In Situ Hyperspectral Remote Sensing for Monitoring of Alpine Trampled and Recultivated Species

Abstract

Vegetation, through its condition, reflects the properties of the environment. Heterogeneous alpine ecosystems play a critical role in global monitoring systems, but due to low accessibility, cloudy conditions, and short vegetation periods, standard monitoring methods cannot be applied comprehensively. Hyperspectral tools offer a variety of methods based on narrow-band data, but before extrapolation to an airborne or satellite scale, they must be verified using plant biometrical variables. This study aims to assess the condition of alpine sward dominant species (Agrostis rupestris, Festuca picta, and Luzula alpino-pilosa) of the UNESCO Man&Biosphere Tatra National Park (TPN) where the high mountain grasslands are strongly influenced by tourists. Data were analyzed for trampled, reference, and recultivated polygons. The field-obtained hyperspectral properties were verified using ground measured photosynthetically active radiation, chlorophyll content, fluorescence, and evapotranspiration. Statistically significant changes in terms of cellular structures, chlorophyll, and water content in the canopy were detected. Lower values for the remote sensing indices were observed for trampled plants (about 10–15%). Species in recultivated areas were characterized by a similar, or sometimes improved, spectral properties than the reference polygons; confirmed by fluorescence measurements (Fv/Fm). Overall, the fluorescence analysis and remote sensing tools confirmed the suitability of such methods for monitoring species in remote mountain areas, and the general condition of these grasslands was determined as good.

Phenotyping Plant Responses to Biotic Stress by Chlorophyll Fluorescence Imaging

“…The ETR could be also estimated by PRI at leaf scale; however, a PRI calibrated for the pigments content provided an even better estimation (Rahimzadeh-Bajgiran et al, 2012). Other VIs, such as the normalized multi-band drought index (NMDI) or the water band index (WBI), have also been found to correlate with F V /F M and Φ PSII for a range of alpine sward species (Kycko et al, 2019). Furthermore, the maximum daily photosynthetic rate correlated with NDVI and SR (Gamon et al, 1995).…”

Lead-Induced Changes in Fluorescence and Spectral Characteristics of Pea Leaves

“…Pigment content was analyzed based on the fresh weight (FW) of the leaves (mg Chl/FW). The concentrations of the pigments (in µg/mL) was calculated with Equations (2)-(4) [38]:…”

Remote sensing techniques to assess chlorophyll fluorescence in support of crop monitoring in Poland

“…The observed NDVI and NDII temporal curves are comparable to Estimates of the ratio of carotenoids to chlorophyll can be followed using the SIPI (structural independent pigment index) curves. The distinctly increased values observed for maize at heading and sugar beets at the beets' root development stage in 2019 confirm that the vegetation was stressed (Kycko et al 2019a).…”

“…At the next stage of the work, correlation analysis was performed comparing particular VIs derived from satellite images and those ChlF values measured on the ground in order to find if a significant relationship existed between these two parameters. Assessments of Fv/Fm from VIs derived from remote sensing data have been reported by several studies (Tan et al 2012;Peng et al 2017;Kycko et al 2019a;Kycko et al 2019b;Wei et al 2019;Zagajewski et al, 2017;Zagajewski et al 2018). For instance, some researchers compared the results of VIs to assess the Fv/Fm of maize, and reached the conclusion that out of the various kinds of VI that had a close relationship with Fv/Fm, SIPI performed best (Tan et al, 2012).…”

“…If ground cover was significant, the impact of the background was significantly reduced, and Fv/Fm could be better estimated using NDVI (Wei et al 2019). Kycko et al (2019a) and Zagajewski et al (2018) used in-situ hyperspectral remote sensing as an important technique to fulfill real-time monitoring of plant condition based on its superior performance in acquiring vegetation canopy information rapidly and non-destructively. In studies conducted by Peng et.…”