store, enrich,analyze & visualize their data to make spatially-aware decisions. In this example we are going to use points clustering to analyze how to find the best place to locate six stores in Portland city based on proximity to customers.
In this tutorial we are going to showcase how to leverage the public data offering from our Data Observatory and use the data from a subscription to build an interactive dashboard in our map-making tool, Builder. In order to build this dashboard we are going to first create a tileset in order to be able to visualize a larger amount of data.
A geospatial analysis of land use dynamics has special relevance for the management of many phenomena, such as the assessment of the loss of soil due to erosion or the reduction of rural land in favour of the built-up areas. In this regard, Digital elevation Models (DEM) are important inputs to quantify the characteristics of the land surface. In this example we are building a map from a tileset createad by CARTO from a new NASA Digital Elevation Model (NASADEM). We are going to represent the distribution of land elevation by using a gradual color palette and then build a 3D visualization by assigning heights to polygons.