Ahmadi, Kosari, and Malaek Table 4. The Main Applications of a Multispectral Sensor Bands [19] Band Blue Spectral Range μm 0.44-0.51 Examples of Applications * Identification of soil and plant * Detection of coastlines * Specification of plants Green 0.52-0.60 * Identification of healthy plants and infested plants * The depth of coastal waters estimation * Detection of cultural artifacts Red 0.63-0.69 * Identification of plant species * Identification of soils based on geological boundaries NIR 0.77-0.9 * Biomass estimation * Moisture of soil estimation * Identification of land and water Shortwave Infra-Red-1 (SWIR-1) 1.55-1.75 * Determination of plants moisture * Identification of cloud and snow * Identification of snow and ice Shortwave Infra-Red-2 (SWIR-2) 2.07-2.35 Thermal Infra-Red 10.3-12.4 * Identification of stones and minerals * Determination of plants moisture * Earth surface temperature estimation * Moisture of soil estimation * Specification of clouds * Fire detection detecting small differences in reflected or emitted energy. Imagery data are represented by positive digital numbers which vary from 0 to one less than a selected power of 2 as follows: Radiometric Resolution = 2 B − 1 (1) Where B corresponds to the number of bits used for coding the output of each detector element in each of the spectral bands. B could be considered as the performance quantitative criteria for radiometric resolution requirement [19]. In the case of the cubesat payload, there is no constraint for the number of quantization bits of the detector element. In general, higher value of B results in better performance of the cubesat optical payload. Step 4. Determination of constraints and quantitative criteria. The performance constraints usually limit the implementation techniques available to the system designer. Some of the most common performance constraints and factors which normally impact them could be found in [1]. The performance constraints are also expressed in terms of a qualitative phrase at first and then by quantitative criteria to finally FEBRUARY 2018 how that constraint has been satisfied could be evaluated. The performance constraints are another restrictive factor of the allowable design area in the design plane. In addition to the performance constraints and quantitative criteria, the DPs which have interactions with them should also be identified. Some of the constraints by which the design of cubesats payloads are dominated are listed in Table 5. Constraint of payload mass is not a performance constraint but since the performance constraints are collected to carry out the performance sizing of the cubesat payload, this constraint could be used for the results of the performance sizing to be verified at the end of this phase. Payload mass ≤ 1.5 Kg Constraint of payload power is also not a performance constraint as the constraint of payload mass; since the performance constraints are collected to carry out the performance sizing of the cubesat payload, this constraint could be used for the results of the performance sizing to be verified at the end of this phase. Payload orbit Power ≤ 1.8 W IEEE A&E SYSTEMS MAGAZINE 41