Dear colleague,

I attach an awesome article about your question. I hope this helps.

Check at the book "Análise da Paisagem com GIS" authored by Stefan Lang & Thomas Blaschke, Oficina de Textos Ltda., São Paulo/Brasil, 2009.

The book mentioned brings an exhaustive discussion on landscape metrics, FRAGSTATS and related issues. It has several exercises which can be easily adapted to your area under study.

A specialist in Landscape Metrics since he made his PhD in that field is Prof. Jan Bogaert form the University of Liège.

A direct access to a (pretty) complete list of landscape metrics is given by FRAGSTATS. See http://www.umass.edu/landeco/research/fragstats/documents/Metrics/Metrics%20TOC.htm

Prof. Bogaert added new metrics to the fragstats list. His email is:

[email protected]

Cheers,

Frank

Thank you for all your answers! I'm looking for something conveniently "encyclopedic", and the Fragstats help/manual does seem to be the closest, although there might be more beyond what it implements. They say that version 4.2 will also have continuous surface metrics and cell metrics, so I guess we can expect that soon the help/manual will also become even more complete.

Ok, they seem to already describe metrics not yet apparently implemented, like the Linearity Index. Thank you again.

Dear colleague,

I attach an awesome article about your question. I hope this helps.

Thank you, Carles, this does look interesting.

Here there are a couple of articles that might be interesting:

- Peng et al 2010. Evaluating the effectiveness of landscape metrics in quantifying spatial patterns.http://www.sciencedirect.com/science/article/pii/S1470160X09000843

- Sundell-Turner and Rodewald 2008. A comparison of landscape metrics for conservation planning. http://www.sciencedirect.com/science/article/pii/S0169204608000467

And in case you are looking into spatially implementing some of the landscape metrics, this article can be also of interest (offers 40 metrics):

- Zaragozi et al 2012. A free and open source programming library for landscape metrics calculations. http://www.sciencedirect.com/science/article/pii/S1364815211002209

Thank you, María, I will check these out.

Meanwhile, I found something:

There is or was a group and/or project named LARG (Landscape Analysis and Resource Management Research Group), I believe from the Z_GIS, University of Salzburg, that has made a database of indicators, which is named IDEFIX, and apparently has about 82 metrics. There are other three tools (which seem to be extensions for ESRI products). They are downloadable.

-> https://sites.google.com/site/largvlate/home

(This is a google site, I don't know why)

Hope it's helpful.

P.S.

-> María Piquer-Rodríguez:

The 3rd paper you linked mentions one of these austrian tools (V-LATE)!

Considering the previous answers to your question, I suggest two recent papers focusing on trends of their use in landscape research that could be useful.

The first one is published in an open access journal:

http://landscaperesearch.livingreviews.org/Articles/lrlr-2009-1/

The second one is more recent and follows this interesting analysis presented in 2009 in the first one

http://www.sciencedirect.com/science/article/pii/S1470160X1200283X

Thank you, Giuseppe.

You may also want to take a look at:

Third-order geomorphometric variables (derivatives): definition, computation and utilization of changes of curvatures

Jozef Minár, Marián Jenčo, Ian S. Evans, Jozef Minár, Martin Kadlec, Jozef Krcho, Jan Pacina, Libor Burian, Alexandra Benová

International Journal of Geographical Information Science

Vol. 27, Iss. 7, 2013

Hi Joao,

I also attach a little article based on the really highly integrative work of Susanne Frank. Maybe you can contact her under [email protected]

Yours

Christine

Sorry - here now the attachment...

To look for something really new in quantification of landscape structure see "Landscape patterns from mathematical morphology on maps with contagion" from K.H. Riitters et al. Landscape Ecol, Vol. 24: 699-709.

-> Bharath: Interesting Applications, Thank you.

-> Sytze: Thank you for bringing up the z-axis (no pun intended)!

-> Christine: Thank you so much. 'Pimp Your Landscape" is absolutely the funniest keyword I have ever seen!

-> Giovanni: Thank you, I wasn´t aware of MSPA.

-> Giuseppe: Double Thanks

Hi Joao,

Re MSPA, we recently publish an application study on fragmentation and connectivity in SE of Spain where we used MSPA:

http://www.sciencedirect.com/science/article/pii/S1617138112000647

Hope is of your interest!

Maria

Thank you María, really nice application. Isn't this still iberian lynx territory? That could be an incentive for conserving areas that may be of not a huge interest themselves, but contribute to connect others. J

The Iberian lynx territory is located more to the west of Andalusia (SW of Spain). The south-east of Spain is far too arid for this emblematic species. But in this regard, and as you point out, conserving sites that seem to hold low biodiversity today but are highly connective is also a very interesting strategy in terms of species adaptation to future global changing conditions. Best, Maria

Riitters, K. H., O’Neill, R. V., Hunsaker, C. T., Wickham, J. D., Yankee, D. H., Timmins, S. P., Jones, K. B. & Jackson, B. L. (1995). A Factor Analysis of Landscape Pattern and Structure Metrics, Landscape Ecology, 1(1), 29-36, is the best collection of landscape metrics I've ever seen. The article does factor analysis on 55 different landscape metrics.

Thanks Charles. I would like to report that the article quoted above and most of the research conducted afterwards indicate that out of 55 apparently different landscape metrics only few are carrying really independent information. Therefore, not all 55 landscape metrics are useful. Most authors reduce such complexity of metrics to 1) composition (how much is there) and 2) configuration (contagion) (how it is spatially arranged).

Giovanni, that's why I really liked Riitters et al so much. Their factor analysis determined that (#s off the top of my head) five metrics accounted for 80ish% of the variability for the 55 metrics they identified from previous literature. So, if you don't know what metrics are best for a novel application, you'll know which five will give you a pretty good understanding of landscape variability for that application.

-> Charles, Giovanni: Thank you.

Something on a similar line seems to be:

Cushman, McGarigal and Neel (2008) Parsimony in landscape metrics: Strength,

universality, and consistency. Ecological Indicators 8, 691–703.

They mention the existence of over 100 metrics of landscape structure

at class and landscape levels, go on to evaluate the redundancy of

49 class-level and 54 landscape-level metrics, and reduce them to 24 and 17,

respectively.

This is far more than five, which they attribute to the use of newer metrics in their study, "including 'patch dispersion', 'similarity', 'area–weighted mean proximity index', 'variability in shape complexity', and 'correlation length' among others".

J

I would add, have a look at the FRAGSTATS manual (Kevin McGarigal's web site, http://www.umass.edu/landeco/research/fragstats/fragstats.html). It lists and calculates several hundred metrics and provides a good account of how to calculate each one and what it measures.

Thank you Graeme. That had already been suggested by Alessandro and Frank, though (see above).

Apologies, didn't read the earlier posts that were hidden on my screen!

Just a brief comment on connectivity that is a caveat for a possible list of landscape metrics to be chosen. A widely accepted goal of conservation is to build a conservation network that is resilient to fragmentation and environmental change. However, fragmentation is a relative concept as well as connectivity. Effective corridors should provide suitable and reliable connectivity among habitats across scales for species mobile or less mobile for gene exchange under uncertainty and change. However, often a "static" vision of landscapes is adopted (i.e. the cartography of land uses/covers) whereas landscapes (habitats included) are dynamic. Indeed, they do change either under different seasonal conditions, or under multiple driving forces like, for instance, climate change. As a result, what we are looking for, i.e. fragmentation or effective corridors, can systematically change on the map, and what is fragmented or suitable as corridor under certain conditions could not be suitable or fragmented when season, conditions or the set of focal species are changed. Just because we are not so good in predicting the future and what could be a suitable network sustaining biological diversity and gene exchange, we have to rely on past time series (at a suitable scale) to define the trajectory of every landscape piece to see whether it is predictable or not, that is, if it is persistent or not. Once you get a "predictability" map then you can think of choosing landscape metrics or applying different modelling tools like graph-based measures of connectivity to derive, under uncertainty; what possibly could be an effective corridor network and a suitable fragmentation for the future. So you could discover that along with "classical" green and blue ways other elements in the landscape could be crucial for the network based on their predictability. You could also discover which unpredictable landscape pieces are crucial for the maintenance of the overall connectivity in the face of climate change and try to transform them in "persistent" through planning and management efforts. See, for instance, the paper "Highlighting order and disorder in social–ecological landscapes to foster adaptive capacity and sustainability" recently appeared in Landscape Ecology.

The same principle should be applied to fragmentation/connectivity for marine systems (see Modeling population connectivity by ocean currents, a graph-theoretic approach for marine conservation appeared in Landscape Ecology). Indeed, for many marine species, population connectivity is determined largely by ocean currents transporting larvae and juveniles between distant patches of suitable habitat. So, connectivity relies on the persistence of ocean currents suggesting areas that might be prioritized for marine conservation efforts and that are working like "stepping stones" in the maintenance of the overall network. On the other hand, you might identify "new" candidate stepping stone areas in case of predicted changes in the oceanic current pattern due to climate change. Unfortunately most of marine biologists and ecologists involved in marine conservation do not consider the importance of ocean currents.

Another similar thread that may be of interest to those following these one:

https://www.researchgate.net/post/What_is_the_best_GIS_tool_to_calculate_habitat_connectivity_in_the_landscape?cp=re65_x_p2&ch=reg&loginT=gSV-btbMJT3UYrjKz85sF8U2MMbtqWgqCg6Vfy2XKsc%2C&pli=1#view=528b4d34d2fd64e7718b4649

Hi Joao,

I recently read the new paper by Fahrig (2013) and thought that , although maybe a bit off topic, could be interesting for you to take into consideration- she is moving beyond the variables patch size and isolation towards a new hypothesis of habitat amount in the local landscape around a patch when looking into relationships species richness- habitat distribution.

Cheers,

Maria

We have developed a software for most useful indexes (if needed we could implement some additional).

What is important: it's free and it works on georeferenced rasters and vector files (output is naturally also georeferenced).

here you can find it:

http://zoz.cbk.waw.pl/index.php/en/software-en/incsim

Michał

Hi!

This paper has a nice list of different LM:

Šímová, P., Gdulová, K., 2012. Landscape indices behavior: A review of scale effects.

Applied geography, 34, p. 385–394.

DOI: http://dx.doi.org/10.1016/j.apgeog.2012.01.003

Rok