Hi, I can recommend ImageJ. It is freeware and pretty straightforward to use. 

Please have a look at these links for more information:

https://www.researchgate.net/post/Can_anybody_explain_how_to_findout_leaf_area_in_cm2_using_ImageJ_or_any_other_software

https://www.researchgate.net/post/Can_someone_please_walk_me_through_ImageJ_for_leaf_area_analysis

http://ucanr.edu/sites/fruittree/files/49325.pdf

https://imagej.nih.gov/ij/docs/pdfs/examples.pdf

Koenraad

Hello, I have use the GRASS GIS software to estimate LAI from a fish-eye photo image. It is free.

For details, refer to the following URL:

https://grass.osgeo.org/

Tomoko Akitsu

You can use GRASS GIS available on https://grass.osgeo.org/... 

I appreciate your useful information.

http://regent.qc.ca/assets/winfolia_about.html 

if you have not checked winfolia please do

Thank you,Dear Byambagerel Suran

I used ImageJ software in my project. It was good, but I could not get the means straight. There was not a bad experience at all

What about Hemisfer? is it reliable?

you can also use Hemisfer software

Finally I think the digimizer software is good too.

but i am not sure about hemisfer. it has totally difference usage.

Thank you all.

Leaf area index (LAI) is the projected surface area of leaves per unit ground surface area. More details can be found in literature and Wikipedia helps too (https://en.wikipedia.org/wiki/Leaf_area_index).

If you have to measure projection area of leaves or needles, then the approach is probably to scan them using flatbed scanner and then classify the image pixels as target and background and count pixels. You need also a reference measure of pixel size. There are probably many software programs that provide such classification and pixel counting functionality.

It is impossible to measure LAI for canopy or plant from photographs. The useful quantities measured from photographs are canopy gap fraction and gap size distribution. LAI has to be then predicted using canopy gap fraction or gap size distribution data and a model.

Dear Dr. Mait Lang

you must try digimizer software. Maybe to change your opinion. of course, you need a reference for measurement. So you must put the ruler in the picture beside the leaves before taking the photo.

Definitely the meaning of the photo is the image that the user takes in the laboratory to speed up. And not the images are taken from the scenery.

I would be happy to know more about your valuable comments in this regard.

Sincerely,

As Mait properly said, I guess you are interested in estimating (specific) leaf area of a single of some separated leaves. LAI Is a different quantity and it is conventionally estimated from photography of a canopy. If you are interested in specific leaf area, many softwares exists, as Mait already said, such as GIMP or imageJ

Dear Francesco Chianucci

first of all, I asked this question as an agronomist, So we talk about crops, not the tree.

Secondly, we are talking about people who do not have a dedicated device to measure LAI.

Third, the way I did it was to separate the leaves from the plants in a specific area, For example, one square meter. Then put all the leaves together on one surface with a ruler. Afterwards, I took a photo from all. Thus I analyzed by Digimizer.

Now I want to know if you approve of my work.

Regards.

I think It Is a matter of if you want a direct methods, which is often used to validate other approaches, or a fast indirect method for routine measurements of LAI

If you rip all leaves in a ground surface with known size and measure the area of each leaves, sum these leaf areas and divide by the ground surface...yes you have a leaf area index, but I think It Is very time consuming as It Is a direct and restrittive approach. You could reduce the effort by rip all leaves, take their Total dry weights, measure the area of a samples of leaves along with their dry weights to calculate Specific Leaf Area (SLA) and multiply the total dry weights per SLA.

If you want a more routine method I think you should better consider taking canopy photo from a pole oriented downward (in case of short crop) classify image pixels as vegetation/non-vegetation and apply models to retrieve LAI from non-vegetation (gap) fraction. In case of fisheye photography, can-eye allows to retrieve LAI in these images, otherwise take a look at these papers:

https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/j.2041-210X.2011.00151.x

https://www.sciencedirect.com/science/article/pii/S016819231400210X

ِDear Francesco Chianucci

Thank you very much for your complete answer and guidance.