The iSpecField-WNIR offers a spectral range of 200-1700nm and features a unique optical design with noise calibration technology. It has the capability to perform real-time automatic dark current calibration. The instrument employs a fixed holographic grating for one-time spectral separation, resulting in fast testing. The minimum integration time can be as short as 10 microseconds, allowing for rapid measurements. It also offers a wide dynamic range and utilizes dual-channel high-pixel detectors for synchronous measurements. The spectrometer provides high spectral data resolution, making it suitable for a wide range of applications, including the mineral identification, soil research, remote sensing measurements, crop monitoring, forest studies, oceanography, and mineral exploration.

Typical Applications

Technical Advantages

● Spectral Range: The iSpecField-NIR covers a spectral range of 200-1700nm and utilizes a fixed holographic grating for rapid scanning.

●High-Resolution Detectors: It is equipped with a 2048-pixel area BT-CCD detector and 256/512-pixel InGaAs detectors, allowing for high-resolution and precise dual-channel synchronous measurements.

●Fast Integration Time: The device has a minimum integration time of 20 microseconds, supporting a large dynamic range and enabling remote trigger for one-click measurement.

●Built-in Features: Includes a built-in camera with over 8MP auto-focus, GPS, laser pointer, and optical shutter control for enhanced data collection capabilities.

●Real-Time Display: Capable of real-time display of solar azimuth and zenith angles, BRDF testing, UAV aerial survey mode, and common vegetation indices such as NDVI, DVI, EVI, CARI, PRI, RDVI, RVI, SAVI, SIPI, TVI, WI, VARI_700, and VARI_green.

●Multi-Function Sensors: Supports synchronous data acquisition, including GPS positioning, object imaging, angle measurement, distance measurement, and air temperature and humidity display.

●Software Compatibility: Comes with SpecAnalysis spectral data post-processing software, which is compatible with ENVI and other third-party tools. The software includes an integrated USGS database and 41 vegetation indices.

●Extensive Optical Accessories: Offers a wide range of optical accessories such as standard white/gray boards, leaf transmission clamps, specialized mineral soil probes, pistol grip fiber probes, indoor solar light sources, field of view lenses, BRDF measurement attachments, laboratory transmittance/reflectance mounting devices, and remote triggers. These accessories support both field and laboratory measurements, enabling tests of transmittance, reflectance, irradiance, and radiance.

●Field Collection Terminal: The handheld probe features a 7-inch screen or a pistol grip fiber probe with an optional 5.1-inch Android tablet.

●Battery Life: Provides a large capacity battery with 4-5 hours of operation. The battery module is replaceable, ensuring long-duration field measurements.

●Portability: Weighs less than 5 kg, making it portable and easy to carry for fieldwork.

SpecAnalysis

Technical Advantages

Main Technical Indicators

Optical Accessories

Application in Agriculture and Forestry

Vegetation serves as a significant domain of application in the field of optoelectronics, particularly in remote sensing. The utilization of remote sensing in the vegetation analysis primarily revolves around the determination of vegetation distribution, classification, and growth patterns. Different plant species exhibit distinctive spectral signatures due to variations in their structural composition and chlorophyll content, with notable discrepancies observed in the near-infrared spectral range. Spectral imaging techniques can effectively discern between various types of vegetation, such as deciduous and evergreen trees, by capitalizing on the phenological differences during different seasons. Additionally, alterations in the vegetation structure and chlorophyll content resulting from factors like diseases and pest infestations manifest prominently in the near-infrared range, presenting discernible deviations from healthy vegetation. Prominent factors influencing the spectral characteristics of vegetation encompass the botanical taxonomy, seasonal dynamics, and the influences exerted by pests and diseases. n

The key spectral features of vegetation can be summarized as follows in the field of optoelectronics: In the visible light range of 0.4 to 0.76 μm, a distinct reflection peak is observed, typically with reflectance ranging from 10% to 20%, centered around 0.55 μm (green). Additionally, there are two absorption bands flanking this peak at approximately 0.45 μm (blue) and 0.67 μm (red). Moving into the near-infrared range of 0.7 to 0.8 μm, a significant increase in reflectance occurs, characterized by a steep slope. Near 1.1 μm, another notable peak is observed, representing a unique spectral feature specific to vegetation. Transitioning to the mid-infrared range of 1.3 to 2.5 μm, the presence of water content in plants becomes a prominent factor. As a result, there is a substantial increase in absorption and a corresponding decrease in reflectance. Three distinct absorption valleys are evident near 1.4 μm, 1.9 μm, and 2.6 to 2.7 μm, primarily governed by the absorption properties of water within the cellular structure of leaves. The influencing factors in this absorption phenomenon encompass leaf thickness and water content.

Application in Ecological Environment

Soil remote sensing, within the field of optoelectronics, focuses on utilizing the spectral characteristics of soil to identify and classify different soil types, analyze the spatial distribution patterns of soil, and provide a scientific foundation for the rational development, utilization, management, and conservation of soil resources. By preventing the soil quality degradation and quantity reduction, it aims at improving soil conditions and facilitate the sustainable utilization of soil resources, fostering advancements in soil remote sensing science.

Under natural conditions, the reflectance spectrum of the soil surface exhibits a relatively smooth profile without prominent peaks or valleys. Generally, soils with finer particles tend to have higher reflectance values. The reflectance of soil is influenced by factors such as the organic matter content, moisture content, soil composition, and fertility. However, due to the smooth spectral curve, the differentiation of soil brightness on remote sensing images across various spectral bands may not be readily apparent.

Multiple factors contribute to variations in the spectral characteristics of soil, including the primary minerals, secondary minerals, soil moisture content, organic matter content, soil texture, and particle size. The main spectral features of soil are as follows: In its natural state, the reflectance curve of the soil surface lacks distinct peaks and absorption valleys, appearing relatively smooth. Under dry conditions, the spectral properties of soil primarily relate to the presence of primary minerals, secondary minerals, and organic matter.

As the soil moisture content increases, the reflectance of soil decreases, particularly in the vicinity of water absorption bands (around 1.4 μm, 1.9 μm, and 2.7 μm), where the decrease is particularly pronounced. Soil minerals, including quartz, mica, feldspar, oxides, among others, contribute to the differentiation of soil characteristics through the analysis of corresponding mineral contents. Additionally, the size and proportion of soil particles serves as indicators of particle size and water retention capacity.

Application in Mineral Exploration

Surface rocks are generally classified into three major categories: sedimentary rocks, volcanic rocks, and metamorphic rocks. The reflectance spectra of several rocks are shown in the figure below. The spectral nature of surface rock is essentially a mixed spectrum of minerals, and its spectral characteristics are influenced by factors such as the composition, structure, texture, and surface condition. Therefore, the identification of minerals through the reflectance spectra of surface minerals can achieve the goal of determining the type of rock.

The reflectance spectrum of rocks is primarily determined by the mineral composition, content, and material structure. Prominent absorption peaks are commonly observed in surface rocks, including hydroxyl-bearing minerals (2.10-2.40 μm), crystalline water minerals (1.40 μm, 2.40 μm), carbonate minerals (1.90 μm, 2.35 μm, 2.5 μm), and iron minerals (0.5 μm, 1.1 μm), among others. For example, the spectral characteristics of rocks in the 3-5 μm wavelength range are determined by the vibrational modes of molecular bonds such as oxygen-silicon and oxygen-aluminum. In addition to material composition, environmental conditions, surface characteristics of rocks and minerals, and physical weathering can also cause variations in the reflectance spectra of rocks, such as changes in reflectance values, positions, widths, absorption depths, and shapes of spectral bands.

Spectral instruments used for remote sensing require low energy and provide rapid analysis within a few seconds. They do not require any chemical reagents and pose no harm to human health. By acquiring spectral reflectance data, they can be utilized for the study of gemstone materials. The high spectral resolution can accurately reveal the information of harmonic and combination frequencies of molecular vibrations in gemstones, allowing for the analysis of complex structural information related to chemical bond interactions. Therefore, the high spectral resolution has significant potential in the gemstone analysis.

Application in Aquatic Environmental Oceanography

Ocean remote sensing has a broad coverage area and offers the advantages of simultaneity, allowing for continuous, long-term, and rapid observations of the ocean. It provides a comprehensive depiction of oceanic features, including sea surface temperature, oceanic currents, water distribution, waves, coastal sediment plumes, as well as phenomena such as red tides and oil spills. Ocean remote sensing is primarily applied in the investigation and monitoring of large-scale ocean circulation, nearshore surface flow fields, harbor water quality, marine surface chlorophyll concentration, and other aspects related to oceanography, meteorology, biology, physics, marine dynamics, marine pollution, and nearshore engineering.

Ocean remote sensing can be classified into three modalities: space-based remote sensing, airborne remote sensing, and ground-based remote sensing. Remote sensing methods can be divided into two types: active remote sensing, where electromagnetic waves are emitted from sensors to the ocean surface and the returning signals are used to extract oceanic information or images; and passive remote sensing, where sensors only receive the thermal radiation or scattered solar and sky radiance from the ocean surface to retrieve oceanic information or images.

Chlorophyll-a and total suspended matter are two important substances that influence the color of seawater and reflect changes in ocean water quality, making them crucial indicators for marine environmental monitoring. The reflectance of water is generally low, usually less than 10%, much lower than most other terrestrial objects. Water exhibits strong reflectance in the blue-green spectrum, while it absorbs strongly in other visible light spectra. The reflectance spectrum of pure water shows a peak in the blue region, which decreases gradually with increasing wavelength. In the near-infrared region, the reflectance of water is close to zero. However, in the presence of chlorophyll, the reflectance spectrum of clear water exhibits a peak in the green spectrum, and the height of the peak increases with the concentration of chlorophyll. This characteristic can be used to monitor and estimate algal biomass. Conversely, turbid water and sediment-laden water have higher reflectance than pure water, with reflectance peaks appearing in the yellow-red region.