Editorial

2 pages, 158 KiB

Open AccessEditorial

Editorial for Special Issue “Optical Remote Sensing of Boreal Forests”

by Miina Rautiainen and Jan Pisek

Remote Sens. 2018, 10(11), 1766; https://doi.org/10.3390/rs10111766 - 08 Nov 2018

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Boreal forests (or taiga) are the world’s largest terrestrial biome and represent one third of the world’s forest cover. [...] Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

Research

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15 pages, 4274 KiB

Open AccessArticle

Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests

by Michael M. Loranty, Sergey P. Davydov, Heather Kropp, Heather D. Alexander, Michelle C. Mack, Susan M. Natali and Nikita S. Zimov

Remote Sens. 2018, 10(11), 1686; https://doi.org/10.3390/rs10111686 - 25 Oct 2018

Cited by 40 | Viewed by 7057

Abstract

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent [...] Read more.

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km² upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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19 pages, 5862 KiB

Open AccessArticle

In Situ Observations Reveal How Spectral Reflectance Responds to Growing Season Phenology of an Open Evergreen Forest in Alaska

by Hideki Kobayashi, Shin Nagai, Yongwon Kim, Wei Yang, Kyoko Ikeda, Hiroki Ikawa, Hirohiko Nagano and Rikie Suzuki

Remote Sens. 2018, 10(7), 1071; https://doi.org/10.3390/rs10071071 - 05 Jul 2018

Cited by 15 | Viewed by 5066

Abstract

Plant phenology timings, such as spring green-up and autumn senescence, are essential state information characterizing biological responses and terrestrial carbon cycles. Current efforts for the in situ reflectance measurements are not enough to obtain the exact interpretation of how seasonal spectral signature responds [...] Read more.

Plant phenology timings, such as spring green-up and autumn senescence, are essential state information characterizing biological responses and terrestrial carbon cycles. Current efforts for the in situ reflectance measurements are not enough to obtain the exact interpretation of how seasonal spectral signature responds to phenological stages in boreal evergreen needleleaf forests. This study shows the first in situ continuous measurements of canopy scale (overstory + understory) and understory spectral reflectance and vegetation index in an open boreal forest in interior Alaska. Two visible and near infrared spectroradiometer systems were installed at the top of the observation tower and the forest understory, and spectral reflectance measurements were performed in 10 min intervals from early spring to late autumn. We found that canopy scale normalized difference vegetation index (NDVI) varied with the solar zenith angle. On the other hand, NDVI of understory plants was less sensitive to the solar zenith angle. Due to the influence of the solar geometry, the annual maximum canopy NDVI observed in the morning satellite overpass time (10–11 am) shifted to the spring direction compared with the standardized NDVI by the fixed solar zenith angle range (60−70°). We also found that the in situ NDVI time-series had a month-long high NDVI plateau in autumn, which was completely out of photosynthetically active periods when compared with eddy covariance net ecosystem exchange measurements. The result suggests that the onset of an autumn high NDVI plateau is likely to be the end of the growing season. In this way, our spectral measurements can serve as baseline information for the development and validation of satellite-based phenology algorithms in the northern high latitudes. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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14 pages, 3247 KiB

Open AccessArticle

Measurement of Diurnal Variation in Needle PRI and Shoot Photosynthesis in a Boreal Forest

by Matti Mõttus, Rocío Hernández-Clemente, Viljami Perheentupa, Vincent Markiet, Juho Aalto, Jaana Bäck and Caroline J. Nichol

Remote Sens. 2018, 10(7), 1019; https://doi.org/10.3390/rs10071019 - 26 Jun 2018

Cited by 4 | Viewed by 4226 | Correction

Abstract

The photochemical reflectance index (PRI) is calculated from vegetation narrowband reflectance in two bands in the visible part of the spectrum. Variations in PRI are associated with changes in the xanthophyll cycle pigments which regulate the light use efficiency of vegetation. Correlations have [...] Read more.

The photochemical reflectance index (PRI) is calculated from vegetation narrowband reflectance in two bands in the visible part of the spectrum. Variations in PRI are associated with changes in the xanthophyll cycle pigments which regulate the light use efficiency of vegetation. Correlations have been found between remotely-sensed PRI and various photosynthetic productivity parameters at the scales from leaves to landscapes. Environmental satellites can provide only an instantaneous value of this index at the time of overpass. The diurnal course of needle (leaf) PRI needs to be known in order to link the instantaneous values robustly with photosynthetic parameters at time scales exceeding one day. This information is not currently available in the scientific literature. Here we present the daily cycle of Scots pine needle and canopy PRI in a southern boreal forest zone in the presence of direct solar radiation during the peak growing season of two consecutive years. We found the PRI of the needles which are exposed to direct radiation to have a distinct diurnal cycle with constant or slightly increasing values before noon and a daily minimum in the afternoon. The cycle in needle PRI was not correlated with that in the incident photosynthetic photon flux density (PPFD). However, when PPFD was above 1000 μmol m⁻² s⁻¹, approximately between 8 a.m. and 5 p.m., needle PRI was correlated with the light use efficiency (LUE), measured with shoot chambers. The timing of the minimum needle PRI coincided with the minimum canopy value, as measured by an independent sensor above the canopy, but the correlation between the two variables was not significant. Our field results corroborate the applicability of needle PRI in monitoring the daily variation in LUE. However, to apply this to remote sensing of seasonal photosynthetic productivity, the daily cycle of leaf PRI needs to be known for the specific vegetation type. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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15 pages, 3573 KiB

Open AccessArticle

Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series

by José R. García-Lázaro, José A. Moreno-Ruiz, David Riaño and Manuel Arbelo

Remote Sens. 2018, 10(6), 940; https://doi.org/10.3390/rs10060940 - 14 Jun 2018

Cited by 30 | Viewed by 4388

Abstract

A Bayesian classifier mapped the Burned Area (BA) in the Northeastern Siberian boreal forest (70°N 120°E–60°N 170°E) from 1982 to 2015. The algorithm selected the 0.05° (~5 km) Long-Term Data Record (LTDR) version 3 and 4 data sets to generate 10-day BA composites. [...] Read more.

A Bayesian classifier mapped the Burned Area (BA) in the Northeastern Siberian boreal forest (70°N 120°E–60°N 170°E) from 1982 to 2015. The algorithm selected the 0.05° (~5 km) Long-Term Data Record (LTDR) version 3 and 4 data sets to generate 10-day BA composites. Landsat-TM scenes of the entire study site in 2002, 2010, and 2011 assessed the spatial accuracy of this LTDR-BA product, in comparison to Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD45A1 and MCD64A1 BA products. The LTDR-BA algorithm proves a reliable source to quantify BA in this part of Siberia, where comprehensive BA remote sensing products since the 1980s are lacking. Once grouped by year and decade, this study explored the trends in fire activity. The LTDR-BA estimates contained a high interannual variability with a maximum of 2.42 million ha in 2002, an average of 0.78 million ha/year, and a standard deviation of 0.61 million ha. Going from 6.36 in the 1980s to 10.21 million ha BA in the 2010s, there was a positive linear BA trend of approximately 1.28 million ha/decade during these last four decades in the Northeastern Siberian boreal forest. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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17 pages, 16263 KiB

Open AccessEditor’s ChoiceArticle

Comparing Three Different Ground Based Laser Scanning Methods for Tree Stem Detection

by Ivar Oveland, Marius Hauglin, Francesca Giannetti, Narve Schipper Kjørsvik and Terje Gobakken

Remote Sens. 2018, 10(4), 538; https://doi.org/10.3390/rs10040538 - 31 Mar 2018

Cited by 55 | Viewed by 7339

Abstract

A forest inventory is often carried out using airborne laser data combined with ground measured reference data. Traditionally, the ground reference data have been collected manually with a caliper combined with land surveying equipment. During recent years, studies have shown that the caliper [...] Read more.

A forest inventory is often carried out using airborne laser data combined with ground measured reference data. Traditionally, the ground reference data have been collected manually with a caliper combined with land surveying equipment. During recent years, studies have shown that the caliper can be replaced by equipment and methods that capture the ground reference data more efficiently. In this study, we compare three different ground based laser measurement methods: terrestrial laser scanner, handheld laser scanner and a backpack laser scanner. All methods are compared with traditional measurements. The study area is located in southeastern Norway and divided into seven different locations with different terrain morphological characteristics and tree density. The main tree species are boreal, dominated by Norway spruce and Scots pine. To compare the different methods, we analyze the estimated tree stem diameter, tree position and data capture efficiency. The backpack laser scanning method captures the data in one operation. For this method, the estimated diameter at breast height has the smallest mean differences of 0.1 cm, the smallest root mean square error of 2.2 cm and the highest number of detected trees with 87.5%, compared to the handheld laser scanner method and the terrestrial laser scanning method. We conclude that the backpack laser scanner method has the most efficient data capture and can detect the largest number of trees. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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Open AccessFeature PaperEditor’s ChoiceArticle

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

by Lanhui Wang and Rasmus Fensholt

Remote Sens. 2017, 9(12), 1277; https://doi.org/10.3390/rs9121277 - 08 Dec 2017

Cited by 24 | Viewed by 6429

Abstract

Global warming has greatly stimulated vegetation growth through both extending the growing season and promoting photosynthesis in the Northern Hemisphere (NH). Analyzing the combined dynamics of such trends can potentially improve our current understanding on changes in vegetation functioning and the complex relationship [...] Read more.

Global warming has greatly stimulated vegetation growth through both extending the growing season and promoting photosynthesis in the Northern Hemisphere (NH). Analyzing the combined dynamics of such trends can potentially improve our current understanding on changes in vegetation functioning and the complex relationship between anthropogenic and climatic drivers. This study aims to analyze the relationships (long-term trends and correlations) of length of vegetation growing season (LOS) and vegetation productivity assessed by the growing season NDVI integral (GSI) in the NH (>30°N) to study any dependency of major biomes that are characterized by different imprint from anthropogenic influence. Spatial patterns of converging/diverging trends in LOS and GSI and temporal changes in the coupling between LOS and GSI are analyzed for major biomes at hemispheric and continental scales from the third generation Global Inventory Monitoring and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) dataset for a 32-year period (1982–2013). A quarter area of the NH is covered by converging trends (consistent significant trends in LOS and GSI), whereas diverging trends (opposing significant trends in LOS and GSI) cover about 6% of the region. Diverging trends are observed mainly in high latitudes and arid/semi-arid areas of non-forest biomes (shrublands, savannas, and grasslands), whereas forest biomes and croplands are primarily characterized by converging trends. The study shows spatially-distinct and biome-specific patterns between the continental land masses of Eurasia (EA) and North America (NA). Finally, areas of high positive correlation between LOS and GSI showed to increase during the period of analysis, with areas of significant positive trends in correlation being more widespread in NA as compared to EA. The temporal changes in the coupled vegetation phenology and productivity suggest complex relationships and interactions that are induced by both ongoing climate change and increasingly intensive human disturbances. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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17 pages, 1135 KiB

Open AccessTechnical Note

Estimation of Gap Fraction and Foliage Clumping in Forest Canopies

by Andres Kuusk, Jan Pisek, Mait Lang and Silja Märdla

Remote Sens. 2018, 10(7), 1153; https://doi.org/10.3390/rs10071153 - 21 Jul 2018

Cited by 25 | Viewed by 5308

Abstract

The gap fractions of three mature hemi-boreal forest stands in Estonia were estimated using the LAI-2000 plant canopy analyzer ( LI-COR Biosciences, Lincoln, NE, USA), the TRAC instrument (Edgewall, Miami, FL, USA), Cajanus’ tube, hemispherical photos, as well as terrestrial (TLS) and airborne [...] Read more.

The gap fractions of three mature hemi-boreal forest stands in Estonia were estimated using the LAI-2000 plant canopy analyzer ( LI-COR Biosciences, Lincoln, NE, USA), the TRAC instrument (Edgewall, Miami, FL, USA), Cajanus’ tube, hemispherical photos, as well as terrestrial (TLS) and airborne (ALS) laser scanners. ALS measurements with an 8-year interval confirmed that changes in the structure of mature forest stands are slow, and that measurements in the same season of different years should be well comparable. Gap fraction estimates varied considerably depending on the instruments and methods used. None of the methods considered for the estimation of gap fraction of forest canopies proved superior to others. The increasing spatial resolution of new ALS devices allows the canopy structure to be analyzed in more detail than was possible before. The high vertical resolution of point clouds improves the possibility of estimating the stand height, crown length, and clumping of foliage in the canopy. The clumping/regularity of the foliage in a forest canopy is correlated with tree height, crown length, and basal area. The method suggested herein for the estimation of foliage clumping allows the leaf area estimates of forest canopies to be improved. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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15 pages, 6424 KiB

Open AccessLetter

Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP

by Sornkitja Boonprong, Chunxiang Cao, Wei Chen and Shanning Bao

Remote Sens. 2018, 10(6), 807; https://doi.org/10.3390/rs10060807 - 23 May 2018

Cited by 25 | Viewed by 5059

Abstract

Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these [...] Read more.

Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these methods are complicated and time consuming when increasing the number of observed parameters. In this work, we present a random forest variable importance (RF-VIMP) scheme called multilevel RF-VIMP to compare and assess the relationship between 36 spectral indices (parameters) of burnt boreal forest recovery in the Great Xing’an Mountain, China. Six Landsat images were acquired in the same month 0, 1, 4, 14, 16, and 20 years after a fire, and 39,380 fixed-location samples were then extracted to calculate the effectiveness of the 36 parameters. Consequently, the proposed method was applied to find correlations between the forest recovery indices. The experiment showed that the proposed method is suitable for explaining the efficacy of those spectral indices in terms of discrimination and trend analysis, and for showing the satellite data and forest succession dynamics when applied in a time series. The results suggest that the tasseled cap transformation wetness, brightness, and the shortwave infrared bands (both 1 and 2) perform better than other indices for both classification and monitoring. Full article

(This article belongs to the Special Issue Optical Remote Sensing of Boreal Forests)

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