scholarly journals Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

2015 ◽  
Vol 45 (2) ◽  
pp. 167-174 ◽  
Author(s):  
Symone Maria de Melo FIGUEIREDO ◽  
Eduardo Martins VENTICINQUE ◽  
Evandro Orfanó FIGUEIREDO ◽  
Evandro José Linhares FERREIRA
Keyword(s):  
Tree Species ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Elevation Gradient ◽  
Forest Tree ◽  
Entropy Method ◽  
Slope Aspect ◽  
Tropical Species ◽  
Ecological Requirements ◽  
Timber Tree

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

scholarly journals Spatial analysis of damaged vegetation in the Mianyuan River basin after the Wenchuan Earthquake

2015 ◽  
Vol 3 (5) ◽  
pp. 3225-3250
Author(s):  
H. Z. Zhang ◽  
J. R. Fan ◽  
X. M. Wang ◽  
T. H. Chi ◽  
L. Peng
Keyword(s):  
Slope Stability ◽  
Wenchuan Earthquake ◽  
River Basin ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Probabilistic Approach ◽  
Model Development ◽  
Slope Aspect ◽  
2008 Wenchuan Earthquake ◽  
Elevation Model

Abstract. The 2008 Wenchuan earthquake destroyed large areas of vegetation. Presently, these areas of damaged vegetation are at various stages of recovery. In this study, we present a probabilistic approach for slope stability analysis that quantitatively relates data on earthquake-damaged vegetation with slope stability in a given river basin. The Mianyuan River basin was selected for model development, and earthquake-damaged vegetation and post-earthquake recovery conditions were identified via the normalized difference vegetation index (NDVI), from multi-temporal (2001–2014) remote sensing images. DSAL (digital elevation model, slope, aspect, and lithology) spatial zonation was applied to characterize the survival environments of vegetation, which were used to discern the relationships between successful vegetation regrowth and environmental conditions. Finally, the slope stability susceptibility model was trained through multivariate analysis of earthquake-damaged vegetation and its controlling factors (i.e. topographic environments and material properties). Application to the Subao River basin validated the proposed model, showing that most of the damaged vegetation areas have high susceptibility levels (88.1% > susceptibility level 3, and 61.5% > level 4). Our modelling approach may also be valuable for use in other regions prone to landslide hazards.

scholarly journals Towards improved, cost-effective surveillance of Ixodes ricinus ticks and associated pathogens using species distribution modelling

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Manuela Signorini ◽  
Anna-Sofie Stensgaard ◽  
Michele Drigo ◽  
Giulia Simonato ◽  
Federica Marcer ◽  
...  
Keyword(s):  
Ixodes Ricinus ◽  
Habitat Suitability ◽  
Pathogen Detection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cost Effective ◽  
Limiting Factor ◽  
Sampling Effort ◽  
Remotely Sensed Data ◽  
Ecological Requirements

Various ticks exist in the temperate hilly and pre-alpine areas of Northern Italy, where Ixodes ricinus is the more important. In this area different tick-borne pathogen monitoring projects have recently been implemented; we present here the results of a twoyear field survey of ticks and associated pathogens, conducted 2009-2010 in North-eastern Italy. The cost-effectiveness of different sampling strategies, hypothesized a posteriori based on two sub-sets of data, were compared and analysed. The same two subsets were also used to develop models of habitat suitability, using a maximum entropy algorithm based on remotely sensed data. Comparison of the two strategies (in terms of number of ticks collected, rates of pathogen detection and model accuracy) indicated that monitoring at many temporary sites was more cost-effective than monthly samplings at a few permanent sites. The two model predictions were similar and provided a greater understanding of ecological requirements of I. ricinus in the study area. Dense vegetation cover, as measured by the normalized difference vegetation index, was identified as a good predictor of tick presence, whereas high summer temperatures appeared to be a limiting factor. The study suggests that it is possible to obtain realistic results (in terms of pathogens detection and development of habitat suitability maps) with a relatively limited sampling effort and a wellplanned monitoring strategy.

scholarly journals Mapping Forest Fire Risk—A Case Study in Galicia (Spain)

2020 ◽  
Vol 12 (22) ◽  
pp. 3705
Author(s):  
Ana Novo ◽  
Noelia Fariñas-Álvarez ◽  
Joaquín Martínez-Sánchez ◽  
Higinio González-Jorge ◽  
José María Fernández-Alonso ◽  
...  
Keyword(s):  
Forest Fire ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Risk ◽  
Fire Regimes ◽  
Slope Aspect ◽  
Fire Weather Index ◽  
Novel Approach ◽  
Fuel Model ◽  
Forest Fire Risk

The optimization of forest management in roadsides is a necessary task in terms of wildfire prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing a decision-making support about vegetation management for firefighting. In this study, nine relevant parameters: elevation, slope, aspect, road distance, settlement distance, fuel model types, normalized difference vegetation index (NDVI), fire weather index (FWI), and historical fire regimes, were considered as indicators of the likelihood of a forest fire occurrence. The parameters were grouped in five categories: topography, vegetation, FWI, historical fire regimes, and anthropogenic issues. This paper presents a novel approach to forest fire risk mapping the classification of vegetation in fuel model types based on the analysis of light detection and ranging (LiDAR) was incorporated. The criteria weights that lead to fire risk were computed by the analytic hierarchy process (AHP) and applied to two datasets located in NW Spain. Results show that approximately 50% of the study area A and 65% of the study area B are characterized as a 3-moderate fire risk zone. The methodology presented in this study will allow road managers to determine appropriate vegetation measures with regards to fire risk. The automation of this methodology is transferable to other regions for forest prevention planning and fire mitigation.

scholarly journals FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 593-596 ◽  
Author(s):  
Shou Hao Chiang ◽  
Miguel Valdez ◽  
Chi-Farn Chen
Keyword(s):  
Maximum Entropy ◽  
Satellite Imagery ◽  
Tree Species ◽  
Maximum Entropy Method ◽  
Forest Tree ◽  
Entropy Method ◽  
Surface Reflectance ◽  
Species Classification ◽  
Forest Tree Species ◽  
Tree Species Classification

Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. <br><br> In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled with terrain variables produced better result, with the higher overall accuracy and kappa coefficient than first experiment. The results indicate that the Maximum Entropy method is an applicable, and to classify tree species using satellite imagery data coupled with terrain information can improve the classification of tree species in the study area.

scholarly journals FOREST TREE SPECIES DISTRIBUTION MAPPING USING LANDSAT SATELLITE IMAGERY AND TOPOGRAPHIC VARIABLES WITH THE MAXIMUM ENTROPY METHOD IN MONGOLIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 593-596 ◽  
Author(s):  
Shou Hao Chiang ◽  
Miguel Valdez ◽  
Chi-Farn Chen
Keyword(s):  
Maximum Entropy ◽  
Satellite Imagery ◽  
Tree Species ◽  
Maximum Entropy Method ◽  
Forest Tree ◽  
Entropy Method ◽  
Surface Reflectance ◽  
Species Classification ◽  
Forest Tree Species ◽  
Tree Species Classification

Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. &lt;br&gt;&lt;br&gt; In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled with terrain variables produced better result, with the higher overall accuracy and kappa coefficient than first experiment. The results indicate that the Maximum Entropy method is an applicable, and to classify tree species using satellite imagery data coupled with terrain information can improve the classification of tree species in the study area.

scholarly journals Greening and Browning Trends across Peru’s Diverse Environments

2020 ◽  
Vol 12 (15) ◽  
pp. 2418 ◽  
Author(s):  
Molly H. Polk ◽  
Niti B. Mishra ◽  
Kenneth R. Young ◽  
Kumar Mainali
Keyword(s):  
Time Series ◽  
Protected Area ◽  
Landscape Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Elevation Gradient ◽  
Positive Trend ◽  
Scientific Legacy ◽  
Alexander Von Humboldt ◽  
Moderate Resolution Imaging Spectroradiometer

If he were living today, Alexander von Humboldt would be using current technology to evaluate change in the Andes. Inspired by von Humboldt’s scientific legacy and the 2019 celebrations of his influence, we utilize a Moderate Resolution Imaging Spectroradiometer (MODIS)time-series vegetation index to ask questions of landscape change. Specifically, we use an 18-year record of Normalized Difference Vegetation Index (NDVI) data as a proxy to evaluate landscape change in Peru, which is well known for its high biological and ecological diversity. Continent-level evaluations of Latin America have shown sites with a positive trend in NDVI, or “greening” and “browning”, a negative trend in NDVI that suggests biophysical or human-caused reductions in vegetation. Our overall hypothesis was that the major biomes in Peru would show similar NDVI change patterns. To test our expectations, we analyzed the NDVI time-series with Thiel-Sen regression and evaluated Peru overall, by protected area status, by biome, and by biome and elevation. Across Peru overall, there was a general greening trend. By protected area status, surprisingly, the majority of greening occurred outside protected areas. The trends were different by biome, but there were hotspots of greening in the Amazon, Andean Highlands, and Drylands where greening dominated. In the Tropical Subtropical Dry Broadleaf Forest biome, greening and browning signals were mixed. Greening trends varied across the elevation gradient, switching from greening, to browning, and then back to greening as elevation increased. By biome and elevation, the results were variable. We further explored biome-specific drivers of greening and browning drawing on high-resolution imagery, the literature, and field expertise, much as we imagine von Humboldt might have approached similar questions of landscape dynamism.

scholarly journals Multi-scale selection models predict breeding habitat for two Arctic-breeding raptor species

2020 ◽  
Vol 6 (1) ◽  
pp. 24-40
Author(s):  
Philippe Galipeau ◽  
Alastair Franke ◽  
Mathieu Leblond ◽  
Joel Bêty
Keyword(s):  
Habitat Selection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spatial Scales ◽  
Environmental Indicators ◽  
Breeding Habitat ◽  
Slope Aspect ◽  
Peregrine Falcon ◽  
Apex Predators ◽  
Selection Models

Raptors are important environmental indicators because they are apex predators and can be sensitive to disturbance. Few studies have addressed habitat preferences of tundra-nesting raptors, and those that exist have focused on fine-scale characteristics. With increasing economic development predicted to occur throughout the Canadian Arctic, the investigation of raptor breeding habitat at broad spatial scales is required. We modeled breeding habitat selection for two raptor species on north Baffin Island, NU, Canada. During aerial surveys conducted over six breeding seasons, we documented 172 peregrine falcon (Falco peregrinus tundrius) and 160 rough-legged hawk (Buteo lagopus) nesting sites. We used these locations in conjunction with remote sensing data to build habitat selection models at three spatial scales. Topography, distance to water, and normalized difference vegetation index explained selection at all scales; slope aspect was also important at the finest scale. To validate landscape scale models, we conducted a validation survey that resulted in the detection of 45 new nests (peregrine falcon n = 21, rough-legged hawk n = 24). We did not detect any new nests in areas where model-predicted occurrence was expected to be low. Conversely, we found more than half of previously undetected nests in areas where model-predicted occurrence was expected to be high.

Scale-Location Dependence of the Relationship between NDVI and Environmental Factors in Wuyi Mountain

2014 ◽  
Vol 955-959 ◽  
pp. 3828-3834
Author(s):  
Wei Cheng Zou ◽  
G. R. Xiao
Keyword(s):  
Environmental Factors ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Windward Side ◽  
Slope Aspect ◽  
Leeward Side ◽  
Small Scale ◽  
Medium Scale ◽  
Wavelet Coherency

The correlation between Normalized Difference Vegetation Index (NDVI) and environmental factors is examined at different scales and locations in world heritage of Wuyi Mountain by wavelet coherency. These factors are elevation, slope, aspect, distance to nearest resident, distance to nearest road , and distance to nearest river along two transects based on data of DEM, residents, roads, rivers and ALOS remote sensing image in 2009.The results show that:(1) The relationships between NDVI and environmental factors change along with scale. The relationships between NDVI and environmental factors in the first transect are all weak at small scale (<480m). At medium scale (480-7680m), NDVI is significantly correlated with elevation, slope, resident , and road. At large scale (>7680m), NDVI is significantly correlated with elevation, resident and river. For the second transect, NDVI is significantly correlated with aspect at small scale; and significantly correlated with elevation, aspect, slope and river at medium scale; and significantly correlated with elevation, aspect, and slope at large scale. Thus elevation is the dominant controlling factors on the vegetation cover.(2)The relationships between NDVI and environmental factors also change when location changes. There is positive correlation between NDVI and elevation below the altitude of 600 m and the windward side of the southeast monsoon above 600m, while it is negative in the leeward side above 600m. Besides, NDVI is directly related with road, resident, slope, and river in the areas where the elevation is below 1200m, but inversely above 1200m.

scholarly journals Forest Tree Composition: A Comparative Study of Timber Species in Bayelsa State Nigeria

2020 ◽  
Vol 2 (2) ◽  
pp. 64-73
Author(s):  
Samuel Olatokunbo Ihinmikaiye ◽  
Bernard Edache Ochekwu ◽  
Josiah Muonam Ikuli ◽  
Doris Akinjagunla Atinuke ◽  
Abel Zikenal Keresinbofa
Keyword(s):  
Tree Species ◽  
Basal Area ◽  
Ground Level ◽  
Diversity Indices ◽  
Forest Tree ◽  
Timber Species ◽  
Anthropogenic Pressure ◽  
Sample Plot ◽  
Management Options ◽  
Timber Tree

Measuring tree species diversity is critical for forest management, particularly where timber species suffer undue anthropogenic pressure. This study was carried out in Bayelsa State, Nigeria. A sample plot was systematically chosen from randomly selected communities in each of the three senatorial districts Bayelsa West (BW), Bayelsa East (BE) and Bayelsa Central (BC) of the State. Each sample plots measured 25 m x 25 m and all timber tree species that were at least six feet above ground level within each sample plot were identified, counted and measured. Fifty individual timbers were encountered in the sample plot at Ogobiri community in BW, fifty-two at Kolo 1 community in BE and fifty-six at Gbarain community in BC belonged to 18, 16 and 14 different families respectively. Families with the largest number of species in the plots were Gentianaceae and Meliaceae, and the highest diversity indices were recorded from BE senatorial district. Generally, the basal area of the sample plots increases with an increase in diameter at breast height. The forested zones were on flat terrain characterized by seasonal flood inundation, and the similarities of timber species in the plots occurred as (BW-BC)> (BW-BE)> (BC-BE). Also, four tree species Coelocaryon preussii, Sacoglottis gabonensis, Milicia excelsa and Triplochiton scleroxylon were identified as rare species, and management options that would ensure ad infinitum supply of timber species were proposed.

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