Vegetation Index Variables Research Articles

Developing a spectral angle based vegetation index for detecting the early dying process of Chinese fir trees

Forests play an important role in global ecosystems, but natural disasters such as drought and disease and pest-induced damages often affect growth of trees and even lead to tree death. There have been various vegetation indices (VIs) developed to detect the damages of trees using remote sensing technologies. However, developing an effective and accurate VI for detecting forest damages at an earlier stage is still challenging. In this study, a total of 32 target trees and 17 reference trees were selected from one of Chinese fir plantations that account for 24% of the afforested area in China. The barks of the target trees at 20 cm and 70 cm above the ground were respectively peeled off in August of 2016 to let the trees die. The hyperspectral data were collected from the selected branches with leaves using a high-performance spectrometer HR-1024i (Spectra Vista Corporation) with 1024 bands covering the region of wavelengths from 350 nm to 2500 nm. The spectral data collection was conducted from both the target and reference trees by non-imaging monthly from August of 2016 to February of 2017 until the target trees died. Based on statistical analysis, a Green to Red Region Spectral anGle Index (GRRSGI) was proposed and compared with other ten widely used VIs to detect the early dying process of the damaged trees. The results showed that compared with the reference trees, the damaged trees reduced the reflectance peaks of green bands and the absorption valleys of red bands and the frequency distributions of spectral reflectance from the damaged trees turned from statistically normal to non-normal in the region of 550–640 nm. This indicated that the spectral bands in the region of green to red bands were sensitive to the dying process of the target trees. Moreover, the performance of the VIs for detecting the dying process of the damaged trees varied depending on the time period after the trees damaged. The proposed GRRSGI based on the spectral bands of 550–640 nm led to the performance similar to all other VIs after three months of the damages but significantly better than them in the first two months after the damages. Except for GRRSGI, the Green-Red Spectral Area Index (GRSAI) also performed better than other VIs. Compared with GRSAI, however, the proposed GRRSGI performed slight better when the spectral data of 550–640 nm were re-sampled using the spectral intervals of 5–40 nm with an increase of 5 nm and significantly better when the re-sampling of the hyperspectral data was conducted in the region of 550–670 nm. This implied the proposed GRRSGI provided the greater potential of detecting the early dying process of the damage trees.

Expression profiling of DREB1 and evaluation of vegetation indices in contrasting wheat genotypes exposed to drought stress

DREBs, the Dehydration Responsive Element binding proteins belonging to the superfamily of AP2/ERF plant transcription factors regulate diverse processes of plant development and stress responses. The expression level of DREB1 transcription factor gene was examined under drought in wheat genotypes of Azerbaijani origin differing in drought resistance: two tetraploid wheat (Triticum durum Desf.), cultivars Barakatli 95 (tolerant), Garagylchyg 2 (sensitive) and two hexaploid wheat (Triticum aestivum L.), cultivars Azamatli 95 (less sensitive), Giymatli 2/17 (sensitive), as well as German hexaploid winter wheat cultivar Batis and the synthetic hexaploid wheat accession Syn022L. The seeds were sown in pots in control and drought blocks inside the growth chamber and 12-day-old seedlings were exposed to drought stress. These genotypes were thoroughly phenotyped for variability of vegetation indices like NDVI, SR, OSAVI, ARI1, GM2 and PRI using spectro-radiometer PolyPen RP400 & RP410 under control and drought stress. In tetraploid genotypes and synthetic wheat accession, the vegetation indices were less affected by drought than in hexaploids and the response to stress recovery was faster. Drought sensitive genotypes experienced lower vegetation indices as compared to the tolerant ones. The expression of DREB1 gene was analyzed at 7 days after stress, when the visible stress-related traits were observed. The transcript level was determined by qRT-PCR using the elongation factor 1 alpha (Elf1-α) gene as an internal control. There was no genotypic difference in the basal expression of DREB1 under control conditions. Overall, the transcript levels were significantly increased among all genotypes exposed to drought stress. Futher, under drought stress the expression level of DREB1 in tolerant genotypes increased more than in drought sensitive ones. The German wheat cultivar Batis revealed the highest up-regulation of DREB1 under drought stress conditions. These data will help to screen drought stress tolerance at large scale among the diverse wheat gene pool non-invasively using digital phenotyping.

KEANEKARAGAMAN JENIS POHON DAN POTENSI SERAPAN KARBON TAMAN KEHATI BUMI PATRA, INDRAMAYU, JAWA BARAT

Pemerintah Indonesia berkomitmen menurunkan emisi gas rumah kaca, antara lain melalui pencegahan deforestasi dan penanaman pohon. Penanaman pohon di perkotaan antara lain dilakukan melalui pembangunan hutan kota dan taman keanekaragaman hayati (taman kehati). Taman kehati memiliki fungsi meningkatkan keanekaragaman hayati di perkotaan dan menyerap gas rumah kaca. Penelitian ini bertujuan untuk mengetahui keanekaragaman jenis pohon di Taman Kehati Bumi Patra, dan kontribusinya terhadap serapan karbon. Inventarisasi dan pengukuran diameter dan tinggi pohon dilakukan dengan metode sensus. Hasil penelitian mencatat Taman Kehati Bumi Patra memiliki luas 19,30 hektare memiliki tanaman 38 jenis, berjumlah 1.889 pohon atau kerapatan rata-ratanya 98 pohon per hektar. Indeks keanekaragaman jenis (H’) vegetasi di taman kehati ini adalah 3,16, dengan indeks kemerataan jenis (e) 0,90 dan indeks kekayaan jenis ® 5,36. Biomassa dan kandungan karbon di Taman Kehati Bumi Patra sebesar 123,38 ton setara dengan 61,69 ton C. Rata-rata potensi biomassa dan karbon per hektar adalah 6,38 ton/ha atau 3,120 ton C/ha. Potensi biomassa dan kandungan karbon didominasi oleh angsana (Pterocarpus indicus Willd) dan mangga (Mangifera indica L.), masing-masing sebesar 119,44 ton (59,72 ton C) dan 2,62 ton (1,31 ton C).

Drought Stress Detection in Juvenile Oilseed Rape Using Hyperspectral Imaging with a Focus on Spectra Variability

Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, ‘Cadeli’ and ‘Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to −0.96[−2.21,0.21] and −0.71[−1.97,0.49] units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of 0.33[0.16,0.68] for ‘Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes.

Carbon uptake changed but vegetation composition remained stable during transition from grazing to mowing grassland management

Grasslands could play an important role in supporting livestock, in carbon sequestration and in biodiversity conservation. Different grassland managements may change the vegetation composition of grasslands, which could alter these ecosystem services. We studied the effects of grazing vs. mowing on the vegetation composition (2012–2016) and on the carbon uptake (2011–2013) of sandy grasslands in Hungary to study if the vegetation composition differs and if it does, whether it affects carbon uptake. To observe differences in vegetation composition between the two types of management regimes we performed fine-scale vegetation survey in adjacent grazed and mowed sites. We compared species compositions and vegetation diversity indices between the management regimes based on permutational ANOVA, mixed effect model and information theory models. We used fine-scale vegetation survey because it has the potential to indicate vegetation changes within six years as changes in species richness and diversity are usually detected after 10–20 years. Carbon uptake was measured in parallel with eddy covariance technique at both sites. In spite of the contrasting management regimes the vegetation composition was stable (no differences observed in the diversity indices), while carbon uptake was significantly greater in the grazed (sink: +1 ± 0.7 t C ha−1 year−1) compared to the mowed site (source: -0.3 ± 0.6 t C ha−1 year−1). The vegetation was heterogeneous (patchy) and had a high species richness at both sites (grazed: 91 species ha−1, mowed: 90 species ha−1) which might have contributed to the stability of the vegetation composition. We concluded that differences in carbon uptake existed between the grazed vs. mowed sites due to biomass removal intensity with no differences in the vegetation composition.

Assessing winter wheat foliage disease severity using aerial imagery acquired from small Unmanned Aerial Vehicle (UAV)

One of the major goals in all wheat (Triticum aestivum L.) breeding programs is to develop disease-resistant varieties. Unmanned Aerial Vehicles (UAVs) equipped with remote sensors can provide spectral measurements that can be used to assess foliage disease severity. Measurement of disease severity trait during the genotype selection process has always been challenging as it takes a substantial amount of time, cost, and labor to phenotype many breeding lines. This study investigates the potential use of low-cost UAV, equipped with digital cameras as a field phenotyping tool for foliage disease severity in awheat breeding program. A field experiment was conducted in 2017 and 2018 at Castroville, Texas. The experiment site has favorable weather conditions for developing wheat leaf rust (Puccinia triticina f. sp.tritici). Red, Green, and Blue band (RGB) images were acquired by flying rotary-wing UAV. Images were then processed to develop orthomosaics and three vegetation indices were calculated. The obtained image dataset was further processed to generate plot-level data. Visual notes on field response and leaf rust severity were taken to calculate the coefficient of infection (CI). A significant variation in vegetation indices was found among the wheat genotypes in both years. Normalized Difference Index (NDI), Green Index (GI), and Green Leaf Index (GLI) were linearly related to CI with R2 values ranging from 0.72 to 0.79 (p < 0.05) in 2017 and 0.63 to 0.68 (p < 0.05) in 2018. Ground-based Normalized Difference Vegetation Indices (NDVI) also showed a significant relationship with CI in both years (R2 = 0.86, p < 0.05 in 2017 and R2 = 0.83, p < 0.05 in 2018). The results showed that UAVs imaging and automated data extraction can facilitate the acquisition of high throughput phenotyping data for disease severity ratings.

Temporal and Spatial Vegetation Index Variability and Response to Temperature and Precipitation in the Qinghai-Tibet Plateau Using GIMMS NDVI

Temporal and Spatial Vegetation Index Variability and Response to Temperature and Precipitation in the Qinghai-Tibet Plateau Using GIMMS NDVI

Intra-Field Canopy Nitrogen Retrieval from Unmanned Aerial Vehicle Imagery for Wheat and Corn Fields

Crop nitrogen (N) needs to be accurately predicted to allow farmers to effectively match the N supply to the crop N demand during crop growth in order to minimize environmental impacts as excess N could seep into the water supplies around the field. The objective of this study is to use Unmanned Aerial Vehicle (UAV) multispectral MicaSense imagery validated with ground hyperspectral measurements to predict canopy nitrogen weight (g/m2) of wheat and cornfields in Ontario. A simple linear regression was established to predict the canopy nitrogen weight from various vegetation indices (VI). Ratio Vegetation Index (RVI) performed the best out of all the tested vegetation indices, with an R 2 of 0.93 for the wheat fields and 0.83 for the corn fields. RVI estimation was also consistent throughout the growing season, which is optimal in precision agriculture. Once applied the RVI-based regression model to the UAV imagery, the best RMSE was 0.95 g/m2 for the wheat McColl field using the image of May 24th and 0.66 g/m2 for the corn Jack North field using the image of June 7th. Such information for accurately predicting nitrogen is important for farmers as it will lead to a more efficient fertilizer application program.

Rehabilitation of critical land by Implementing complex agroforestry at the prioritized subwatersheds in the Muria Region

&lt;pre&gt;The prioritized subwatersheds are comprised of seven subwatersheds that have been declared critical within the 52 subwatersheds in the Muria Mountains. An area of approximately 11,000 ha, the topography of the prioritized subwatersheds is wavy—the typical slope ranges from 25 to 45%—and susceptible to erosion. The purpose of this research was to evaluate agroforestry cropping patterns to support soil conservation and reclamation on critical lands. This study is a quantitative description of research conducted through survey. The results show that most of the researched area has Inceptisols soil type with sandy, clay, and loam textures. The nitrogen, phosphate, potassium, C-organic, and organic matter contents are relatively low while the vegetation Diversity Index is categorized as medium. Sengon trees dominate in the prioritized subwatersheds area, followed by mahogany, coffee, and teak with average Importance Values of 89.57, 60.24, 78.40, and 21.03, respectively. This research shows that an agroforestry system comprised of sengon trees and coffee is ideally applied in the prioritized subwatersheds. Coffee requires shade and reduces rain-induced erosion; sengon trees function as a shade while at the same time contributing to the soil as a source of nutrients. During rains, this combined agroforestry system is able to control surface runoff and soil erosion. A sengon/coffee-tree based agroforestry system is ecologically friendly and appropriate for development in the prioritized subwatersheds.&lt;/pre&gt;

Vegetation Condition of Community-Managed Forests in Aik Bual Village and Setiling Village, Lombok Island

Community-based forest management practices vary according to biophysical and management factors. This study aimed to explain the vegetation conditions of community-based forest management in Aik Bual and Setiling village, Lombok Tengah. The study site was divided into protected forest areas (HL) in Aik Bual Village with a legal community forest permit (Aik Bual-HKm), HL in Setiling Village with no legal community forest permit (Setiling-Non Permit), and HL in Aik Bual Village with no legal community forest permit (Aik Bual-Non Permit). Field measurement was conducted in July 2018 by establishing 12 plots of 20 m x 20 m. Each plot consisted of subplots of 10 m x 10 m, 5 m x 5 m, and 2 m x 2 m to collect data of woody and non-woody plants with the criteria of diameter (D) as follows: D ≥ 20 cm, 10 cm ≤ D &lt; 20 cm, 2 cm ≤ D &lt;10 cm, and D &lt; 2 cm with tree height of &lt; 1,5 m, respectively. The results showed that Aik Bual-HKm, Setiling-Non Permit and Aik Bual-Non Permit had 24, 13 and 22 species, respectively. Dominant species of vegetation at D ≥ 20 cm were Erythrina variegata and Swietenia macrophylla, at 10 cm ≤ D &lt; 20 cm were Musa paradisiaca and Durio zibethinus, at 2 cm ≤ D &lt; 10 cm was Coffea canephora, and at D &lt; 2 cm were C. canephora and S. macrophylla. Vegetation diversity index (H') of plants at D ≥ 2 cm in Aik Bual-HKm was slightly higher (H'=1,78) than that in Setiling-Non Permit (H’=1,04) and Aik Bual-Non Permit (H’=1,15), although these are classified as moderate. The results illustrated the possible differences of vegetation diversity in community-managed forests with and without legal permission.Keywords: agroforestry, land tenure, protected forest, vegetation analysis

Analysis of Spatial and Temporal Variations of Vegetation Index in Liaodong Bay in the last 30 years based on the GEE Platform

In order to determine the space-time characteristics of vegetation growing, aiming at the problems of poor efficiency in remote sensing information extraction of traditional methods, based on the Google Earth Engine (GEE) platform, NDVI data was extracted using Landsat image in the growing season from 1990 to 2019, and the space-time characteristics of vegetation were discussed with unitary linearity regression. The results showed that, 1) Taking 2010 as the turning point, NDVI of surface vegetation in Liaodong Bay showed a trend of first increase, then decrease and then increase during the past 30 years. The total area of vegetation cover have less change, while the proportion of medium-high coverage (0.6<NDVI<0.8) and high coverage (0.8<NDVI<1) increased significantly, 2) The spatial distribution of NDVI in Liaodong Bay have obvious differences, which shows a trend of gradual decrease from the Liaohe estuary delta to both sides. Affected by the development of coastal resources, NDVI increased firstly and then decreased from land to sea. In conclusion, the space-time change of NDVI in Liaodong Bay is affected by human development activities and ecological restoration. As an important quantitative factor, NDVI can provide basic data for the evaluation of environmental carrying capacity and ecological restoration.

The effect of fire on vegetation diversity indices, a case study: Sirachal research station

The effect of fire on vegetation diversity indices, a case study: Sirachal research station

Multi-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana

Operational monitoring of vegetation and its response to climate change involves the use of vegetation indices (VIs) in relation to relevant climatic data. This study analyses the temporal variations of vegetation indices in response to climatic data (temperature and precipitation) to better understand the phenological changes in the Wa-West and Tolon districts of Ghana during 1999–2011. This study also examines the inter-annual variation of vegetation indices and lag effects of climate variables (temperature and precipitation) using simple regression and correlation approaches. Results indicate that the mean Normalized Difference Vegetation Index (NDVI) and Normalized Difference Soil Index (NDSI) were significantly correlated with the mean temperature, whereby the value of NDVI increases with a decrease in temperature and value of NDSI increases with an increase in temperature. On examining seasonal variations, our findings indicated that the months of August and September have the highest mean NDVI values. This study confirms that consistently rising temperature and altered precipitation patterns have exerted a strong influence on temporal distributions and productivities of the terrestrial ecosystems of the Tolon and Wa-West districts of Ghana. Furthermore, this research demonstrates how vegetation indices can be used as an indicator to monitor phenological changes in the terrestrial ecosystem.

Application conditions and impact factors for various vegetation indices in constructing the LAI seasonal trajectory over different vegetation types

Abstract Leaf area index (LAI) is a required input for various ecological and crop models. To investigate the application conditions of various vegetation indices (VIs), especially the VIs constructed by red-edge band (VIRE) for estimating LAI, six VIs derived from Medium Resolution Imaging Spectrometer (MERIS) data were used to construct LAI seasonal trajectory for different vegetation types at 15 sites. The PROSAIL model combined with the Extended Fourier Amplitude Sensitivity Test (EFAST) method was adopted to explore the influences and physical basis of canopy biophysical and non-canopy variables on the construction of LAI seasonal trajectory using VIs. For deciduous forests, the normalized difference vegetation index (NDVI) had the highest sensitivity to LAI when LAI 2. For evergreen forests, there were no obvious differences among the sensitivities of six VIs to LAI when LAI 5. For crops, all the VIs had the similar sensitivities at LAI 3. For all three types of vegetation, the VIRE maintained relatively high sensitivity to LAI over the whole range of LAI, especially at high LAI values. The VIs were most affected by chlorophyll content (Cab) and average leaf inclination angle (ALA); their total contribution was about 85%. However, the influence of ALA on VIRE was relatively weak, implying that the VIRE had the potential to establish a universal model for LAI estimation among different vegetation types. Therefore, the optimal VIs over different ranges of LAI were suggested to estimate LAI. In addition, the VIRE should be a preferred choice for estimating LAI to reduce the simulation errors of seasonal LAI, if the RE band is available.

Dynamics of bacterial community in litter and soil along a chronosequence of Robinia pseudoacacia plantations

As the driver of plantation ecosystem function, microorganisms can decompose plant residues and soil organic matter. To identify dynamics of microbial communities in litter and soil and its influence by vegetation and soil at regional scales, the plantations of Robinia pseudoacacia at different successional stages (13, 19, 29, and 44 y) was selected on the Loess Plateau. High-throughput sequencing of the 16S rRNA gene was used to examine bacterial communities in litter and soil, and changes in vegetation, litter, and soil characteristics were analyzed. With increase of stand age, coverage and biomass of understory vegetation increased significantly and peaked at 44-y. Concentrations of carbon (C), nitrogen (N), and phosphorus (P) in litter and soil increased significantly, whereas pH values decreased significantly. Composition and diversity of bacterial communities in litter and soil were significantly different. Diversity and richness of litter bacterial communities were higher than that of soils. Relative abundances of Actinobacteria and Proteobacteria in litter were higher than that in soil; relative abundance of Acidobacteria exhibited the reverse trend. The diversity and richness index of vegetation significantly affected that of litter bacterial communities. Soil C/P significantly affected the Simpson and Shannon index of soil bacterial communities. The C/P and pH of litter and soil were significantly correlated with bacterial composition, primarily including Actinobacteria, Acidobacteria, and Gemmatimonadetes. Diversity of litter bacterial communities was more sensitive to the diversity and richness of vegetation flora than that of soil in the succession of R. pseudoacacia. Canopy density, vegetation, and litter and soil nutrients might directly or indirectly affect bacterial communities. Carbon, phosphorus, and pH may be critical factors influencing the composition of bacterial communities in litter and soil.

Effects of Land-Use Practices on Woody Plant Cover Dynamics in Sahelian Agrosystems in Burkina Faso since the 1970s–1980s Droughts

The 1970s–1980s droughts in the Sahel caused a significant degradation of land and plant cover. To cope with this situation, populations have developed several biophysical and social adaptation practices. Many of these are agroforestry practices and contribute to the maintenance of agrosystems. Unfortunately, they remain insufficiently documented and their contributions to the resilience of agrosystems insufficiently evaluated. Many authors widely link the regreening in the Sahel after droughts to the resumption of rainfall. This study examines the contribution of agroforestry practices to the improvement of woody plant cover in the North of Burkina Faso after the 1970s–1980s droughts. The examination of practices is carried out by integrating the rainfall, soil, and geomorphology variables. Landsat images are used to detect changes in woody plant cover: increasing, decreasing, and no-change in the Enhanced Vegetation Index. In addition, 230 field observations, coupled with interviews conducted on the different categories of change, have allowed to characterize the biophysical environment and identify land-use practices. The results show a variability of vegetation index explained to 9% (R2 = 0.09) by rainfall. However, Chi-Squared independence tests show a strong dependence between changes in woody plant cover and geomorphology (p = 0.0018 *), land use, land cover (p = 0.0001 *), and land-use practices (p = 0.0001 *). Our results show that rainfall alone is not enough to explain the dynamics of agrosystems’ woody plant cover. Agricultural and social practices related to the dynamics of farmer perceptions play a key role.

DISCRIMINATION AND CHARACTERIZATION OF PROMINENT DESERTIC VEGETATIONS USING HYPERSPECTRAL IMAGING DATA

Abstract. Imaging Hyperspectral data are advent as potential solutions in modeling, discrimination and mapping of vegetation species. Hyperspectral remote sensing provides valuable information about vegetation type, leaf area index, chlorophyll, and leaf nutrient concentration. Estimation of these vegetation parameters has been made possible by calculating various vegetation indices (VIs), usually by ratioing, differencing, ratioing differences and combinations of suitable spectral band. This paper presents a ground-based hyperspectral imaging system for characterizing vegetation spectral features. In this study, a ground-based hyperspectral imaging data (AISA VNIR 400–960 nm, Spectral Resolution @ 2.5 nm) was used for spectral vegetation discrimination and characterization of natural desertic tree species. This study assessed the utility of hyperspectral imagery of 240 narrow bands in discrimination and classification of desert tree species in Jodhpur region using ENVI software. Vegetation indices derived from hyperspectral images used in the Analysis for tree species classification discrimination study. Prominent occurring two desertic tree species, viz., Neem and Babul in Jodhpur region could be effectively discriminated. Study demonstrated the potential utility of narrow spectral bands of Hyperspectral Imaging data in discriminating vegetation species in a desertic terrain.

Isolating the Observed Influence of Vegetation Variability on the Climate of La Plata River Basin

AbstractThis work aims to isolate and quantify the local and remote biogeophysical influences of slowly varying vegetation variability on the climate of La Plata basin (LPB) in the austral spring season (September–November) using observational records. Past studies have shown strong land–atmosphere coupling in LPB during this season. The analysis uses a 34-yr record (1981–2014) of the modified enhanced vegetation index (EVI2) from the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology dataset and the third-generation normalized difference vegetation index (NDVI) from Global Inventory Modeling and Mapping Studies. The dominant patterns of vegetation index variability in space and time are assessed using empirical orthogonal function/principal component analysis over the LPB. The dominant mode in the austral spring is a vegetation dipole, with greening (browning) or positive (negative) vegetation index anomalies in the northeastern (southwestern) part of the basin. Using the stepwise generalized equilibrium feedback assessment (SGEFA), the effect of the vegetation variability on the atmosphere is then isolated. The dominant mode of LPB vegetation variability in austral spring is related to warmer temperatures in the southwest LPB and enhanced precipitation over the central and southern parts of the basin. A mechanism is proposed for the increase in latent heat flux and cooler temperatures in the northeastern LPB due to greening, and the increase in sensible heat flux, warmer temperatures, and decrease in surface pressure in southwestern LPB due to browning. The geostrophic response to this induced pressure gradient leads to anomalous northerly enhancement of moisture-laden winds, deeper penetration of moisture into LPB, and increased precipitation over the central and southern parts of the basin.

The Diversity of Riparian Trees Vegetation at Around The Lawo River, South Sulawesi, Indonesia

Abstrak. The study aimed to examine the diversity of riparian tree vegetation on the banks of the Lawo River in Soppeng Regency. This research is descriptive and carried out for three months, starting from June to August 2018. This study uses a quadrant method with a plot size of 20 m x 20 m. Data analysis was performed to calculate diversity index, evenness index, and similarity index of riparian tree vegetation. The results showed that riparian tree vegetation found in the littoral zone of the Lawo River totaled nineteen (19) species belonging to eight families. Plant Gmeliana arborea (fam: Verbenaceae) is the most common plant. Species Diversity Index is a medium category. The Species Evenness Index is high (close to 1). Riparian tree vegetation on the banks of the Lawo river observed at five points shows almost the same vegetation conditions.

KEANEKARAGAMAN JENIS VEGETASI TINGKAT POHON DI HUTAN ADAT GUNUNG SOKA DUSUN PADANG SEBATIK KECAMATAN AIR BESAR KABUPATEN LANDAK

Forest is an ecosystem unit in the form of a stretch of land containing biological natural resourcesdominated by trees in its natural environment which can not be separated from the life of indigineous communities. This study aims to find out the diversity of vegetation types of stand composition trees in Gunung Soka Indigenous Forest. This study used transect method and the transect lineswere determined purposively. There were 4 (four) transect lines with 500 m lenght, 10 m wide to the left and 10 m wide to the right. The observation plot was 20 m, and there were 25 plots, so the total was 1 ha. There were 100 plots to study with 4 transect line so the total area was 4 ha. The result show that there are 23 trees vegetation consists of 13 family, 741 of individual trees in Gunung Soka Indigenous Forest. The highest important value index (INP) was found in engkabang bukit (Shorea pinanga Scheff.) with a value of 82,25, while the lowest important value index was found in keraci (Quercus lucida Roxb.) with a value of 1,42. The Dominance index (C) of trees vegetation is 0,17525 or C = 1 ,which shows that there are more than one dominant tree. The Diversity index (DS) of trees vegetation is closte to 1, which shows moderate diversity of species. The Highest species Abundance index (e) of tree vegetation was found in line 1 with a value of 0,9493, meanwhile the lowest value was found in line 2 with a value of 0,5764.Kata Kunci : Diversity,indigenous forest, tree vegetation