“SASPlanet is a program designed for viewing and downloading satellite maps”

La recomandarea unui prieten, (thx Liviu) 🙂 pun pe blog link catre o mica platforma software care permite vizualizarea si descarcarea imaginilor satelitare din diverse surse.

Marturisesc ca m-am dus initial la linkul dat de google insa m-am lasat pagubas pentru ca tot ce am facut a fost sa descarc un “software informer”, adica un instrument cu ajutorul caruia imi descarc softul, etc. etc. etc. dar nu a produs decat un uninstall scurt. Asa ca am sapat si am gasit tool-ul aici: motiv pentru care va recomand acest link. In dreapta: download, si veti descarca o arhiva de vreo 12.5 mb, o chestie “portabila”, care dupa dezarhivare, va fi “ready to run”.

Cam asa arata:


SASPlanet is a program designed for viewing and downloading high-resolution satellite imagery and conventional maps submitted by such services as Google Maps, DigitalGlobe, Kosmosnimki, Yandex.Maps, Yahoo! Maps, VirtualEarth, Gurtam, OpenStreetMap, eAtlas, Genshtab maps, iPhone maps, Navitel maps, Bings Maps (Bird’s Eye) etc., but in contrast to all these services all downloaded images will remain on your computer and you will be able to view them, even without connecting to the internet. In addition to the satellite-based maps you can work with the political landscape, combined maps and maps of the Moon and Mars.

Cu alte cuvinte, putem vedea si descarca (offline), chiar si hartile de pe Luna sau Marte. Wow, am zis, interesant. Si culmea, chiar functioneaza.

Creditele, desigur, merg la gagiul asta, Viktor Demydov:

Un scurt tutorial, care va duce si la alte tutoriale, gasiti aici:

Nu ma intru in alte detalii, pentru ca treaba e destul de “self-explanatory”.


Vertical Datum – Earth’s Elevation Reference Frame

vertical datum
Geoid from NASA’s Grace Mission – Image Courtesy of NASA/JPL

What is a Vertical Datum?

When the Federal Emergency Management Agency (FEMA) assesses the possibility of 100-year flood and states that flood waters will rise 25 feet…

…what exactly is “25 feet” referenced to?

We need a consistent starting point to compare flood and ground elevations. Enter the vertical datum.

Surveyors, geodesists and insurers use the vertical datum as a surface of zero elevation to which heights can be referred to.

Tidal Datums vs Vertical Geodetic Datums

When you talk about vertical datums, you can break them into two:

Tidal datums reflect the interface between water and land and is defined by the tidal variation. For example, a tide gauge in the water measures mean sea level. Tidal datums are localized because the transition between types of datums can shift quickly. It’s also time dependent.

Tidal Gauge | Image  Credit: NOAA
Installing a Tide Gauge | Image Credit: NOAA

A Geodetic datum is a reference surface of zero elevation to which heights are referred to over a large geographic extent. These datums are used to measure height (altitude) and depth (depression) above and below mean sea level. Commonly used vertical datums in North America are the National Geodetic Vertical Datum of 1929 (NGVD29) and the North American Vertical Datum of 1988 (NAVD88).

A (vertical) geodetic datum often ties in tidal datums. A geodetic datum reference might use a tidal datum as a start point. If you think about it, a community’s height system should be consistent with a tidal datum because that’s where the water will flow.

Types of Reference Heights

There are different types of heights to be aware of when referring to a vertical datum. These are the 3 primary types of heights, although other types of heights exist:

Reference Ellipsoid / Spheroid

Orthometric – This height represents the distance between the Earth surface and geoid at a specific point. Surveyors usually refer to orthometric heights. When you take the height at the peak of a mountain. It’s an orthometric height measured as a distance between the surface and the geoid.

The Geoid – The geoid coincides with mean sea level as if you are imagining it as an extension under (or over) land areas. The geoid is an equipotential surface at which gravity is normal – closely approximating mean sea level. This is because of the varying densities that are present in the Earth at different places. There are gravity anomalies with undulations differing from place-to-place.

Land and mountains prevent us from the seeing the geoid surface on the Earth. The Earth’s interior differs in density everywhere. This means that gravity varies everywhere on the Earth. This is why we measure gravity or the gravitational equipotential surface. We can then infer that this is how water would settle and model it mathematically. The geoid then gives a true zero surface for measuring elevations.

Reference Ellipsoid – The reference ellipsoid is a mathematical model of the shape of the Earth with the major axis along the equatorial radius. It approximates the geoid, but mostly coincides with geodetic network computations which point coordinates (latitude and longitude) are referred to.

National Geodetic Vertical Datum of 1929 (NGVD29)

Commonly used vertical datums in North America are the National Geodetic Vertical Datum of 1929 (NGVD29) and the North American Vertical Datum of 1988 (NAVD88).

The National Geodetic Vertical Datum of 1929 (NGVD29) (previously titled the Mean Sea Level Datum) was derived using 26 long-term tidal gauge stations and 1st order leveling stations constrained at mean sea level. These 26 tide gauges were set up in harbors along the east and west coast of the United States (and along the Gulf of Mexico. Twenty-one stations were in the United States and five in Canada.

Image Credit: NOAA
Image Credit: NOAA

During a twenty year period beginning in 1877, a “level line” was surveyed across the entire United States. As the network of level lines across the country expanded, this became the basis for the vertical datum.

NGVD29 was the system used by surveyors, engineers and mapping for most of the 20th century. But it was replaced by the more accurate North American Vertical Datum of 1988 because of its importance in floodplain management.

North American Vertical Datum of 1988

One of the main reasons for the change to NAVD88 was because the National Geodetic Survey (NGS) found that the sea was actually not level at all. There were local variations caused by wind, currents and topography of the sea bed.

The numbers didn’t fit because mean sea level was higher at one locations compared to elsewhere. Eventually, satellite technology found that these distortions were being caused by gravity.

Geoid NASA Grace Mission
Geoid from NASA’s Grace Mission – Image Courtesy of NASA/JPL

The North American Vertical Datum of 1988 (NAVD 88) is based on an adjustment of leveling observations from across the country. A highly accurate surveying technique called geodetic leveling was used to measure height differences across the country. The 1988 vertical datum was based on over 600,000 kilometers of control leveling. It also used satellite technology to improve on earlier vertical datums.

The tools for accurate elevation measurement have also remained fairly consistent over the years with the use of level rods and a sighting instrument to measure the height differences between two points. Today a laser may replace the use a telescope but the approach remains the same.

Eventually, satellites such as GRACE, GOCE paired with GPS technology found that these distortions were being caused by gravity. These satellite systems account for differences in gravitational forces in different areas.

Floodplain Mapping with the Vertical Datum

How likely is your home of flooding?

This is what organizations like Federal Emergency Management Agency (FEMA) are responsible for.

If we say that flood waters will rise 25 feet, what exactly is “25 feet” referenced to? We need a consistent starting point to compare flood and ground elevations. This is why consistent vertical datums and mean sea level are so important. Effective floodplain management depends on accurate surveying.

During a new construction, FEMA measures proposed structure elevations. They compare base flood elevations to ensure that new construction will be reasonably safe from flooding.

NGVD29 vs NAVD88
NGVD29 vs NAVD88

What’s important is that all survey points must use the same vertical datum throughout the survey. Differences in vertical datums can range from three feet or more in the Rocky mountains where gravitational forces are high… to a couple of inches in other areas.

NAVD88 corrects many of the problems with NGVD29. The 1988 vertical datum was based on over 600,000 kilometers of control leveling performed since 1929 and reflects geological crustal movements or subsidence that may have changed benchmark elevation.

If you were to perform surveys for floodplain mapping, up until recently most flood insurance maps used NGVD29. However, FEMA has made the switch to NAVD88.

Vertical Datum Transformation

What’s important is that when conducting a survey, all measurements must use the same vertical datum throughout the survey. Differences between NAVD29 and NAVD88 can range from three feet or more in the Rocky mountains where gravitational forces are high… to a couple of inches in other areas.

Rocky Mountains Geoid
Data Courtesy of NASA’s GRACE Gravity Model – Gravity anomalies in mountainous areas

A vertical coordinate transformation isn’t a simple plug-in-play formula. These transformations require software to transform to different vertical datums. The NAVD88 is a correction of thousands of control points of elevation datum.

VDatum is a free tool by NOAA to transform data among a variety of tidal, orthometric and ellipsoidal vertical datums. Users can convert their data from different horizontal/vertical references into a common and desired reference level.


A horizontal coordinate system gives us the side-by-side that is our latitude and longitude. A vertical datum is another component of your typical horizontal coordinate system.

Most vertical datums in North America use sea level as the basic reference plane from which we measure elevation changes. With mean sea level (MSL) as a reference point of zero, it is possible to measure height or topography accurately. We can also begin to understand if ocean levels are rising or falling over time.

We are on a three-dimensional planet which has ups-and-downs in addition to the side-to-side in a horizontal coordinate system on the surface.

To handle the ups-and-downs, we have the vertical datum which gives a place to put the zero measurement with mean sea level as the basis for our ups-and-downs. This is called the geoid.

A Complete Guide to LiDAR: Light Detection and Ranging


LiDAR Point Cloud

What is Light Detection and Ranging (LiDAR)?

How would you like to wave your magic wand and all of a sudden find out how far everything is away from you? No magic wands necessary. This is how LiDAR (Light Detection and Ranging) works – minus the magic wand.

LiDAR is fundamentally a distance technology. An airborne LiDAR system actively sends light energy to the ground. This light emitted is known as a pulse.

The LiDAR measures reflected light back to the sensor. This reflected light is known as a return.

So pulses of light travel to the ground. They return and are detected by the sensor giving the range (a variable distance) to the Earth. This is how LiDAR earned its name – Light Detection and Ranging.

That was easy.

But let’s dissect LiDAR a little more. What are LiDAR applications in GIS? What are LiDAR outputs? What are the components in a LiDAR system?

Today, we will demystify light detection and ranging. You will go from zero, to a LiDAR hero with this LiDAR guide.

READ MORE: Top 6 Free LiDAR Data Sources.

Sculpt laser-accurate outputs using LiDAR

Light detection and ranging is active remote sensing. This means the LiDAR itself sends a pulse of near infrared light and it waits for the pulse to return. This is different than passive sensors which collects reflected energy from the sun. Active sensors are very accurate because it’s being controlled in the platform.

LiDAR is a sampling tool. It has the brute force to send 160,000 pulses per second. It creates millions of points. Point density is usually less than one meter with accuracy of about 15 cm vertically and 40 cm horizontally.

Airborne Light Detection and Ranging (LiDAR)
Airborne Light Detection and Ranging (LiDAR)

A LiDAR unit scans the ground from side to side as the plane flies because this covers a larger area. Some pulses will be directly at nadir. But most pulses travel at an angle (off-nadir). So a LiDAR system accounts for angle when it calculates elevation.

Light detection and ranging is an exciting technology product with a variety of applications. What are some of the outputs from LiDAR?

1. Number of Returns

Imagine you’re hiking in a forest. You look up.

Forest LiDAR
Sunlight through Forest Canopy

If you can see light, this means that LiDAR pulses can go through too. This means that LiDAR can also hit the bare Earth or short vegetation. A significant amount of the LIDAR energy can penetrate the forest canopy just like sunlight.

But LiDAR won’t necessarily only hit the bare ground. In a forested area, it can reflect off different parts of the forest until the pulse finally hits the ground:

Using a LiDAR to get bare ground points, you’re not x-raying through vegetation. You’re really peering through the gaps in the leaves. LiDAR collects a massive number of points.

These multiple hits of the branches is the number of returns.

Number of Returns

In a forest, the laser pulse goes down. We get reflections from different parts of the forest – 1st, 2nd, 3rd returns until it finally hits the bare ground. If there’s no forest in the way, it will just hit the surface.

Sometimes a pulse of light doesn’t reflect off one thing. As with the case of trees, one light pulse could have multiple returns. LiDAR systems can record information starting from the top of the canopy through the canopy all the way to the ground. This makes LiDAR highly valuable for understanding forest structure and shape of the trees.

2. Digital Elevation Models

How do you build a Digital Elevation Model from LiDAR?

Digital Elevation Models are bare earth (topology) models of the Earth’s surface. You can derive Digital Elevation Models (or Digital Terrain Models) by using the ground hits from LiDAR. Ground hits are the last return of the LiDAR.

Digital Elevation Model

Sometimes the last return may not even make it to the bare ground. But for LiDAR, this is more rare than you think.

Which points are ground hits? There are ways to filter the LiDAR points. Take the ground hits (topology only) meaning the last returns from LiDAR.

Filter last return points. Interpolate. Build your DEM.

With a DEM, you can generate products like slope (rise or fall expressed in degrees or percent), aspect (slope direction) and hillshade (shaded relief considering illumination angle) maps.

READ MORE: Free Global DEM Data Sources.

LiDAR Digital Elevation Model
LiDAR Digital Elevation Model

3. Canopy Height Model (CHM)

Light detection and ranging attains very accurate information about the ground surface. We can also get very accurate information about what’s on top of the ground with a Digital Surface Model (DSM).

A Canopy Height Models (Normalized Digital Surface Model (nDSM)) gives you true height of topological features on the ground.

So how do you get true height of features on the Earth?

Take the first return including topology (tree, building). Subtract the last return which are the ground hits (bare Earth).

Canopy Height Model

For example:

The top of the tree height minus the ground height. Interpolate the result. You get a surface of features real height on the ground.

LiDAR Canopy Height Model
LiDAR Canopy Height Model

4. Light Intensity

The strength of LiDAR returns varies with the composition of the surface object reflecting the return. The reflective percentages are referred to as LiDAR intensity.

Light Intensity

But a number of factors affect light intensity. Range, incident angle, beam, receiver and surface composition (especially) influences light intensity. When the pulse is tilted further away, the return energy decreases.

Light intensity is particularly useful in distinguishing features in land use/cover. For example, impervious surfaces stand out in light intensity images. Object-based image classification segmentation can separate these features using light intensity values.

LiDAR Light Intensity

5. Point Classification

LiDAR data sets may already be classified by the vendor with a point classification. The codes are generated by the reflected laser pulse in a semi-automatic way.

Not all vendors add this LAS classification field. (It is usually agreed in the contract beforehand).

LiDAR Point Classification

The American Society for Photogrammetry and Remote Sensing (ASPRS) has defined a list of classification codes for LiDAR. Classes include ground, vegetation (low, medium and high), building, water, unassigned, etc.

Point classification may fall into more than one category. These points are usually flagged and have secondary classes.

LiDAR data is a rare, precious GIS resource

If you gave me a 5 second countdown to choose one GIS data type to work with for the rest of my life…. I’d probably start screaming LIDAAARRRRR!

Yes, I’d be all dramatic because you gave me a 5 second countdown to respond.

Light detection and ranging is accurate, large-scale and covers the most ground. You can understand bare ground elevation, canopy heights, light intensity and more. Anyone who is serious about understanding landscape topology should use LiDAR.

But LiDAR is a beast of a data set to work with. LiDAR is stored in LAS file format as a point cloud. This file format is maintained by ASPRS. The LAS format facilitates exchange between vendors and customers with no information being lost.

So where IS the LiDAR data? Where can you find sample LiDAR data?

Here is a list of the top 6 free LiDAR data sources for you to get a jump start on your search.

open topography webmap

Nothing is better than free.

But in most cases, you will have to purchase LiDAR data. LiDAR is generally flown commercially by helicopter, airplane and drone.

From ground to air, explore the types of LiDAR systems

1. Profiling LiDAR was the first type of Light Detection and Ranging used in the 1980s for single line features such as power lines. Profiling LiDAR sends out an individual pulse in one line. It measures height along a single transect with a fixed Nadir angle.

2. Small Footprint LiDAR is what we use today. Small-footprint LiDAR scans at about 20 degrees moving backwards and forwards (scan angle). If it goes beyond 20 degrees, the LiDAR instrument may start seeing the sides of trees instead of straight down.

Two types of LIDAR are topographic and bathymetric:
i. Topographic LIDAR maps the land typically using near-infrared light.
ii. Bathymetric LiDAR uses water-penetrating green light to measure seafloor and riverbed elevations.

3. Large Footprint LiDAR uses full waveforms and averages LiDAR returns in 20m footprints. But it’s very difficult to get terrain from large footprint LiDAR because you get a pulse return based on a larger area which could be sloping. There are generally less applications for large footprint LiDAR. Only SLICER (Scanning Lidar Imager of Canopies by Echo Recovery) and LVIS (Laser Vegetation Imaging Sensor), both built by NASA and are experimental.

4. Ground-based LiDAR sits on a tripod and scans the hemisphere. Ground-based LiDAR is good for scanning buildings. It’s used in geology, forestry, heritage preservation and construction applications.

You have x-ray vision using these LiDAR applications

LiDAR elevation points

Light detection and ranging is being used every day in surveying, forestry, urban planning and more. Here are a couple of LiDAR applications that stand out:

Riparian ecologists use LiDAR to delineate stream orders. With a LiDAR-derived DEM, tributaries become clear. It’s easier to see where they go far superior than standard aerial photography.

Foresters use LiDAR to better understand forest structure and shape of the trees because one light pulse could have multiple returns. As with the case of trees, LiDAR systems can record information starting from the top of the canopy through the canopy all the way to the ground.

If Google’s self-driving car got pulled over by the cops, how would it react? Self-driving cars use Light Detection and Ranging?. The first secret behind Google’s self-driving car is LiDAR scanner. It detects pedestrians, cyclists stop signs and other obstacles.

Archaeologists have used LiDAR to find subtle variations in elevation on the ground. It was a bit of a surprise when archaeologists found square patterns on the ground over vegetation. These square patterns were ancient buildings and pyramids by ancient Mayan and Egyptian civilizations.

READ MORE: 100 Remote Sensing Applications

LiDAR system components: breaking it down

How does a light detection and ranging system work? There are 4 parts of an airborne LiDAR. These 4 parts of a LiDAR system work together to produce highly accurate, usable results:

  • LiDAR sensors scan the ground from side to side as the plane flies. The sensor is commonly in green or near-infrared bands.
  • GPS receivers track the altitude and location of the airplane. These variables are important in attaining accurate terrain elevation values.
  • Inertial measurement units tracks the tilt of the airplane as it flies. Elevation calculations use tilt to accurately measure incident angle of the pulse.
  • Computers (Data Recorders) record all of the height information as the LiDAR scans the surface.

These LiDAR components cohesively make up a Light Detection and Ranging system.

Storage of the return: full waveform vs discrete LiDAR

Light detection and ranging return pulses are stored in two ways:

  • Full waveform
  • Discrete LiDAR

What are the differences between full waveform and discrete LiDAR systems?

Imagine that in the forest that LiDAR pulse is being hit by branches multiple times. Pulses are coming back as 1st, 2nd, 3rd returns. Then you get a large pulse by the bare ground return.

When you record the data as separate returns, this is called Discrete Return LiDAR. Discrete takes each peak and separates each return.

Discrete LiDAR

Light Detection and Ranging is moving towards a full waveform system:

When you record the WHOLE RETURN as one continuous wave, this would be called full-waveform LiDAR. Full waveform data is more complicated. You can simply count the peaks and that makes it discrete.

Full Waveform LiDAR


Light Detection and Ranging uses lasers to measure the elevation of features like forests, buildings and the bare earth.

It’s similar to sonar (sound waves) or radar (radio waves) because it sends a pulse and measures the time it takes to return. But LiDAR is different than sonar and radar because it uses light. This means LiDAR is an active remote sensing system.

The applications for LiDAR is stunning. It’s definitely growing in GIS.

Forest structure, archaeology, land use mapping, flood modelling, transportation planning, architecture, oil and gas exploration, public safety, automated vehicles, military and conservation. If we had a nickel for everywhere LiDAR is being integrated, we’d be Bruce Wayne rich.

We’ve broke down light detection and ranging with this LiDAR guide. You can now consider yourself a LiDAR guru.

A Topographic Profile of Arizona’s Massive Meteor Crater


Topograhic Profiles Feature

Topographic Profiles as Cross-sectional Views

Topographic profiles are cross-sectional views showing elevation along a line. In other words, if you could slice the Earth along that line and view it from the side, that two-dimensional graph displaying height would be a topographic profile.

Topographic profiles have different terms to describe them – vertical profiles, cross-section graphs or 2D elevation charts.

They also have different uses in engineering (like fiber optic cable design), hydrology (slope along a channel with a rise over run) and land use planning (ski slope design).

We’re going to show you how to construct topographic profiles using a DEM with the 3D analyst extension in ArcGIS.

Arizona’s Meteor Crater

All that force to make such an impact on Earth… Pretty incredible, isn’t it?

Arizona Meteor Crater
Map data @2016 Google Imagery @2016 Digital Globe (Arizona Meteor Crater)

For those who don’t know, this is the Meteor Crater, also known as Barringer Crater in Coconino County, Arizona (35°1′38″N, 111°1′21″W)

Staring at this thrusting impact from the meteor… you can’t help but wonder, how much impact did the meteor make into the Earth? Well, it’s tough to see looking from the top-down. Here’s how the Digital Elevation Model (DEM) looks:

Arizona Meteor Crater DEM

A 3D view could be helpful, but how about a vertical profile?

In order to graph out topographic profiles, you will have to enable the 3D extension. You’ll also have to add the 3D toolbar.

Toolbar 3D analyst

The interpolate line lets you draw a line to analyze the slope and create topographic profiles.

You’re going to start drawing a line where you want the elevation profile. We free hand the line across the meteor crater. Adding a bit of transparency for reference, here’s where our profile line will plot out the topographic profile:

Arizona Meteor Crater DEM Cross Section Line

Select the Profile Graph tool, and it looks like this:

Arizona Meteor Crater Topographic Profile

You can eyeball the topographic profile and estimate that it made about 150 – 170 meters of an impact into the Earth. Further to that, it’s about a mile or so wide.

Not the place you’d like to be standing when disaster strikes.

Now, It’s Your Turn to Create a Topographic Profile

You can do some pretty neat stuff with the 3D analyst tools. Generating cross-section lines and 2D graphs are just one of them.

A topographic profile of Mount Everest… Or even plot out a mountain near your home with these free global DEM data sources.

Simply, 2D graphs show height on the land.

They are cross sectional 2D views along a line drawn through a portion of a topographic map with tons of real-world applications.

GIS Spatial Data Types: Vector vs Raster

What GIS Data Types Exist?

Data consists of observations we make from seeing the real world. Spatial data consists observations with locations. Spatial data identifies features and positions on the Earth’s surface. Spatial data is how we put our observations on the map.

All GIS software has been designed to handle spatial data. Spatial data (also called geospatial data) is how geographic information is captured in a GIS.

Vector and raster data are the two primary data types used in GIS. Both vector and raster data have spatial referencing systems. These are latitudes and longitudes that pinpoint positions on Earth.

We know the two main spatial data models are vector and raster data. But what is the difference between raster and vector data? When should data be displayed as a raster or vector?

Let’s explore spatial data types in more detail:

Vector Spatial Data Types

Vector data is not made up of a grid of pixels. Instead, vector graphics are comprised of vertices and paths.

The three basic symbol types for vector data are points, lines and polygons (areas). Since the dawn of time, maps have been using symbols to represent real-world features. In GIS terminology, real-world features are called spatial entities.

The cartographer decides how much data needs to be generalized in a map. This depends on scale and how much detail will be displayed in the map. The decision to choose vector points, lines or polygons is governed by the cartographer and scale of the map.

Points as XY Coordinates

Vector points are simply XY coordinates. When features are too small to be represented as polygons, points are used.

For example:

At a regional scale, city extents can be displayed as polygons because this amount of detail can be seen when zoomed in. But at a global scale, cities can be represented as points because the detail of city boundaries cannot be seen.

Vector data are stored as pairs of XY coordinates (latitude and longitude) represented as a point. Attribute information like street name or date of construction could accompany it in a spatial database or table describing its current use.

Point Vector Data Type

Lines As Connected Points

Vector lines connect vertices with paths. If you were to connect the dots in a particular order, you would end up with a vector line feature.

Lines usually represent features that are linear in nature. Cartographers can use a different thickness of line to show size of the feature. For example, 500 meter wide river may be thicker than a 50 meter wide river.

They can exist in the real-world such as roads or rivers. Or they can also be artificial divisions such as regional borders or administrative boundaries.

Points are simply pairs of XY coordinates (latitude and longitude). When you connect each point or vertex with a line in a particular order, they become a vector line feature.

Networks are line data sets but they are often considered to be different. This is because linear networks are topologically connected elements. They consist of junctions and turns with connectivity. If you were to find an optimal route using a traffic line network, it would follow one-way streets and turn restrictions to solve an analysis. Networks are just that smart.

Vector Data Type Line

Polygons As Closed Lines

When a set of vertices are joined in a particular order and closed, they becomes a vector polygon feature. In order to create a polygon, the first and last coordinate pair are the same and all other pairs must be unique.

Polygons represent features that have a two-dimensional area. Examples of polygons are buildings, agricultural fields and discrete administrative areas.

Cartographers use polygons when the map scale is large enough to be represented as polygons.

Vector Data Type Polygon

Raster Spatial Data Types

Raster data is made up of pixels (also referred to as grid cells). They are usually regularly-spaced and square but they don’t have to be. Rasters often look pixelated because each pixel is associated with a value or class.

For example:

Each pixel value in a digital photograph is associated with a red, green and blue value. Or each value in a digital elevation model represents a value of elevation. It could represent anything from thematic categories, heights or spectral value.

Raster models are useful for storing data that varies continuously, as in an aerial photograph, an elevation surface or a satellite image. But it depends on the cell size for spatial accuracy.

Raster Cellsize

Raster data models can be discrete and continuous.

Discrete rasters

Discrete rasters are also referred to as thematic or categorical raster data. They have distinct themes or categories. For example, one grid cell represents a land cover class or a soil type.

In a discrete raster land cover/use map, you can distinguish each thematic class. Each class can be discretely defined where it begins and ends. Each land cover cell is definable. The land cover class fills the entire area of the cell

Discrete data usually consists of integers to represent classes. For example, the value 1 might represent urban areas, the value 2 represents forest, etc. Political boundaries or ownership are other examples of discrete rasters.

Discrete raster

Continuous Rasters

Continuous rasters are grid cells with gradual changing data such as elevation, temperature or an aerial photograph. Continuous data is also known as non-discrete or surface data.

A continuous raster surface can be derived from a fixed registration point. For example, a digital elevation model is measured from sea level. Each cell represents a value above or below sea level. An aspect cell value is derived from a fixed direction such as north, east, south or west.

Phenomena can gradually vary along a continuous raster from a specific source. For example, a raster depicting an oil spill can show how the fluid moves from high concentration to low concentration. At the source of the oil spill, concentration is higher. It diffuses outwards with diminishing values as a function of distance.

Continuous raster

Vector Data Advantages and Disadvantages

Did you know?

Spaghetti Data Model
Spaghetti Data Model

The spaghetti data model was one of the first conceptual models to structure features in a GIS. It was a simple GIS model where lines may cross without intersecting or topology and usually no attributes are created.

Vector Advantages:

Vector data is not made up of a grid of pixels. Instead, vector data is comprised of paths. This means that graphical output is generally more aesthetically-pleasing. It gives higher geographic accuracy because data isn’t dependent on grid size.

Topology rules can help data integrity with vector data models. Vector data structure is the model of choice for efficient network analysis and proximity operations.

Vector Disadvantages:

Continuous data is poorly stored and displayed as vectors. In order to display continuous data as a vector, it would require substantial generalization.

Although topology is useful for vector data, it is often processing intensive. Any feature edits requires updates on topology. With a lot of features, vector manipulation algorithms are complex.

Raster Data Advantages and Disadvantages

Raster Advantages:

Raster grid format is the natural output of choice of satellite data. Raster positions are simple. With cell size and a bottom-left coordinate, each cell position can be inferred.

Data analysis with raster data is usually quick and easy to perform. With map algebra, quantitative analysis is intuitive equally with discrete or continuous rasters.

Map Algebra

Raster Disadvantages:

Graphic output and quality is based on cell size. It can have a pixelated look and feel. Linear features and paths are difficult to display and depends on spatial resolution.

Networks are awkward with raster data. They are difficult to establish. Multiple fields with attribute data is difficulty and maps are often restricted to displaying a single attribute field.

Raster datasets can become potentially very large because a value must be recorded and stored for each cell in an image. This means that a soil map with 20 classes requires the same amount of storage space as a map showing only one value such as a forest. Resolution increases as the size of the cell decreases. But this comes at a cost for speed of processing and data storage.

Take Your Pick: Vector or Raster Spatial Data Types

Deciding which spatial data type should be used to model real-world features is not always straight-forward.

Sometimes the answer is simple:

Aerial imagery is only available in raster format. But there are many other features that can be stored as a vector or raster data type.

It really depends on the way in which the individual conceptualizes the feature to select spatial data types.

  • Do you want to work with pixels or coordinates? Raster data works with pixels. Vector data consists of coordinates.
  • Do you want to scale your features? Vectors can scale objects up to the size of a billboard. You don’t get that type of flexibility with raster data
  • Do you have restrictions for file size? Raster file size can result larger in comparison with vector data sets with the same phenomenon and area.

Spatial Data Structures

Spatial data types provide the information that a computer requires to reconstruct the spatial data in digital form.

In the raster world, we have grid cells representing real world features. In the vector world, we have points, lines and polygons that consist of vertices and paths. Vector and raster data have their advantages and disadvantages.

View Landsat 8 Imagery With Free Tool

Pentru cine e interesat de imagini satelitare Landsat 8.\

Users can search, view, and download Landsat 8 imagery with this free online web viewer developed by EOS Data Analytics.

Users can search for Landsat 8 imagery by geographic location or scene ID.  Imagery results are then easily browsable.  The results can be further filtered based on date of image acquisition, cloudiness and sun elevation.  The web browser is built using the open data archive Landsat on AWS (more: Landsat 8 satellite imagery available for free via Amazon Web Services).  Built using MapBox’s mapping platform and loaded with base layers from OpenStreetMap, the map browser also uses tile technology to rapidly render imagery scenes.  This technology also makes viewing data on tablets and smartphones possible.

Once the desired scene is selected, the user can then selected which bands to view.  EOS DA has developed technology that transforms the raw satellite imagery data stored in 16-bit GeoTIFF format on-the-fly into the displayed images.

EOS DA's Landsat 8 data viewer.

Exploring the different bands available makes for some interesting views.  For example, the North Sea’s water surface looks like a deep universe with a myriad of stars pan sharpen RGB:


This view of a valley in Kazakhstan looks like a painting:


Explore the Landsat 8 viewer and be sure to submit any feedback you have on the experience by clicking the submit feedback button located in the lower right hand column (right above the Twitter logo).

Visit: Landsat 8 Viewer

15 Amazing FREE GIS Software

O colectie foarte utila si interesanta de tool-uri FREE puteti gasi mai jos, sintetizata de cei de la monde geospatial.

Geographic information System (GIS) is a revolutionary Innovation which foundation was laid in the 20th century. It has transformed the way we perceive the concept of Map reading and spatial analysis. To put simply, GIS has revolutionized every facet of geography.  It has taken map analysis done on an A4 to the level of 2D and 3D analysis and adds excellent visualization.

In the most clear and concise manner, GIS is a tool or system designed to create, model, remodel, capture, analyze, store and capture information relating to map creation, representation of information on the map and various human activities. It also focuses on spatial analysis. Though GIS was designed for domains such as cartography and geography, its use has surpassed these domains. It has become a vital tool in the fields such as telecommunication and network services, urban planning, transportation planning, agricultural application and navigation.

To achieve all this, GIS software is utilized. GIS software is devised to plan, create, store, display, manage and scrutinize various forms of geographic data and spatial information. Sadly, professionals and students face difficulty getting most times due to licensing fee. However, this write-up hopes to end this conundrum for GIS software users. The following are fifteen free GIS software (open source application)


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QGIS is one of the foremost free GIS software. It was developed by the QGIS development team in 2002. It has become renowned for its unique tools for cartography design. The software is leading figure when it comes to map design, modeling and creation. The maps are made up of several layers of raster and vector layers.

It also has a straightforward user interface. It has a unique drop – down menu bar which contain features like Project, Raster, vector, Plugins and so on.

One amazing feature of QGIS is the GIS analysis tools. It has over 500 hundred GIS analysis tools. Some of them are the Raster tools, Vector tools, Domain specific tools and Image tools. The software is plugin enabled. It most powerful plugin tool is the Semi- Automatic Classification Plugin.

It runs on very popular operating system such as Windows, Linux, Mac OS X, and Android.


To download QGIS visit this link >>

grass gis 1

Grass GIS is free open source application GIS software.  It is used for map design, analysis, and image and graphics design. It also used for geospatial analysis and data management. It is equipped with tools to handle raster imaging, vector, topological imaging and temporal tools. It can handle all data relating raster and vector. It also has hi- tech network and satellite tools.

GRASS GIS is an efficient and capable tool for geographical and spatial analysis. This is the strength of the software. It is one of the most powerful GIS software. It possesses more than 300 vector and raster management tools. The raster, images, temporal tools and spatial data are presented in 3D imaging. Some of the satellite tools it possesses include vegetation indices and atmospheric correction.

It is also a powerful tool for modeling and remodeling of maps. Some modeling tools features are landscape patch analysis and hydrology.

One major downside of this software is that it is not the best for map creation and design. Its cartography features are limited and rigid.

A GRASS GIS runs on most popular operating system out there. It runs on Windows, OS X and Linux.

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To download GRASS GIS visit this link >>


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 Whitebox GAT is free open source software for GIS analysis. It was released in October 2009.  It was developed by the University of Guelph center for Hdyrogematics. It was originally designed for educational and research purposes for use at the center of Hydrogematics. However, the versatility and user-friendly graphics interface have made it a worldwide choice for GIS analysis.

Whitebox GAT is furnished with the latest geospatial tools and vector analysis tools. The graphic user interface (GUI) is top notch. With over four hundred analytical tools in the domains of vector analysis, map design and raster data management.

It has certain tools that make it unique such as: GIS tools for cost- distance analysis, multi-criteria evaluation and clumping. Its imaging processing tools are NDVI, contrast enhancement and numerous spatial filters. Its hydrology tools are: max flux analysis, watershed extraction and DEM preprocessing tools.

The latest version of the software was released 27 January, 2017. It is equipped with raster and vector data analysis technology. It supports multiple scripting languages such as Python and JavaScript.

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To download WHITEBOX GEOSPATIAL ANALYSIS TOOLS visit this link >>

terraview 1

TerraView is a free GIS software application built under the platform TerraLib GIS Library.  TerraView allows for vector data and raster data (grids and images).  Vector data and raster data are stored in relational or geo-relational database. TerraView allows vector operations including intersection and buffer maps.  All information is stored in MySQL and ACCESS.

Terra view has quality visualization interface. The interface gives room for several views on databases and producing thematic maps.

Terraview also has statistical functions such as semivariograms and regionalization.

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To download TerraView visit this link >>

saga gis 1

 SAGA (System for Automated Geoscientific Analyses) GIS was developed specifically for geoscientific purposes initially.  It was developed by a pack of brilliant researchers from the University of Gottingen. They focused the uses mainly geoscientific standpoint. However, it has evolved into multipurpose GIS software.

The best feature of this software is the top notch geoscientific analysis tool.  It is the perfect tool for terrain analysis such as hillshading, watershed extraction and visibility analysis. One amazing feature of the software is the 3D imaging enablement. The color setup of the software also makes viewing credible. What makes the 3D imaging even better is the presence of an Anaglyph tool. It makes images look real life situation.

Another arsenal of SAGA GIS is the geostatistics tools. It has a large of geostatistics tools for complex statistical work. It is perfect for statisticians. It delivers analysis in regression technique, semi- variogram technique. Meridional and longitudinal grid statistics are also very useful tools in the software.

Morphotery tools are also available. It can be used to measure the wetness index of place. One weakness of the software is Lack of excellent cartography tools for modeling and remodeling. It is not the best for map design and editing.

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To download SAGA GIS visit this link >>

6. gvSiG
gvsig 1

This GIS Software came into the spotlight in 2004. It originated from Spain. Ever since then, it has been growing in leaps and bounds. GVSIG commands the best 3D imaging software for GIS. Combining NASA’s world wind SDK, the 3D output is breathtaking.

Another powerful feature is sophistication of the mobile version. The mobile version of this software allows user to collect real time data such as the amount of rainfall in a place. It also has maps to navigate anywhere in the world.

As CAD and GIS are starting to synch together, gvSIG as state of the art tools such as tools to trace geometry, edit vertices, and polygons.

It is also imbued with remote sensing. It has a tool dedicated to vegetation (Agriculture). It has tools powerful enough to monitor chlorophyll in plants.

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To download gvSIG visit this link >>

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ILWIS (Integrated Land and Water Information System) was developed by ITC Ecschede in Netherlands. It is mostly used by researchers in the field of biology, geospatial analysis and water planning management.

ILWIS is useful in Geostatistical analysis backed with kriging for improved interpolation. It is imbued with state of the art raster and vector design.

It is able to handle advanced modeling and spatial data analysis. Its image processing is detailed and encompassing. It is not just encompassing, it is backed with 3D visualization and powerful zooming features.

It manages data very well. It runs only on Windows.

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To download ILWIS visit this link >>

kalypso 1

Kalypso is a GIS tool developed by Bjorsen consulting Engineers (BCE) and department for rivers and costal engineering at Hamburg University.

As an open Source software, it was developed specifically for numerically projections and calculation in water management.

It also has tools for hydrodynamic models. It handles data on flood depth determination, flood risk determination. It also has a very user- friendly interface.

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To download Kalypso visit this link >>

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uDig (User Friendly Desktop Internet GIS) was developed by Refraction Research, a Canadian based company.

It has an outstanding user- friendly interface. Its drag and drop UI is one of the unique features.

It offers quality web mapping technologies such as KML, GEORSS, WMS and WFS.

From the standpoint of editing tools, the software offers salient or basic editing tools of GIS software. uDig can also handle some complex vector operation. The spatial toolbox can be activated manually with the aid of GRASS.

It has been used as a platform for creating various GIS applications including DIVA GIS.

It is written in JAVA language. It runs on various operating systems such as Windows, Mac OS X, and Linux.

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To download uDig visit this link >>

mapwindow 1

Mapwindow GIS is GIS software developed by Mapwindow open source item. Mapwindow GIS supports data analysis, maneuvering of geospatial analysis. It also has a unique mapping and GIS modeling System.

The user interface is easy to navigate. The layouts are simple and straightforward. The zooming capability is top notch.

It also supports various file formats. It allows for easy importation and exportation of files. You can import file format such as ASC, BIL, IMG, FLT, DHM, JPG and PNG. Created maps can be saved in series of formats such as GIF, EMF and JPG.

The shapefile editor allows user to view the features of shapes in the target layer, defining shapes as well as create and edit shapes files

It has a geoprocessing facility for helping to activate several raster operations. It runs only on Microsoft Windows.

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To download Mapwindow GIS visit this link >>

geoda 1

Geoda is open source GIS software. It is a powerful tool for spatial data analysis and geovisualization. It is a useful tool in geostatistics. It employs tools such as histogram, scatter plots to conduct exploratory analysis of the data in geostatistics.

It has a world class tools to perform global and local spatial regression. It can also handle basic linear regression.

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To download Geoda visit this link >>

flacon view 1

Falcon View is geospatial software developed by Georgia Tech Research Institute. It supports and displays various types of map format. However, it is most suitable for aeronautical charts, maps, satellite images and elevation maps.

Falcon View is flight planning management software. It is used by the US department of defense and National Geospatial Intelligence Agencies.

Falcon View supports 3D. The 3D enablement improves visual for surface missions. The software has a sky view mode.

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To download Falcon View visit this link >>

13. Jump GIS
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Jump GIS is active open source software written in JAVA language. It supports vector and raster GIS framework. The software reads various file formats. Some of them are: ESRI Shapefile, GML, and DXF. It also reads various file formats in raster such as TIFF, JPEG, PNG and BMP.

It has plugins for editing, printing, spatial analysis, GPS and databases. It is now known as Open Jump GIS.

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To download Jump GIS visit this link >>

Diva-GIS 1

DIVA-GIS is a free and open source geographic information system (GIS) to make maps of species distribution data and analyze these data. DIVA-GIS was specifically developed at CIP for use with genebank data such as available through national or international genebank documentation systems and SINGER.

It consists many useful tools such as Grid Calculator (multiplying, adding rasters), Neighbourhood ( changing raster resolution) and Georeference Image. DIVA-GIS also has an Ecological Niche Modeling tool which can be used to predictive modeling ( it uses Bioclim and Domain algorithms).

From DIVA-GIS desktop one can directly connect to DIVA-GIS Free GIS Data site and download climate grids, DEM, sattelite images or country level data.

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To download DIVA-GIS visit this link >>

15. Capaware


Capaware  is a framework for developing 3D multilayer geographical worlds. It is a free software project which began in 2007, released for the purpose of promoting the development of free software in the Canary Islands by its Government.

Capaware allows interaction with 3D virtual terrain mapping, and is distributed under license GPL.

Capaware, which is developed in C++, allows connection to external servers using OGC protocol to obtain data. We can also configure and manage the resource layers and elements that can be displayed on the ground.


To download Capaware visit this link >>