scholarly journals Global Forest Types Based on Climatic and Vegetation Data

2022 ◽  
Vol 14 (2) ◽  
pp. 634
Author(s):  
Chen Xu ◽  
Xianliang Zhang ◽  
Rocío Hernandez-Clemente ◽  
Wei Lu ◽  
Rubén D. Manzanedo
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forest Type ◽  
Tree Cover ◽  
Small Range ◽  
Vegetation Types ◽  
Forest Types ◽  
Type Distribution ◽  
Forest Attributes ◽  
Descriptive Names

Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aimed to improve the distribution of forest types to be more realistic and useful for biodiversity preservation, forest management, and ecological and forestry research. The forest types were classified using an unsupervised cluster analysis method by combining climate variables with normalized difference vegetation index (NDVI) data. Unforested regions were masked out to constrict our study to forest type distributions, using a 20% tree cover threshold. Descriptive names were given to the defined forest types based on annual temperature, precipitation, and NDVI values. Forest types had distinct climate and vegetation characteristics. Regions with similar NDVI values, but with different climate characteristics, which would be merged in previous classifications, could be clearly distinguished. However, small-range forest types, such as montane forests, were challenging to differentiate. At macroscale, the resulting forest types are largely consistent with land-cover types or vegetation types defined in previous studies. However, considering both potential and current vegetation data allowed us to create a more realistic type distribution that differentiates actual vegetation types and thus can be more informative for forest managers, conservationists, and forest ecologists. The newly generated forest type distribution is freely available to download and use for non-commercial purposes as a GeoTIFF file via doi: 10.13140/RG.2.2.19197.90082).

scholarly journals A Spatial and Temporal Assessment of Vegetation Greening and Precipitation Changes for Monitoring Vegetation Dynamics in Climate Zones over Africa

2021 ◽  
Vol 10 (3) ◽  
pp. 129
Author(s):  
Vincent Nzabarinda ◽  
Anming Bao ◽  
Wenqiang Xu ◽  
Solange Uwamahoro ◽  
Madeleine Udahogora ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forest Type ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Plant Health ◽  
Tree Cover ◽  
Climatic Zones ◽  
Dramatic Decline ◽  
Precipitation Changes

Vegetation is vital, and its greening depends on access to water. Thus, precipitation has a considerable influence on the health and condition of vegetation and its amount and timing depend on the climatic zone. Therefore, it is extremely important to monitor the state of vegetation according to the movements of precipitation in climatic zones. Although a lot of research has been conducted, most of it has not paid much attention to climatic zones in the study of plant health and precipitation. Thus, this paper aims to study the plant health in five African climatic zones. The linear regression model, the persistence index (PI), and the Pearson correlation coefficients were applied for the third generation Normalized Difference Vegetation Index (NDVI3g), with Climate Hazard Group infrared precipitation and Climate Change Initiative Land Cover for 34 years (1982 to 2015). This involves identifying plants in danger of extinction or in dramatic decline and the relationship between vegetation and rainfall by climate zone. The forest type classified as tree cover, broadleaved, deciduous, closed to open (>15%) has been degraded to 74% of its initial total area. The results also revealed that, during the study period, the vegetation of the tropical, polar, and warm temperate zones showed a higher rate of strong improvement. Although arid and boreal zones show a low rate of strong improvement, they are those that experience a low percentage of strong degradation. The continental vegetation is drastically decreasing, especially forests, and in areas with low vegetation, compared to more vegetated areas, there is more emphasis on the conservation of existing plants. The variability in precipitation is excessively hard to tolerate for more types of vegetation.

scholarly journals Effects of Windthrows on Forest Cover, Tree Growth and Soil Characteristics in Drought-Prone Pine Plantations

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 817
Author(s):  
Jesús Julio Camarero ◽  
Michele Colangelo ◽  
Antonio Gazol ◽  
Manuel Pizarro ◽  
Cristina Valeriano ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Pinus Halepensis ◽  
Soil Characteristics ◽  
Tree Cover ◽  
Mediterranean Forests ◽  
Soil Microbial Community Structure ◽  
Soil Features ◽  
Disturbance Intensity

Windstorms are forest disturbances which generate canopy gaps. However, their effects on Mediterranean forests are understudied. To fill that research gap, changes in tree, cover, growth and soil features in Pinus halepensis and Pinus sylvestris plantations affected by windthrows were quantified. In each plantation, trees and soils in closed-canopy stands and gaps created by the windthrow were sampled. Changes in tree cover and radial growth were assessed by using the Normalized Difference Vegetation Index (NDVI) and dendrochronology, respectively. Soil features including texture, nutrients concentration and soil microbial community structure were also analyzed. Windthrows reduced tree cover and enhanced growth, particularly in the P. halepensis site, which was probably more severely impacted. Soil characteristics were also more altered by the windthrow in this site: the clay percentage increased in gaps, whereas K and Mg concentrations decreased. The biomass of Gram positive bacteria and actinomycetes increased in gaps, but the biomass of Gram negative bacteria and fungi decreased. Soil gaps became less fertile and dominated by bacteria after the windthrow in the P. halepensis site. We emphasize the relevance of considering post-disturbance time recovery and disturbance intensity to assess forest resilience within a multi-scale approach.

scholarly journals Lower Noise Annoyance Associated with GIS-Derived Greenspace: Pathways through Perceived Greenspace and Residential Noise

2018 ◽  
Vol 15 (7) ◽  
pp. 1533 ◽  
Author(s):  
Angel M. Dzhambov ◽  
Iana Markevych ◽  
Boris Tilov ◽  
Zlatoslav Arabadzhiev ◽  
Drozdstoj Stoyanov ◽  
...  
Keyword(s):  
Noise Level ◽  
Vegetation Index ◽  
Green Space ◽  
Normalized Difference Vegetation Index ◽  
Buffer Zone ◽  
Tree Cover ◽  
Noise Sources ◽  
Noise Abatement ◽  
Noise Annoyance ◽  
Lower Noise

Growing amounts of evidence support an association between self-reported greenspace near the home and lower noise annoyance; however, objectively defined greenspace has rarely been considered. In the present study, we tested the association between objective measures of greenspace and noise annoyance, with a focus on underpinning pathways through noise level and perceived greenspace. We sampled 720 students aged 18 to 35 years from the city of Plovdiv, Bulgaria. Objective greenspace was defined by several Geographic Information System (GIS)-derived metrics: Normalized Difference Vegetation Index (NDVI), tree cover density, percentage of green space in circular buffers of 100, 300 and 500 m, and the Euclidean distance to the nearest structured green space. Perceived greenspace was defined by the mean of responses to five items asking about its quantity, accessibility, visibility, usage, and quality. We assessed noise annoyance due to transportation and other neighborhood noise sources and daytime noise level (Lday) at the residence. Tests of the parallel mediation models showed that higher NDVI and percentage of green space in all buffers were associated with lower noise annoyance, whereas for higher tree cover this association was observed only in the 100 m buffer zone. In addition, the effects of NDVI and percentage of green space were mediated by higher perceived greenspace and lower Lday. In the case of tree cover, only perceived greenspace was a mediator. Our findings suggest that the potential for greenspace to reduce noise annoyance extends beyond noise abatement. Applying a combination of GIS-derived and perceptual measures should enable researchers to better tap individuals’ experience of residential greenspace and noise.

scholarly journals Forest Site and Type Variability in ALS-Based Forest Resource Inventory Attribute Predictions over Three Ontario Forest Sites

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 226 ◽  
Author(s):  
Karin van Ewijk ◽  
Paul Treitz ◽  
Murray Woods ◽  
Trevor Jones ◽  
John Caspersen
Keyword(s):  
Prediction Accuracy ◽  
Forest Type ◽  
Stem Density ◽  
Forest Site ◽  
Forest Resource ◽  
Forest Types ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Forest Attributes ◽  
The Impact

Over the last decade, spatially-explicit modeling of landscape-scale forest attributes for forest inventories has greatly benefitted from airborne laser scanning (ALS) and the area-based approach (ABA) to derive wall-to-wall maps of these forest attributes. Which ALS-derived metrics to include when modeling forest inventory attributes, and how prediction accuracies vary over forest types depends largely on the structural complexity of the forest(s) being studied. Hence, the purpose of this study was to (i) examine the usefulness of adding texture and intensity metrics to height-based ALS metrics for the prediction of several forest resource inventory (FRI) attributes in one boreal and two Great Lakes, St. Lawrence (GLSL) forest region sites in Ontario and (ii) quantify and compare the site and forest type variability within the context of the FRI prediction accuracies. Basal area (BA), quadratic mean diameter-at-breast height (QMD), and stem density (S) were predicted using the ABA and a nonparametric Random Forests (RF) regression model. At the site level, prediction accuracies (i.e., expressed as RMSE (Root Mean Square Error), bias, and R2) improved at the three sites when texture and intensity metrics were included in the predictor set, even though no significant differences (p > 0.05) could be detected using the nonparametric RMANOVA test. Stem density benefitted the most from the inclusion of texture and intensity, particularly in the GLSL sites (% RMSE improved up to 6%). Combining site and forest type results indicated that improvements in site level predictions, due to the addition of texture and intensity metrics to the ALS predictor set, were the result of changes in prediction accuracy in some but not all forest types present at a site and that these changes in prediction accuracy were site and FRI attribute specific. The nonparametric Kruskal–Wallis test indicated that prediction errors between the different forest types were significantly different (p ≤ 0.01). In the boreal site, prediction accuracies for conifer forest types were higher than for deciduous and mixedwoods. Such patterns in prediction accuracy among forest types and FRI attributes could not be observed in the GLSL sites. In the Petawawa Research Forest (PRF), we did detect the impact of silvicultural treatments especially on QMD and S predictions.

scholarly journals A high-resolution spatial assessment of the impacts of drought variability on vegetation activity in Spain from 1981 to 2015

2019 ◽  
Vol 19 (6) ◽  
pp. 1189-1213 ◽  
Author(s):  
Sergio M. Vicente-Serrano ◽  
Cesar Azorin-Molina ◽  
Marina Peña-Gallardo ◽  
Miquel Tomas-Burguera ◽  
Fernando Domínguez-Castro ◽  
...  
Keyword(s):  
High Resolution ◽  
Forest Fires ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Variations ◽  
Forest Growth ◽  
Dominant Factor ◽  
Drought Severity ◽  
Vegetation Types ◽  
Vegetation Activity

Abstract. Drought is a major driver of vegetation activity in Spain, with significant impacts on crop yield, forest growth, and the occurrence of forest fires. Nonetheless, the sensitivity of vegetation to drought conditions differs largely amongst vegetation types and climates. We used a high-resolution (1.1 km) spatial dataset of the normalized difference vegetation index (NDVI) for the whole of Spain spanning the period from 1981 to 2015, combined with a dataset of the standardized precipitation evapotranspiration index (SPEI) to assess the sensitivity of vegetation types to drought across Spain. Specifically, this study explores the drought timescales at which vegetation activity shows its highest response to drought severity at different moments of the year. Results demonstrate that – over large areas of Spain – vegetation activity is controlled largely by the interannual variability of drought. More than 90 % of the land areas exhibited statistically significant positive correlations between the NDVI and the SPEI during dry summers (JJA). Nevertheless, there are some considerable spatio-temporal variations, which can be linked to differences in land cover and aridity conditions. In comparison to other climatic regions across Spain, results indicate that vegetation types located in arid regions showed the strongest response to drought. Importantly, this study stresses that the timescale at which drought is assessed is a dominant factor in understanding the different responses of vegetation activity to drought.

Forest type distribution on a calcareous terrain in western Newfoundland

1996 ◽  
Vol 72 (2) ◽  
pp. 185-192
Author(s):  
A. R. van Kesteren
Keyword(s):  
Forest Type ◽  
Forest Types ◽  
Forest Land ◽  
Photo Interpretation ◽  
Type Distribution ◽  
Mapping System ◽  
Maximum Elevation ◽  
Elevation Data ◽  
Log Linear ◽  
Air Photo

Terrain factors influencing forest type distribution on a calcareous terrain in western Newfoundland were investigated. Landform elements were mapped at a scale of 1:12,500 utilizing air photo interpretation. Minimum and maximum elevation data along with dominant forest type occurrence were determined in the field. Frequencies of landform element and forest type correspondence were tested using a log-linear G2 analysis. Additionally, elevational differences of both landform elements and forest types were analyzed using the Kruskal-Wallis test. Null hypotheses of no significant landform influence on forest type distribution and no significant elevational differentiation of landform elements were rejected. However, no significant direct elevational differentiation of forest types was detected. Results are supportive of the observations of Damman (1967), indicating a primary toposequence control on forest type distribution. Verified forest type–landform associations could aid the development of a statistically based phytogeomorphic mapping system for forest land use management in Newfoundland. Key words: forest type, landform element, phytogeomorphic mapping, air photo interpretation

scholarly journals Quantifying Drought Sensitivity of Mediterranean Climate Vegetation to Recent Warming: A Case Study in Southern California

2019 ◽  
Vol 11 (24) ◽  
pp. 2902 ◽  
Author(s):  
Chunyu Dong ◽  
Glen MacDonald ◽  
Gregory S. Okin ◽  
Thomas W. Gillespie
Keyword(s):  
High Temperatures ◽  
Southern California ◽  
Mediterranean Climate ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coastal Sage Scrub ◽  
Drought Severity ◽  
Vegetation Types ◽  
Drought Sensitivity ◽  
The Future

A combination of drought and high temperatures (“global-change-type drought”) is projected to become increasingly common in Mediterranean climate regions. Recently, Southern California has experienced record-breaking high temperatures coupled with significant precipitation deficits, which provides opportunities to investigate the impacts of high temperatures on the drought sensitivity of Mediterranean climate vegetation. Responses of different vegetation types to drought are quantified using the Moderate Resolution Imaging Spectroradiometer (MODIS) data for the period 2000–2017. The contrasting responses of the vegetation types to drought are captured by the correlation and regression coefficients between Normalized Difference Vegetation Index (NDVI) anomalies and the Palmer Drought Severity Index (PDSI). A novel bootstrapping regression approach is used to decompose the relationships between the vegetation sensitivity (NDVI–PDSI regression slopes) and the principle climate factors (temperature and precipitation) associated with the drought. Significantly increased sensitivity to drought in warmer locations indicates the important role of temperature in exacerbating vulnerability; however, spatial precipitation variations do not demonstrate significant effects in modulating drought sensitivity. Based on annual NDVI response, chaparral is the most vulnerable community to warming, which will probably be severely affected by hotter droughts in the future. Drought sensitivity of coastal sage scrub (CSS) is also shown to be very responsive to warming in fall and winter. Grassland and developed land will likely be less affected by this warming. The sensitivity of the overall vegetation to temperature increases is particularly concerning, as it is the variable that has had the strongest secular trend in recent decades, which is expected to continue or strengthen in the future. Increased temperatures will probably alter vegetation distribution, as well as possibly increase annual grassland cover, and decrease the extent and ecological services provided by perennial woody Mediterranean climate ecosystems as well.

scholarly journals Assessing vegetation response to drought in the Laohahe catchment, North China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 91-101 ◽  
Author(s):  
Xiaofan Liu ◽  
Liliang Ren ◽  
Fei Yuan ◽  
Jing Xu ◽  
Wei Liu
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Growing Season ◽  
Severity Index ◽  
Drought Severity ◽  
Seasonal Effect ◽  
Vegetation Types ◽  
The Relationship

In order to better understand the relationship between vegetation vigour and moisture availability, a correlation analysis based on different vegetation types was conducted between time series of monthly Normalized Difference Vegetation Index (NDVI) and Palmer Drought Severity Index (PDSI) during the growing season from April to October within the Laohahe catchment. It was found that NDVI had good correlation with PDSI, especially for shrub and grass. The correlation between NDVI and PDSI varies significantly from one month to another. The highest value of correlation coefficients appears in June when the vegetation is growing; lower correlations are noted at the end of growing season for all vegetation types. The influence of meteorological drought on vegetation vigour is stronger in the first half of the growing season, before the vegetation reaches the peak greenness. In order to take the seasonal effect into consideration, a regression model with seasonal dummy variables was used to simulate the relationship between NDVI and PDSI. The results showed that the NDVI–PDSI relationship is significant (α = 0.05) within the growing season, and that NDVI is an effective indicator to monitor and detect droughts if seasonal timing is taken into account.

Separation of Different Vegetation Types in ASTER and Landsat Satellite Images Using Satellite‐derived Vegetation Indices

2014 ◽  
Vol 71 (4) ◽  
Author(s):  
Mazlan Hashim ◽  
Sharifeh Hazini
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Thermal Emission ◽  
Vegetation Indices ◽  
Critical Issue ◽  
Vegetation Types ◽  
Enhanced Vegetation Index ◽  
Density Slicing ◽  
Landsat Satellite

Separation of different vegetation types in satellite images is a critical issue in remote sensing. This is because of the close reflectance between different vegetation types that it makes difficult segregation of them in satellite images. In this study, to facilitate this problem, different satellite derived vegetation indices including: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Enhanced Vegetation Index 2 (EVI2) were derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat-5 TM data. The obtained NDVI, EVI, and EVI2 images were then analyzed and interpreted in order to evaluate their effectiveness to discriminate rice and citrus fields from ASTER and Landsat data. In doing so, the Density Slicing (DS) classification technique followed by the trial and error method was implemented. The results indicated that the accuracies of ASTER NDVI and ASTER EVI2 for citrus mapping are about 75% and 65%, while the accuracies of Landsat NDVI and Landsat EVI for rice mapping are about 60% and 65%, respectively. The achieved results demonstrated higher performance of ASTER NDVI for citrus mapping and Landsat EVI for rice mapping. The study concluded that it is difficult to detect and map rice fields from satellite images using satellite-derived indices with high accuracy. However, the citrus fields can be mapped with the higher accuracy using satellite-derived indices.

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