GF-5 Hyperspectral Data for Species Mapping of Mangrove in Mai Po, Hong Kong

Abstract

Hyperspectral data has been widely used in species discrimination of plants with rich spectral information in hundreds of spectral bands, while the availability of hyperspectral data has hindered its applications in many specific cases. The successful operation of the Chinese satellite, Gaofen-5 (GF-5), provides potentially promising new hyperspectral dataset with 330 spectral bands in visible and near infrared range. Therefore, there is much demand for assessing the effectiveness and superiority of GF-5 hyperspectral data in plants species mapping, particularly mangrove species mapping, to better support the efficient mangrove management. In this study, mangrove forest in Mai Po Nature Reserve (MPNR), Hong Kong was selected as the study area. Four dominant native mangrove species were investigated in this study according to the field surveys. Two machine learning methods, Random Forests and Support Vector Machines, were employed to classify mangrove species with Landsat 8, Simulated Hyperion and GF-5 data sets. The results showed that 97 more bands of GF-5 over Hyperion brought a higher over accuracy of 87.12%, in comparison with 86.82% from Hyperion and 73.89% from Landsat 8. The higher spectral resolution of 5 nm in GF-5 was identified as making the major contribution, especially for the mapping of Aegiceras corniculatum. Therefore, GF-5 is likely to improve the classification accuracy of mangrove species mapping via enhancing spectral resolution and thus has promising potential to improve mangrove monitoring at species level to support mangrove management.

Multi-Decadal Changes in Mangrove Extent, Age and Species in the Red River Estuaries of Viet Nam

“…With the SPOT-7 multispectral bands of Blue (0.455 µm-0.525 µm), Green (0.530 µm-0.590 µm), Red (0.625 µm-0.695 µm), and Near-Infrared (0.760 µm-0.890 µm), the mangrove could be discriminated from other land uses [77], even considering different ages and growth stages [78]. However, minor differences in reflectance between mangrove species could be found at the 0.760 µm-0.890 µm (NIR) [79]. In addition, the Ban mangrove (Figure 10A), Vet (Figure 10B), and Su (Figure 10C) were very similar in terms of stand, leaf, and stems based on our observations, so this also makes it difficult to discriminate between them.…”

No place to hide: Rare plant detection through remote sensing

“…RS has become a widely applied tool in plant studies (e.g. Asner, Hughes, et al., 2008; Asner et al., 2008; Kopeć et al., 2020; Wan et al., 2020) with the increasing availability of RS products that capture a wide variety of environmental features (Corbane et al., 2015; Kerr & Ostrovsky, 2003; Turner et al., 2003). Studies using RS to focus specifically on rare plants remain uncommon, although their number has been growing in recent years (e.g.…”

A Spectrum Extension Approach for Radiometric Calibration of the Advanced Hyperspectral Imager Aboard the Gaofen-5 Satellite

“…Consequently, hyperspectral remote sensing images with rich spectral information were collected by GF-5/AHSI sensors. The availability of hyperspectral images can be widely used in land-use and land-cover change detection, agriculture and forest management, biochemical and biophysical property extraction of the Earth's surface, and so on [4]- [8]. For this, accurate and traceable radiometric calibration is required to achieve radiometric consistency of the hyperspectral images collected with past, current and future hyperspectral sensors.…”