# Tag Info

16

The idea with hexagons is to reduce sampling bias from edge effects of the grid shape, which is related to high perimeter:area ratios. A circle is the lowest ratio, but cannot form a continuous grid, and hexagons are the closest shape to a circle that can still form a grid. Also, if you are working over a larger area, a square grid will suffer more from ...

14

One of the benefits, that I've seen when doing wildlife or habitat modelling especially, is that hexagons allow patterns in the data (ex, edge of a field or any other patch) to be seen more easily than what squares would of offered. Think of a soccer ball too, though not always hexagons, those geometric shapes fit to a curved surface quite nicely. In your ...

11

Actually it's not all that situation dependent and is all about statistical error. Any time you resample to a higher resolution, you are introducing false accuracy. Consider a set of data measured in feet at whole numbers only. Any given point may be +/- 0.5 feet from its actual location. If you resample to the nearest tenth, you are now saying any given ...

8

The hexagon is the most complex regular polygon that can fill a plane (without gaps or overlap). I can see two advantages: It is closer to a circle than the square in terms of shape index, so you suffer less from orientation bias. The "length of contact" is the same on each side (with a square, the neighbours include the four squares at the corners). ...

6

I found the solution! arcpy.Describe object can easily handle this. Here is the example same for feature and raster: buildings is a Shapefile layer, dem is a TIFF layer and added in ArcMap feature = arcpy.Describe("buildings") print feature.extension output message : shp raster = arcpy.Describe("dem") print raster.extension output message : tif

5

Use os.path.splitext() import os filename, ext = os.path.splitext(r'C:\temp2\out\fc10.shp') print ext

4

from GRASS GIS: v.buffer: -c Don't make caps at the ends of polylines from the interface of v.buffer.distance in QGIS (Processing Toolbox): from the interface of v.buffer.column in QGIS (Processing Toolbox): or use GRASS GIS directly and not the GRASS plugin (as says zimmi)

4

You can use Data Driven Pages to quickly loop through each feature of your feature class. Within the settings you can set up what % you want to zoom to - i.e. 100% will have the feature fill the screen, but you might want to try something like 150%. This tool, although designed to make maps, is also useful for inspecting features quickly.

4

there are a few examples of animal counting by remote sensing (whales, gnu, crocodiles, seals...), but they used higher resolution satellite images (<1m) or aerial photographs (see this paper) and there was a clear spectral difference with the background (sometimes in UV or infra-red)). As a rule of thumb, you should have around 10 pixels to detect an ...

4

A key disadvantage of grid squares is that the sample rate is substantially lower along the diagonal vectors to those of the four sides (Jasons point above). If you have some regular linear pattern to your data the orientation of the grid affects the effective sample rate of each context. For example if you have a series of ridges and valleys, orienting ...

4

It's important to note the job titles associated with positions that supersede GIS Technician or GIS Analyst. You won't (hopefully) find too many job postings looking to hire for a GIS Analyst position with the requirement of 10 years of experience. After 5-8 years as a GIS Analyst you would likely start looking to transition to a GIS Coordinator/GIS ...

4

GIS is still a relatively new technology, despite its exploding popularity and application potential, and so it will take time for HR to understand exactly what GIS is for, what a GIS "Analyst" does, and what they should be paid. However, if they see data from reputable national organizations that indicate higher pay is typical (and they will therefore ...

3

ArcGIS has a few tools in the Spatial Statistics toolbox that might be useful. Mean Center Identifies the geographic center (or the center of concentration) for a set of features. Median Center Identifies the location that minimizes overall Euclidean distance to the features in a dataset. Central Feature Identifies the most centrally ...

3

In order to get at the classes you describe, you will need to incorporate a sophisticated classification algorithm and ancillary data derived from the imagery. I would recommend two approaches: 1) an object-oriented image segmentation (IS) approach using IS software such as eCognition or 2) a pixel-based non-metric, decision tree (Random Forest) approach ...

3

Yes, you can add further info, such as the coordinates of intersection points, editing the attribute table and calculating the coordinates with the field calculator using the geometric functions \$x and \$y.

3

I would use Python's itertools and a SearchCursor for a very efficient way to find the spatial relationships you are after. You can incorporate the geometry methods overlaps, contains, and equal to get at the geometry properties. Start off by creating a function to better organize the workflow and for repeatability def findOverlaps(x): Open a search ...

3

Calculate the intersection (i.e. overlap) between the two layers (Vector > Geoprogressing Tools > Intersect...). Use the drop down menus to select the two layers, and specify a location to save the output shapefile. The resulting layer will have attributes from both input layers (e.g. "actual cover" and "target cover"). You can then filter this layer ...

2

This is a bit old, but I was searching for solutions to this problem today (point --> line). The simplest solution I've come across for this related problem is: >>> from shapely.geometry import Point, LineString >>> line = LineString([(0, 0), (1, 1), (2, 2)]) >>> point = Point(0.3, 0.7) >>> point POINT (0.3000000000000000 ...

2

I have used this kind of socio-economic data for a number of projects. It can be very helpful to break out of the district polygons by laying a square grid over the area (side length based on either metres or minutes), and then using a script, calculate a score for each grid cell (e.g. if a grid cell straddles two districts, then calculate a cell value ...

2

I have an idea what may work for you. It is going to be based off some assumptions, but it would help narrow down your list of possible identical features. This would not be an automated process, but it would require manually looking at the duplicates. Based off the comments, it seems like the automated tools don't compare attributes so this would help ...

1

The Topology Checker plugin is a good tool if used correctly. You still have to have a fundamental understanding of your data AND you have to make the 'corrections' manually. The plugin will highlight what it thinks are errors. It is up to you to then examine each and make the appropriate decision for you and your data. With 90 000 items in your layer, you ...

1

You can do this in SQL using a spatial self join. You don't state which SQL dialect you are using, so this example uses Postgres/Postgis, but it could be easily adapted to Oracle or SQL Server. Assuming a table called buildings, with geometry stored in a column called geom: SELECT a.id, b.id from buildings a, buildings b WHERE ST_INTERSECTS(a.geom, ...

1

in QGIS, Topology Checker plugin can propably solve your problem

1

Frequency and summary statistics were definitely present in version 9.2, frequency has been around since I've been using ESRI products (early 1990's). Summary Statistics offers more powerful statistic types over frequency, and can work with a basic license (ArcView) where frequency needs advanced (INFO) license. Same with Intersect, Identity and Union, ...

1

To aggregate the clusters use grouping which produces a field SS_GROUP then for each unique SS_GROUP in the feature class create a convex hull then use Feature to Point to obtain the centroid of that particular cluster, with polygons you can specify inside to guarantee that banana shaped polygons produce a centriod that is inside the polygon but that wont ...

1

One fast way for doing visual analysis is to use DEM as starting point and classify it with pseudocolors. You can edit the class ranges and colors etc. to suit your needs. For further analysis you can use the raster calculator. The next screen capture shows how to make a black/white image where pixels with height<10 m are white and pixels above 10 m ...

1

In my experience, satellite imagery, even high resolution, has not been too effective in tracking caribou, and the best option in applying landsat or other imagery is to use predictive habitat models derived from gps tracking, or directly utilize gps tracking. Landsat based landscape classification provides a very good basis for where to go looking for ...

1

You can create borders by using Polygon to Line tool for each polygon. Then use Near tool on these two borders.

1

This has nothing to do with the amount of data. This is an error caused by NULL values in your data. This should be considered a bug. Please open a ticket for this.] This has been fixed in commit f9e0093. Unfortunately just a bit too late to hit QGIS 2.2.0. It would be very nice if you could test this fix (e.g. with tomorrow's master build) and give a ...

1

The arcpy way of doing this would be the following logic: Referencing Gerry Gabrisch Create Perpendicular Lines to Each Segment of a Shapefile and this Q/A you can create perpendiclar transects at the start and end point of each line segement. The transect feature class may then be used to split the buffered layer using the python logic that @iRfAn has ...

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