LAI

This article aims at finding efficient hyperspectral indices for the estimation of forest sun leaf chlorophyll content (CHL, µg cmleaf− 2), sun leaf mass per area (LMA, gdry matter mleaf− 2), canopy leaf area index (LAI, m2leaf msoil− 2) and leaf canopy biomass (Bleaf, gdry matter msoil− 2). These parameters are useful inputs for forest ecosystem simulations at landscape scale. The method is based on the determination of the best vegetation indices (index form and wavelengths) using the radiative transfer model PROSAIL (formed by the newly-calibrated leaf reflectance model PROSPECT coupled with the multi-layer version of the canopy radiative transfer model SAIL). The results are tested on experimental measurements at both leaf and canopy scales. At the leaf scale, it is possible to estimate CHL with high precision using a two wavelength vegetation index after a simulation based calibration. At the leaf scale, the LMA is more difficult to estimate with indices. At the canopy scale, efficient indices were determined on a generic simulated database to estimate CHL, LMA, LAI and Bleaf in a general way. These indices were then applied to two Hyperion images (50 plots) on the Fontainebleau and Fougères forests and portable spectroradiometer measurements. They showed good results with an RMSE of 8.2 µg cm− 2 for CHL, 9.1 g m− 2 for LMA, 1.7 m2 m− 2 for LAI and 50.6 g m− 2 for Bleaf. However, at the canopy scale, even if the wavelengths of the calibrated indices were accurately determined with the simulated database, the regressions between the indices and the biophysical characteristics still had to be calibrated on measurements. At the canopy scale, the best indices were: for leaf chlorophyll content: NDchl = (ρ925 − ρ710)/(ρ925 + ρ710), for leaf mass per area: NDLMA = (ρ2260 − ρ1490)/(ρ2260 + ρ1490), for leaf area index: DLAI = ρ1725 − ρ970, and for canopy leaf biomass: NDBleaf = (ρ2160 − ρ1540)/(ρ2160 + ρ1540).

ÖZET Bu çalışma, pamuk bitkisinin farklı azot dozlarının bitkinin fizyomorfolojik özelliklerinde oluşan değişimleri saptamak, bu fizyomorfolojik özellikler yardımı ile bitkideki azot durumunu tahmin etmek, geniş pamuk üretim alanlarında azot gereksinimlerini saptamak ve azot uygulama tavsiyelerinde bulunmak amacı ile Mardin ekolojik koşullarında, tesadüf parselleri deneme deseninde 3 tekerrürlü olarak yürütülmüştür. Çalışmada, fizyomorfolojik özellikler (yaprak azot içeriği, yaprak SPAD değeri, yaprak alan indeksi, NDVI) ve kütlü pamuk verimi özelliği incelenmiştir. İncelenen tüm fizyomorfolojik özellikler yönünden yaprak azot içerikleri arasında farklılıklar, istatistiki olarak önemli olduğu saptanmıştır. Yaprak azot içeriği ile incelenen tüm fizyomorfolojik özellikler aralarında ikili ilişkiler, istatistiki olarak önemli olduğu; yaprak azot içeriği ile yaprak SPAD değeri (R 2 : 0.44), yaprak alan indeksi (R 2 : 0.79) arasında linear ilişki, NDVI (R 2 : 0.42), kütlü pamuk verimi (R 2 : 0.65) özellikleri arasında ise quadratik ilişkinin olduğu saptanmıştır. ABSTRACT The aim of this study is to determine the changes in the physio-morphological properties of different plant nitrogen doses in cotton plant and to estimate the nitrogen status of the plant with these physio-morphological features, in order to determine nitrogen requirements in large cotton production areas and to advise on nitrogen application, it was carried out with 3 replications in randomized plot design in Mardin ecological conditions. Physio-morphological properties (leaf nitrogen content, leaf SPAD value, leaf area index, NDVI) and cotton yield were investigated. Differences between leaf nitrogen contents in terms of all physio-morphological characteristics examined were found to be statistically significant. Leaf nitrogen content and the relationship between all physio-morphological properties examined were statistically significant; leaf nitrogen content and leaf SPAD value (R 2 : 0.44), leaf area index (R 2 : 0.79), linear relationship between NDVI (R 2 : 0.42), cotton yield (R 2 : 0.65) was found to have a quadratic relationship.

Leaf area index (LAI), a dimensionless biophysical variable is considered as one of the most important factors in characterizing canopy structure. It estimates the amount of foliage area per unit of ground area and helps indirectly to assess biomass and energy balance in an ecosystem. Remote sensing techniques established a strong correlation between the vegetation reflectance characteristics in red and near infra-red bands and LAI. Good number of image derived vegetation indices has been applied so far to estimate LAI successfully. In this paper correlation is established between field-collected LAI and three soil adjusted vegetation indices, i.e., SAVI, MSAVI and OSAVI derived from IRS-LISS-III data in deltaic ecosystem in Sagar Island of West Bengal, India. LAI was estimated from OSAVI for the whole island as OSAVI yielded best result (R 2 = 0.92). Coarse resolution MODIS LAI (MOD 15A3) product was counter-validated with respect to the LISS-III derived LAI image following the upscale validation approach. Out of the six best-fit models applied, the logistic regression showed strong positive correspondence between the two products (R 2 = 0.71). Uncertainty of the model was also assessed and probable reasons were identified.

Within the frame of a larger project funded by the High Tech Offensive Bayern (HTO) hyperspectral HyMap data have been investigated on their spectral content in order to determine bio-geo-chemo- physical parameters of land cover units in the catchment of Lake Waging-Taching in Upper Bava- ria, Germany. The focus of the current investigations was on parameter extraction from grasslands and

The Leaf Area Index (LAI) and its spatial distribution are key features to describe the forest ecophysiological processes. A stable and reproducible relationship is obtained between the LAI and the standard deviation σNDVI of the pixel‐based satellite‐derived normalized difference vegetation indices (NDVI) of forest stands. In situ measurements of LAI have been performed with the LAI‐2000 Plant Canopy Analyser over 8 years in the managed Fontainebleau forest (France) on about 31 stands each year, including oak, beech, and mixed oak‐beech stands. Simultaneous satellite images have been acquired, atmospherically and geometrically corrected, and included into a geographic information system to get the mean NDVI and the σNDVI for each stand. A total of six different satellites with a 20‐ to 30‐m spatial resolution have been considered over the eight studied years: SPOT1, SPOT2, SPOT4, LANDSAT ETM+, IKONOS, and HYPERION. The mean LAI of a stand is linked to the σNDVI with a unique relationship that appears to be mostly year‐ and satellite‐independent, because the σNDVI is nearly insensitive to additive or proportional shifts on NDVI. The theoretical bases of the σNDVI‐LAI relationship are investigated. The results show the combined importance of the shape of the within‐stand LAI distribution (following a Weibull probability density function) and the shape of the within‐stand LAI‐NDVI curves (showing a saturation). The root mean square error of the predicted LAI over the 259 samples is 1.14 m2/m2 when all years and satellites are considered, using the following equation: LAI = −2.45 ln(σNDVI) − 5.58 (r2 = 0.63)

Leaf area index (LAI) is a key parameter controlling plant productivity and biogeochemical fluxes between vegetation and the atmosphere. Tropical forests are thought to have comparably high LAIs; however, precise data are scarce and environmental controls of leaf area in tropical forests are not understood. We studied LAI and stand leaf biomass by optical and leaf mass-related approaches in five tropical montane forests along an elevational transect (1,050–3,060 m a.s.l.) in South Ecuador, and conducted a meta-analysis of LAI and leaf biomass data from tropical montane forests around the globe. Study aims were (1) to assess the applicability of indirect and direct approaches of LAI determination in tropical montane forests, (2) to analyze elevation effects on leaf area, leaf mass, SLA, and leaf lifespan, and (3) to assess the possible consequences of leaf area change with elevation for montane forest productivity. Indirect optical methods of LAI determination appeared to be less reliable in the complex canopies than direct leaf mass-related approaches based on litter trapping and a thorough analysis of leaf lifespan. LAI decreased by 40–60% between 1,000 and 3,000 m in the Ecuador transect and also in the pan-tropical data set. This decrease indicates that canopy carbon gain, that is, carbon source strength, decreases with elevation in tropical montane forests. Average SLA decreased from 88 to 61 cm2 g−1 whereas leaf lifespan increased from 16 to 25 mo between 1,050 and 3,060 m in the Ecuador transect. In contrast, stand leaf biomass was much less influenced by elevation. We conclude that elevation has a large influence not only on the leaf traits of trees but also on the LAI of tropical montane forests with soil N (nitrogen) supply presumably being the main controlling factor.