دانلود رایگان مقاله بهبود برآورد شاخص سطح برگ بر اساس آنالیز هیستوگرام عکس های نیم کره ای

Abstract

Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976–۱۹۸۱). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was ۶%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage.

4. Conclusions

This work showed the usefulness of the entropy crossover method (ECOM) to determine the OTV for separating the foreground and background in hemispherical photographs. Together, the ECOM and the gap fraction method were suitable for the calculation of LAI. The robustness of the ECOM in working with different sky luminosity was a desirable characteristic for LAI calculation. The confidence of the calculated LAI from ECOM and the gap fraction methods was demonstrated over two different Brazilian ecosystems including Amazon rainforest and pasture, where the maximum error observed with respect to observations was 6%. This method also provided and estimate of the clumping factor, an important parameter for ecological and modeling studies. Our methodology not only provides accurate estimates of LAI, but also is easy to implement, automatic, fast, and reduces the storage size of hemispherical photographs. As such, the calculated LAI values can be obtained in situ immediately after image collection.