Spectral Indices as a Tool to Assess the Moisture Status of Forest Habitats

Abstract

Measurement of water content in forest habitats is considered essential in ecological research on forests, climate change, or forest management. In the traditional forest habitat classification, two systems of habitat conditions analysis are found: single factor and multifactor methods. Both are laborious and therefore costly. Remote sensing methods provide a low-cost alternative. The aim of the presented study was to find the relationship between the spectral indices obtained from satellite images and the forest habitats moisture indices used traditionally in the Polish forest habitats classification. The scientific hypothesis of the research is as follows: it is possible to assess the variation in the humidity of forest habitats on the basis of spectral indices. Using advanced geographic information system (GIS) technology, 923 research plots were tested, where habitat studies performed with the traditional methods were compared with the analysis of 191 spectral indices calculated for Sentinel-2 image data. The normalized difference vegetation index (NDVI) has proved to be the most useful to the assessing of moisture of forest habitats. The ranking of the most correlated indices was calculated as Eintg—the product of the absolute value of the slope and the mean square error complement, and for the top five indices was as follows: NDVI = 0.248619, EXG = 0.242112, OSAVI = 0.239412, DSWI-4 = 0.238784, and RDVI = 0.236995. The results also highlight the impact of water reservoirs on the humidity and trophicity of forest habitats, showing a decrease in the fertility of habitats with an increase in distance from the water reservoir. The results of the study can be used to preparing maps of the diversity of forest types, especially in hard-to-reach places, as well as to assess changes in the moisture status of habitats, which may be useful, for example, in the assessment of the fire risk of forest habitats. We have proved that NDVI can be used in applications for which it was not originally designed.

Prospects for the Preservation of the Main Pinus sylvestris L. Ecotypes in Poland in the Context of the Habitat Conditions of Their Occurrence

“…The ecotype from Kampinoski National Park (2 and 3) was selected based on the results of Przybylski et al [2]. The National Park Bory Tucholskie (6) was chosen due to the results of Młynarczyk et al [15]. The "Rychtalska pine" ecotype (5) was chosen due to the results of Wójkiewicz et al [16] and Barzdajn [14].…”

“…Descriptions of the research areas were supplemented with a summary of atmospheric precipitation according to Muñoz Sabater [18]. [15], after testing 249 vegetation indices calculated according to the formulas stored and described in the "Index Database" (https://www.indexdatabase.de/, accessed on 28 December 2022), demonstrated that the NDVI can be used as an indicator describing both the moisture and trophic status of forest habitats. This was considered an important measure of habitat conditions, which simultaneously influences the condition of forest stands.…”

“…This was considered an important measure of habitat conditions, which simultaneously influences the condition of forest stands. Therefore, NDVI data were calculated and used according to the methodology described by Młynarczyk et al [15]. Following the authors' recommendations, the NDVI was calculated for three months: July, August, and September (2020), which best reflect the NDVI for the temperate climate zone where Poland is located.…”

Estimation of Anthocyanins in Leaves of Trees with Apple Mosaic Disease Based on Hyperspectral Data

“…Yang used hyperspectral data to generate a visualization of the changes in anthocyanin content of litchi during storage [16]. Researchers have studied and constructed various vegetation indices [17][18][19][20], for example, the Difference Spectral Index (DSI), Ratio Spectral Index (RSI), and Normalized Difference Spectral Index (NDSI). Lopes modified DSI, RSI, and NDVI; combined linear, exponential, power, and logarithmic regression in the modeling process; and confirmed the feasibility of using the spectral index to estimate carotenoid and anthocyanin content in lettuce [21].…”

Quantification of short‐term transformations of proglacial landforms in a temperate, debris‐charged glacial landsystem, Kvíárjökull, Iceland

“…Global climate warming has contributed to landform transformation for decades (Song et al, 2018) and increasing average air temperatures have resulted in significant changes in regional climates and local ecosystems, thereby increasing the risks of fires, droughts, floods and landslides (Allen et al, 2010; Flannigan et al, 2009; Gariano & Guzzetti, 2016; Hirabayashi et al, 2013; Młynarczyk et al, 2022). In cold climate settings, the impact has been manifested as dynamic responses in glacial systems (Benn et al, 2012; Benn & Evans, 2010).…”