LAI Clause Samples
The LAI (Liquidated and Ascertained Damages) clause sets out a predetermined amount of damages that a contractor must pay if they fail to complete a project by the agreed deadline. Typically, this clause specifies a daily or weekly rate that accrues for each period of delay, and applies automatically without the need for the client to prove actual losses. Its core practical function is to provide certainty and streamline the process of compensating for delays, thereby allocating risk and incentivizing timely completion of contractual obligations.
LAI. LAI hereby makes the following representations:
(i) As of the date of this Agreement, LAI is authorized to issue an unlimited number of LAI Class A Common Shares, LAI Class B Common Shares and LAI Class C Common Shares. As of the date of this Agreement, LAI’s issued and outstanding capital stock consists of 106,702 LAI Class A Shares, 115,594 LAI Class B Shares and options to purchase 1,897,000 shares of LAI Class C Shares. All of the issued and outstanding shares of capital stock of the Company are duly and validly issued and outstanding and are fully paid and nonassessable.
(ii) Except for the options described in Section 3.4(b)(i) as specifically contemplated by this Agreement, (A) there are no other shares of capital stock or other equity securities of LAI outstanding and no outstanding Equity Rights relating to the capital stock of LAI, and (B) no Person has any Equity Right with respect to capital stock or other equity securities of LAI.
LAI. The LAI is derived from MERIS time series, making use of all available 10-day composites and available at ▇▇▇▇▇.▇▇▇.▇▇ (DOI: 10.15489/ak90g1wty909). Additionally, LAI is calculated for selected Landsat 8 scenes, accompanying the reflectance, LST and albedo images.
LAI. The leaf area index (LAI) is calculated with a spatial resolution of 300 m from the MERIS level 1B data. For the calculation of the LAI, the BEAM MERIS vegetation processor was used. After the LAI processing, a time series analysis was applied to fill data gaps and filter outliers (Tum et al., under review). The result is a continuous data set. For URBANFLUXES this data set was clipped for the three study areas as well as resampled to the 100 m grid. This data set provides information on the phenology during the year. However, because of the course resolution, also LAI is derived from the same images as the reflectance to have an up-to-date complete high resolution data set for the selected dates. This LAI is derived using ATCOR according to the following equation (▇▇▇▇▇▇▇ and ▇▇▇▇▇▇▇▇▇ 2015): 𝑎2 ln( 𝑎0−𝑉𝐼 ) 𝑎1 Where 𝑎0 = 0.820, 𝑎1 = 0.780, 𝑎2 = 0.600 and VI is a vegetation index, in this case SAVI: (𝜌850 − 𝜌650) ∗ 1.5 (𝜌850 + 𝜌650 + 0.5) Where 𝜌850 and 𝜌650 is the reflectance at 850 nm and 650 nm, respectively. Because here empirically derived parameters are used, the absolute LAI values may not be correct, but the approach allows capturing the seasonal trend.