How to read the landscape around a point, one layer at a time
One click on the map, and Naturametrics draws five circles around it and reads fifteen crop
inventories, the age of every forest stand and twenty-five years of tree-cover loss inside each. This walkthrough opens
a real point in the forest above Kelowna, step by step, with where each number comes from and where it stops.
Loading the example point's analysis…
—age of the forest stand at the point, 2019 estimated
—of the 5 km circle is forest
—of tree cover lost within 5 km since 2001
—the worst year for loss within 5 km
measured computed from satellite imagery or from the geometry itself.
estimated a modelled product, with a larger error than the land-use map.
missing a layer that did not respond this time.
1
It all starts from a point
Naturametrics does not need a property line. A click, an address, a postal code or a coordinate is enough: the
analysis is built around the point, so it works the same on a farm, a park, Crown land or a backyard.
In the app: the Search box on the Canada page, a click on the map, or a direct link with
/canada?lat=…&lon=….
2
Five circles around the point
Every analysis runs five times, in circles of 0.5, 1, 2, 5 and 10 km. The small ones say what is at the point; the
large ones, what the landscape around it is like. Each circle contains the smaller ones, so the 10 km circle is the
whole picture and the 0.5 km one is the close-up.
In the app: the Radius selector above the charts, and the circles on the map.
3
Fifteen crop inventories in one circle
Agriculture and Agri-Food Canada's Annual Crop Inventory classifies every 30 m pixel each year, forests and towns as
well as crops. Each column is one year in the 5 km circle, from 2011, when the inventory first covered all of Canada.
In the app: the Crop inventory history chart, and the Annual Crop Inventory layer with its year selector.
4
Near and far tell different stories
The same series as the share of each circle that is natural vegetation: forest, wetland, grassland and shrub. When
the small circles stay green and the large ones fall, the point sits in a remnant inside a changing landscape.
In the app: the Crop inventory history chart with the % button, changing radius.
5
The point's own pixel, no averaging
Before any circle, one pixel: the 30 m square under the click, year by year. It is the sharpest reading and the most
fragile, because a single misclassified year shows up as a change.
In the app: the clicked pixel's class, year by year, is the first sheet of the point spreadsheet (Download data).
6
How old the forest is
The national forest monitoring system (NTEMS, Canadian Forest Service) maps the age of every forested 30 m pixel
in 2019, from three decades of Landsat disturbance and regrowth. Young stands are the ones that burned or were logged;
stands over a century old are what was left standing.
In the app: the Forest age chart, Age at the clicked pixel, and the Stand age layer.
7
Tree cover lost and gained, circle by circle
Hansen/GLAD maps the 30 m pixels that lost their tree cover each year since 2001, and flags, without a date, the
ones that gained it. Counting canopy above 30% as forest, the loss in each circle is set against the forest it had in 2000.
In the app: the Forest change chart, the Loss and gain layer, and the Forest threshold control.
8
The years that stand out
Loss by year, inside the 5 km circle. In the Okanagan, a tall column is almost always fire or salvage logging after
fire. Hansen dates a pixel by the year the loss was first seen, so a late-summer fire often lands partly in the next year.
In the app: the Forest change chart, and Loss from year on the layer.
9
Everything on screen, in one spreadsheet
Each analysis keeps its source, scale and time of calculation, and the export carries them with the numbers: a reading
of a landscape is only worth what it takes to reproduce it.
In the app: the Download data button: an ODS spreadsheet with one sheet per table.
naturametrics.umaterra.com.br/canada
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Loading the example point…
What Naturametrics does not say
It does not tell you why the forest changed. Fire, logging, pests and building all look like loss to a
satellite; the cause is for the forest record or a visit.
It does not date a stand exactly. NTEMS age is a model built from Landsat since the 1980s; stands older than
that are estimated, and the oldest class is open-ended.
It does not count carbon. Area and age describe the landscape; a carbon figure would need an inventory and
growth curves the tool does not have.
It cannot see below 30 m. A narrow riparian strip or a backyard grove is a few pixels at most.
The three UmaTerra tools differ in who draws the boundary they analyse: the state (Indigenous lands
and conservation units), the landholder (a cadastre) or the analyst (a point on the map). Naturametrics is the
analyst's tool: it draws no boundary at all, only circles of fixed size, so two points anywhere are compared on equal terms.
Biondo et al., Registry, coordinate, cadastre (manuscript in preparation, 2026).
Hansen/GLAD records a year, not a date: a pixel is booked in the first year its loss is detected in the
annual Landsat composite. A fire in August can therefore spread its loss over that year and the next, and the two
columns should be read together.
Hansen et al. (2013), Science 342, 850–853.
Every area on this page is a pixel count times the true pixel area, measured on the same grid as the
count. Canada spans 41° to 83° N, and a flat 0.09 ha per pixel, or a grid mismatch, drifts by a third at Kelowna's latitude.
Biondo et al., Registry, coordinate, cadastre (manuscript in preparation, 2026).