Search results for: forest vegetation

Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Eke Bala Sophie Michelle

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The renewable resource character of NTFPs is an opportunity to its sustainability, this study analyzed the role of social capital in the adoption of sustainable management practices of NTFPs by households in the community forest (CF) Morikouali-ye. The analysis shows that 67% of households surveyed perceive the level of degradation of NTFPs in their CF as time passes and are close to 74% for adoption of sustainable management practices of NTFPs that are domestication, sustainable management of the CF, the logging ban trees and uprooting plants, etc. 26% refused to adopt these practices estimate that, at 39% it is better to promote logging in the CF. The estimated probit model shows that social capital through trust, solidarity and social inclusion significantly influences the probability of households to adopt sustainable NTFP management practices. In addition, age, education level and income from the sale of NTFPs have a significant impact on the probability of adoption. The probability of adoption increases with the level of education and confidence among households. So should they be animated by a spirit of solidarity and trust and not let a game of competition for sustainable management of NTFPs in their CF.

Keywords: community forest, social capital, NTFP, trust, solidarity, social inclusion, sustainable management

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Authors: U. Isyaku, C. Upton, J. Dickinson

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Critical institutional approach for understanding pathways to shared prosperity among forest communities enabled questioning the underlying rational choice assumptions that have dominated traditional institutional thinking in natural resources management. Common pool resources framing assumes that communities as social groups share collective interests and values towards achieving greater development. Hence, policies related to natural resources management in the global South prioritise economic prosperity by focusing on how to maximise material benefits and improve the livelihood options of resource dependent communities. Recent trends in commodification and marketization of ecosystem goods and services into tradable natural capital and incentivising conservation are structured in this paradigm. Several researchers however, have problematized this emerging market-based model because it undermines cultural basis for protecting natural ecosystems. By exploring how forest people’s motivations for conservation differ within the context of reducing emissions from deforestation and forest degradation (REDD+) project in Nigeria, we aim to provide an alternative approach to conceptualising prosperity beyond the traditional economic thinking. Through in depth empirical work over seven months with five communities in Nigeria’s Cross River State, Q methodology was used to uncover communities’ perspectives and meanings of forest values that underpin contemporary and historic conservation practices, expected benefits, and willingness to participate in the REDD+ process. Our study finds six discourses about forest and conservation values that transcend wealth creation, poverty reduction and livelihoods. We argue that communities’ decisions about forest conservation consist of a complex mixture of economic, emotional, moral, and ecological justice concerns that constitute new meanings and dimensions of prosperity. Prosperity is thus reconfigured as having socio-cultural and psychological pathways that could be derived through place identity and attachment, connectedness to nature, family ties, and ability to participate in everyday social life. We therefore suggest that natural resources policy making and development interventions should consider institutional arrangements that also include the psycho-cultural dimensions of prosperity among diverse community groups.

Keywords: critical institutionalism, Q methodology, REDD+, shared prosperity

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Authors: Richard Mbatu

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Implementation of the Reducing Emissions from Deforestation and forest Degradation (REDD+) program will not only lead to significant net gains in greenhouse gas reduction but also gains in biodiversity conservation. However, the looming paradigm shift in the program in the form of the proposed landscape governance approach could change this inclination. The concern lies with the fact that pursue of carbon credits by governments and private entities under the proposed landscape approach could encourage obstinate land use behaviors that are detrimental to the cause of biodiversity conservation and ecosystem services. Yet, the landscape approach could also stimulate governments to develop and implement land use management policies for climate change adaptation and mitigation. Using two potential areas of land use under the proposed landscape approach – carbon farming in grasslands and carbon farming in plantations – this paper provides a balanced analytical review of conservation challenges and opportunities for forest governance and beyond under the proposed landscape approach to REDD+. The paper argues that such a balanced view will enable policymakers and other stakeholders to better present their arguments in their efforts to shape the course of the REDD+ program in the post-Paris Agreement era.

Keywords: biodiversity conservation, REDD+, forest governance, grasslands, landscape approach, plantations

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Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

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Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

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Authors: A. Cittadino, P. Gantes, C. Coviella, M. Casset, A. Sanchez Caro

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Three currently active landfills receive the waste from Buenos Aires city and the Great Buenos Aires suburbs. One of the first landfills to receive solid waste from this area was located in Villa Dominico, some 7 km south from Buenos Aires City. With an area of some 750 ha, including riparian habitats, divided into 14 cells, it received solid wastes from June 1979 through February 2004. In December 2010, a biological monitoring program was set up by CEAMSE and Universidad Nacional de Lujan, still operational to date. The aim of the monitoring program is to assess the state of several biological groups within the landfill and to follow their dynamics overtime in order to identify if any, early signs of damage the landfill activities might have over the biota present. Bird and rodent populations, aquatic and terrestrial invertebrates’ populations, cells vegetation coverage, and surrounding areas vegetation coverage and main composition are followed by quarterly samplings. Bird species richness and abundance were estimated by observation over walk transects on each environment. A total of 74 different species of birds were identified. Species richness and diversity were high for both riparian surrounding areas and within the landfill. Several grassland -typical of the 'Pampa'- bird species were found within the landfill, as well as some migratory and endangered bird species. Sherman and Tomahawk traps are set overnight for small mammal sampling. Rodent populations are just above detection limits, and the few specimens captured belong mainly to species common to rural areas, instead of city-dwelling species. The two marsupial species present in the region were captured on occasions. Aquatic macroinvertebrates were sampled on a watercourse upstream and downstream the outlet of the landfill’s wastewater treatment plant and are used to follow water quality using biological indices. Water quality ranged between weak and severe pollution; benthic invertebrates sampled before and after the landfill, show no significant differences in water quality using the IBMWP index. Insect biota from yellow sticky cards and pitfall traps showed over 90 different morphospecies, with Shannon diversity index running from 1.9 to 3.9, strongly affected by the season. An easy-to-perform non-expert demandant method was used to assess vegetation coverage. Two scales of determination are utilized: field observation (1 m resolution), and Google Earth images (that allow for a better than 5 m resolution). Over the eight year period of the study, vegetation coverage over the landfill cells run from a low 83% to 100% on different cells, with an average between 95 to 99% for the entire landfill depending on seasonality. Surrounding area vegetation showed almost 100% coverage during the entire period, with an average density from 2 to 6 species per sq meter and no signs of leachate damaged vegetation.

Keywords: biological indicators, biota monitoring, landfill species diversity, waste management

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Authors: Abubakar Aminu

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Sand dunes, as a major product of desertification, is well known to affect soil resources, water resources and vegetation, especially in arid and semi-arid region; this scenario disrupt the livelihood security of people in the affected areas. The research assessed the episode of sand dune accumulation on water resources, soil and vegetation in Gada local government of Sokoto State, Nigeria. In this paper, both qualitative and quantitative methods were used to generate data which was analyzed and discussed. The finding of the paper shows that livelihood was affected by accumulations of sand dunes as water resources and soils were affected negatively thereby reducing crop yields and making livestock domestication a very difficult and expensive task; the finding also shows that 60% of the respondents agreed to planting of trees as the major solution to combat sand dunes accumulation. However, the soil parameters tested indicated low Organic carbon, low Nitrogen, low Potassium, Calcium and Phosphorus but higher values were recorded in Sodium and Cation exchange capacity which served as evidence of the high or strong aridity nature of the soil in the area. In line with the above, the researcher recommended a massive tree planting campaign to curtail desertification as well as using organic manures for higher agricultural yield and as such, improvement in livelihood security.

Keywords: soils, vegetatio, water, desertification

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Authors: Najoua El Hajjaji El Idrissi, Necip Gokhan Kasapoglu

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Polarimetric Synthetic Aperture Radar-based imaging is a powerful technique used for earth observation and classification of surfaces. Forest evolution has been one of the vital areas of attention for the remote sensing experts. The information about forest areas can be achieved by remote sensing, whether by using active radars or optical instruments. However, due to several weather constraints, such as cloud cover, limited information can be recovered using optical data and for that reason, Polarimetric Synthetic Aperture Radar (PolSAR) is used as a powerful tool for forestry inventory. In this [14paper, we applied support vector machine (SVM) and Mahalanobis distance to the fully polarimetric AIRSAR P, L, C-bands data from the Nezer forest areas, the classification is based in the separation of different tree ages. The classification results were evaluated and the results show that the SVM performs better than the Mahalanobis distance and SVM achieves approximately 75% accuracy. This result proves that SVM classification can be used as a useful method to evaluate fully polarimetric SAR data with sufficient value of accuracy.

Keywords: classification, synthetic aperture radar, SAR polarimetry, support vector machine, mahalanobis distance

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Authors: Saveena Bogtapa, Jagbir Singh Kirti

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Himalaya is one of the most fascinating ranges in the world. In India, it comprises 18 percent of the land area. Lahoul valley which is a part of Trans-Himalaya region is well known for its unique, diverse flora and fauna. It lies in the North-Eastern corner of the state Himachal Pradesh where its altitude ranges between 2500m to 5000m. Vegetation of this region is dry-temperate to alpine type. The diversity of the area is very less, rare, unique and highly endemic. But today, as a lot of environmental degradation has taken place in this hot spot of biodiversity because of frequent developmental and commercial activities which lead to the diversity of this area comes under a real threat. Therefore, as part of the research, butterflies which are known for their attractiveness as well as usefulness to the ecosystem, are used for the study. The diversity of butterflies of a particular area not only provides a healthy environment but also serves as the first step of conservation to the biodiversity. Their distribution in different habitats and altitude type helps us to understand the species richness and abundance in an area. Moreover, different environmental parameters which affect the butterfly community has also recorded. Hence, the present study documents the butterfly diversity in an unexplored habitat and altitude types at Lahoul valley. The valley has been surveyed along with altitudinal gradients (from 2500m to 4500m) and in various habitats like agriculture land, grassland, scrubland, riverine and in different types of forests. Very rare species of butterflies have been explored, and these will be discussed along with different parameters during the presentation.

Keywords: butterflies, diversity, Lahoul valley, altitude, vegetation

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Authors: Zouhaier Nasr, Mohamed Nouri

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The increase in greenhouse gases since the pre-industrial period is a real threat to disrupting the balance of marine and terrestrial ecosystems. Along with the oceans, forest soils are considered to be the planet's second-largest carbon sink. North African forests have been subject to alarming degradation for several decades. The objective of this investigation is to determine and quantify the effect of thinning practiced in pine forests in northern Tunisia on the storage of organic carbon in the trees and in the soil. The plot planted in 1989 underwent thinning in 2005 on to plots; the density is therefore 1600 trees/ha in control and 400 trees/ha in thinning. Direct dendrometric measurements (diameter, height, branches, stem) were taken. In the soil part, six profiles of 1m / 1m / 1m were used for soil and root samples and biomass and organic matter measurements. The measurements obtained were statistically processed by appropriate software. The results clearly indicate that thinning improves tree growth, so the diameter increased from 24.3 cm to 30.1 cm. Carbon storage in the trunks was 35% more and 25% for the whole tree. At ground level, the thinned plot shows a slight increase in soil organic matter and quantity of carbon per tree, exceeding the control by 10 to 25%.

Keywords: forest, soil, carbon, climate change, Tunisia

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Authors: Margareta Rahayuningsih, Nur Rahayu Utami, Tsabit A. M., Muh. Abdullah

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Mount Ungaran is one area that has remaining natural forest in Central Java, Indonesia. Mount Ungaran consists of several habitats that supporting appropriate areas for flora, fauna, and microorganisms biodiversity, particularly of it is protected by government law and IUCN red list data. Therefore, Mount Ungaran also settled up as AZE (Alliance for Zero Extinction) and IBA (Important Bird Area). The land use for agriculture and plantation reduces forest covered areas. It is serious threat to the existence of biodiversity in Moun Ungaran. This research has been identified community local wisdom that possible to be integrated as ethno-biological research and biodiversity conservation. The result showed at least four local wisdom that possible to be integrated to ethno-biological and biodiversity conservation were Wit Weh Woh (a ceremony of life-giving tree), Grebeg Alas Susuk Wangan (a ceremony for forest protection), Iriban (a ceremony of clean water resource protection), and tingkep tandur (a ceremony for ready-harvested plant protection). It is needed ethno-biological researches of local wisdom-contained values, which essential to be developed as a strategy for biodiversity conservation in Mount Ungaran.

Keywords: Mount Ungaran, local wisdom, biodiversity, fragmentation

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Authors: Sakshi Gupta, Kavita Sardana

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Management of a forest catchment involves diverse dimensions, multiple stakeholders, and conflicting interests, primarily due to the wide variety of valuable ecosystem services offered by it. Often, the coordination among different levels of formal institutions governing the catchment, local communities, as well as societal norms, taboos, customs and practices, happens to be amiss, leading to conflicting policy interventions which prove detrimental for such resources. In the case of Ala Catchment, which is a protected forest located at a distance of 9 km North-East of the town of Dalhousie, within district Chamba of Himachal Pradesh, India, and serves as one of the primary sources of public water supply for the downstream town of Dalhousie and nearby areas, several policy measures have been adopted for the restoration of the forest catchment, as well as for the improvement of public water supply. These catchment forest restoration measures include; the installation of a fence along the perimeter of the catchment, plantation of trees in the empty patches of the forest, construction of check dams, contour trenches, contour bunds, issuance of grazing permits, and installation of check posts to keep track of trespassers. While the measures adopted to address the acute shortage of public water supply in the Dalhousie region include; building and maintenance of large capacity water storage tanks, laying of pipelines, expanding public water distribution infrastructure to include water sources other than Ala Catchment Forest and introducing of five new water supply schemes for drinking water as well as irrigation. However, despite these policy measures, the degradation of the Ala catchment and acute shortage of water supply continue to distress the region. This study attempts to conduct an institutional analysis to assess the impact of policy measures for the restoration of the Ala Catchment in the Chamba district of Himachal Pradesh in India. For this purpose, the theoretical framework of Ostrom’s Institutional Assessment and Development (IAD) Framework was used. Snowball sampling was used to conduct private interviews and focused group discussions. A semi-structured questionnaire was administered to interview a total of 184 respondents across stakeholders from both formal and informal institutions. The central hypothesis of the study is that the interplay of formal and informal institutions facilitates the implementation of policy measures for ameliorating Ala Catchment, in turn improving the livelihood of people depending on this forest catchment for direct and indirect benefits. The findings of the study suggest that leakages in the successful implementation of policy measures occur at several nodes of decision-making, which adversely impact the catchment and the ecosystem services provided by it. Some of the key reasons diagnosed by the immediate analysis include; ad-hoc assignment of property rights, rise in tourist inflow increasing the pressures on water demand, illegal trespassing by local and nomadic pastoral communities for grazing and unlawful extraction of forest products, and rent-seeking by a few influential formal institutions. Consequently, it is indicated that the interplay of formal and informal institutions may be obscuring the consequentiality of the policy measures on the restoration of the catchment.

Keywords: catchment forest restoration, institutional analysis and development framework, institutional interplay, protected forest, water supply management

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Authors: Mark Hocking

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There is concern about the potential impact environmental flooding may have on groundwater levels and salinity processes in the Murray-Darling Basin. A study was undertaken to determine if environmental flooding of the Gunbower Forest has an impact on groundwater level and salinity which is in Victoria, Australia. To assess the impact, Impulse Response Functions (IRFs) are applied to time series groundwater monitoring well data in the area surrounding Gunbower Forest. It is found that rainfall is the primary driver of seasonal water table fluctuation, and the Murray River water level is a secondary contributor to the water table fluctuations. The dominant process that influenced the long-term water table level and salinity conditions is associated with pressure changes in the deep regional aquifer. The study demonstrates that groundwater level fluctuations in the vicinity of Gunbower Forest do not correlate with flooding (natural or managed). Groundwater recharge is calculated by applying the bore hydrograph method to the rainfall-attributed forcing function fluctuations. Data collected from thirty-three bores between 1990 to 2020 is processed to determine a 30-year average groundwater recharge rate. A 5% specific yield of the unconfined aquifer is assumed based on previously published data. It is found that the rainfall-attributed mean annual groundwater recharge varied between 2 mm/year and 189 mm/year with a median of 33.6 mm/year. Surface water recharge is also calculated by analysing the surface water attributed forcing function fluctuations and found to be as high as 37 mm/year, with most of the high values in the vicinity of rivers or agricultural land. There is a long-term regional aquifer declining trend where most water table bores have an average falling trend of 20 cm/year independent of rainfall over the past 30 years. It is found that the groundwater level beneath the Gunbower Forest is dominated by groundwater evapotranspiration. Evapotranspiration lowers the water table by as much as 0.5 m within the forest, thereby causing a relative groundwater level depression under the Gunbower Forest. Historical data shows that groundwater salinity in the area varies and has an electrical conductivity of up to 45 000 µS/cm (comparable to seawater). High groundwater salinity occurs both within and outside the Gunbower Forest as well as adjacent to the Murray River. Available groundwater salinity data suggests trends are generally stable; however, data quality and collection frequency could be improved. This study shows that at the majority of locations analyzed, the groundwater recharge occurred due to both rainfall and water loss from the Murray River. It is found that Deep groundwater pressures determined the base groundwater level, and the fluctuation of the deeper aquifer pressures determined the environmental interaction at the water surface. Local groundwater processes, such as high evapotranspiration rates in Gunbower Forest, have the capacity to lower the water table locally. The rise or fall of the regional aquifer water level has the greatest influence on the groundwater salinity in and around Gunbower Forest.

Keywords: groundwater data interpretation, groundwater monitoring, hydrogeology, impulse response function

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Authors: Khalid Al Mutairi, Mashhor Mansor, Magdy El-Bana, Asyraf Mansor, Saud AL-Rowaily

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Urban expansion and the associated increase in anthropogenic pressures have led to a great loss of the Red Sea’s biodiversity. Floristic composition, diversity, and environmental controls were investigated for 210 relive's on twenty coral islands of Farasan in the Red Sea, Saudi Arabia. Multivariate statistical analyses for classification (Cluster Analysis), ordination (Detrended Correspondence Analysis (DCA), and Redundancy Analysis (RDA) were employed to identify vegetation types and their relevance to the underlying environmental gradients. A total of 191 flowering plants belonging to 53 families and 129 genera were recorded. Geophytes and chamaephytes were the main life forms in the saline habitats, whereas therophytes and hemicryptophytes dominated the sandy formations and coral rocks. The cluster analysis and DCA ordination identified twelve vegetation groups that linked to five main habitats with definite floristic composition and environmental characteristics. The constrained RDA with Monte Carlo permutation tests revealed that elevation and soil salinity were the main environmental factors explaining the vegetation distributions. These results indicate that the flora of the study archipelago represents a phytogeographical linkage between Africa and Saharo-Arabian landscape functional elements. These findings should guide conservation and management efforts to maintain species diversity, which is threatened by anthropogenic activities and invasion by the exotic invasive tree Prosopis juliflora (Sw.) DC.

Keywords: biodiversity, classification, conservation, ordination, Red Sea

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Authors: Meenal Surawar, Rajashree Kotharkar

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Urban Heat Island (UHI) is found more pronounced as a prominent urban environmental concern in developing cities. To study the UHI effect in the Indian context, the Nagpur urban area has been explored in this paper using Landsat 7 ETM+ satellite images through Remote Sensing and GIS techniques. This paper intends to study the effect of LU/LC pattern on daytime Land Surface Temperature (LST) variation, contributing UHI formation within the Nagpur Urban area. Supervised LU/LC area classification was carried to study urban Change detection using ENVI 5. Change detection has been studied by carrying Normalized Difference Vegetation Index (NDVI) to understand the proportion of vegetative cover with respect to built-up ratio. Detection of spectral radiance from the thermal band of satellite images was processed to calibrate LST. Specific representative areas on the basis of urban built-up and vegetation classification were selected for observation of point LST. The entire Nagpur urban area shows that, as building density increases with decrease in vegetation cover, LST increases, thereby causing the UHI effect. UHI intensity has gradually increased by 0.7°C from 2000 to 2006; however, a drastic increase has been observed with difference of 1.8°C during the period 2006 to 2013. Within the Nagpur urban area, the UHI effect was formed due to increase in building density and decrease in vegetative cover.

Keywords: land use/land cover, land surface temperature, remote sensing, urban heat island

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Suraj Jena, Rabindra Kumar Panda

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The study region of the reported study was in Eastern India, having a sub-humid sub-tropical climate and sandy loam soil. The rainfall in this region has wide temporal and spatial variation. Due to lack of adequate surface water to meet the irrigation and household demands, groundwater is being over exploited in that region leading to continuous depletion of groundwater level. Therefore, there is an obvious urgency in reversing the depleting groundwater level through induced recharge, which becomes more critical under the climate change scenarios. The major goal of the reported study was to investigate the effects of climate change on groundwater recharge and subsequent adaptation strategies. Groundwater recharge was modelled using HELP3, a quasi-two-dimensional, deterministic, water-routing model along with global climate models (GCMs) and three global warming scenarios, to examine the changes in groundwater recharge rates for a 2030 climate under a variety of soil and vegetation covers. The relationship between the changing mean annual recharge and mean annual rainfall was evaluated for every combination of soil and vegetation using sensitivity analysis. The relationship was found to be statistically significant (p<0.05) with a coefficient of determination of 0.81. Vegetation dynamics and water-use affected by the increase in potential evapotranspiration for large climate variability scenario led to significant decrease in recharge from 49–658 mm to 18–179 mm respectively. Therefore, appropriate conjunctive use, irrigation schedule and enhanced recharge practices under the climate variability and land use/land cover change scenarios impacting the groundwater recharge needs to be understood properly for groundwater sustainability.

Keywords: Groundwater recharge, climate variability, Land use/cover, GCM

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Authors: Jessica Vasil'chuk, Elena Ivanova, Pavel Krechetov, Vladimir Litvinsky, Nadine Budantseva, Julia Chizhova, Yurij Vasil'chuk

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Carbonate minerals’ isotopic composition is widely used as a proxy for environmental parameters of the past. Pedogenic carbonate coatings on lower surfaces of coarse rock fragments are studied in order to indicate the climatic conditions and predominant vegetation under which they were formed. The purpose of the research is to characterize the isotopic composition of carbonate pedofeatures in soils of Minusink Hollow and estimate its correlation with isotopic composition of soil pore water, precipitation, vegetation and parent material. The samples of pedogenic carbonates, vegetation, carbonate parent material, soil water and precipitation water were analyzed using the Delta-V mass spectrometer with options of a gas bench and element analyser. The soils we studied are mainly Kastanozems that are poorly moisturized, therefore soil pore water was extracted by ethanol. Oxygen and carbon isotopic composition of pedogenic carbonates was analyzed in 3 key sites. Kazanovka Khakass state national reserve, Hankul salt lake, region of Sayanogorsk aluminum smelter. Vegetation photosynthetic pathway in the region is mainly C3. δ18O values of carbonate coatings in soils of Kazanovka vary in a range from −7.49 to −10.5‰ (vs V-PDB), and the smallest value −13.9‰ corresponds the coatings found between two buried soil horizons which 14C dates are 4.6 and 5.2 kyr BP. That may indicate cooler conditions of late Holocene than nowadays. In Sayanogorsk carbonates’ δ18O range is from −8.3 to −11.1‰ and near the Hankul Lake is from −9.0 to −10.2‰ all ranges are quite similar and may indicate coatings’ uniform formation conditions. δ13C values of carbonate coatings in Kazanovka vary from −2.5 to −6.7‰, the highest values correspond to the soils of Askiz and Syglygkug rivers former floodplains. For Sayanogorsk the range is from −4.9 to −6.8‰ and for Hankul from −2.3 to −5.7‰, where the highest value is for the modern salt crust. δ13C values of coatings strongly decrease from inner (older) to outer (younger) layers of coatings, that can indicate differences connected with the diffusion of organic material. Carbonate parent material δ18O value in the region vary from −11.1 to −12.0‰ and δ13C values vary from −4.9 to −5.7‰. Soil pore water δ18O values that determine the oxygen isotope composition of carbonates vary due to the processes of transpiration and mixing in the studied sites in a wide range of −2.0 to −13.5‰ (vs V-SMOW). Precipitation waters show δ18O values from -6.6‰ in May and -19.0‰ in January (snow) due to the temperature difference. The main conclusions are as follows: pedogenic carbonates δ13C values (−7…−2,5‰) show no correlation with modern C3 vegetation δ13C values (−30…−26‰), expected values under such vegetation are (−19…−15‰) but are closer to C4 vegetation. Late Holocene climate for the Minusinsk Hollow according to obtained data on isotope composition of carbonates and soil pore water chemical composition was dryer and cooler than present, that does not contradict with paleocarpology data obtained for the region. The research was supported by Russian Science Foundation (grant №14-27-00083).

Keywords: carbon, oxygen, pedogenic carbonates, South Siberia, stable isotopes

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Authors: Lule Basha, Eralda Gjika

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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

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Authors: H. Tavakoli, S. S. Mohtasebi, R. Alimardani, R. Gebbers

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Nitrogen (N) is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. N demand of crops varies spatially across fields due to spatial differences in soil conditions. In addition, the response of a crop to the fertilizer applications is heavily reliant on plant available water. Matching N supply to water availability is thus essential to achieve an optimal crop response. The objective of this study was to determine effect of drought stress on estimation of nitrogen status of winter wheat by some vegetation indices. During the 2012 growing season, a field experiment was conducted at the Bundessortenamt (German Plant Variety Office) Marquardt experimental station which is located in the village of Marquardt about 5 km northwest of Potsdam, Germany (52°27' N, 12°57' E). The experiment was designed as a randomized split block design with two replications. Treatments consisted of four N fertilization rates (0, 60, 120 and 240 kg N ha-1, in total) and two water regimes (irrigated (Irr) and non-irrigated (NIrr)) in total of 16 plots with dimension of 4.5 × 9.0 m. The indices were calculated using readings of a spectroradiometer made of tec5 components. The main parts were two “Zeiss MMS1 nir enh” diode-array sensors with a nominal rage of 300 to 1150 nm with less than 10 nm resolutions and an effective range of 400 to 1000 nm. The following vegetation indices were calculated: NDVI, GNDVI, SR, MSR, NDRE, RDVI, REIP, SAVI, OSAVI, MSAVI, and PRI. All the experiments were conducted during the growing season in different plant growth stages including: stem elongation (BBCH=32-41), booting stage (BBCH=43), inflorescence emergence, heading (BBCH=56-58), flowering (BBCH=65-69), and development of fruit (BBCH=71). According to the results obtained, among the indices, NDRE and REIP were less affected by drought stress and can provide reliable wheat nitrogen status information, regardless of water status of the plant. They also showed strong relations with nitrogen status of winter wheat.

Keywords: nitrogen status, drought stress, vegetation indices, precision agriculture

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Authors: Abdulkadir I.

Abstract:

Scientists have come to terms with the fact that climate change has been and is expected to cause a significant increase in the severity and frequency of drought events. The northeast region of Nigeria is one of the most, if not the most, affected regions by drought in the country. Therefore, it is on this note that the present study applied ArcGIS and XLSTAT Software and explored drought and its trend in the northeast region of the country using the vegetation health index (VHI), Mann-Kendal, and Sen’s slope between 2001 and 2020. The study also explored the areas that remained under drought and no-drought conditions at intervals of five years for the period under review. The result of Mann-Kendal (-0.07) and Sen’s slope (-0.19) revealed that there was a decreasing trend in VHI over the period under review. The result further showed that the period between 2010 and 2015 had a minimum area of no-drought conditions of about 24%, with Gombe State accounting for the lowest percentage among the six States, about 0.9% of the total area of no-drought conditions. The result further showed the areas that were under drought conditions between 2010 and 2015 represented about 9.1%, with Borno State accounting for the highest percentage among the six States, about 2.5% of the total area under drought conditions. The masked-out areas stood at 66.8%, with Borno State accounting for the highest percentage among the six States, about 20.2% of the total area under drought conditions. Therefore, collective efforts are needed to put in place sustainable land management in the affected areas so as to mitigate the sprawl of desertification in the region.

Keywords: climate change, drought, Mann Kendal, sustainable land management, vegetation health index

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Authors: Margareta Rahayuningsih, Nugroho Edi K., Siti Alimah

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Wreathed Hornbill (Rhyticeros undulatus) is the one of hornbill species (Family: Bucerotidae) that found on Mount Ungaran. In the preservation or planning in situ conservation of Wreathed Hornbill require the habitat condition data. The objective of the research was to determine the land cover change on Mount Ungaran using satellite image data and GIS. Based on the land cover data on 1999-2009 the research showed that the primer forest on Mount Ungaran was decreased almost 50%, while the seconder forest, tea and coffee plantation, and the settlement were increased.

Keywords: GIS, Mount Ungaran, threatened habitat, Wreathed Hornbill (Rhyticeros undulatus)

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Authors: Albert Kwabena Osei Konadu

Abstract:

Pterocarpus erinaceus, also known as Rosewood, is tropical wood, endemic in forest savannah transition zones within the middle and northern portion of Ghana. Its economic viability has made it increasingly popular and in high demand, leading to widespread conservation concerns. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective, sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: convention on international trade in endangered species, cubic volume formula, forest transition savannah zones, pterocarpus erinaceus, smallian’s volume formula, tree information form

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Authors: W. Riahi, M. L. Mansour

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Using tools of data processing such as geographic information system (GIS) for the contribution of the space management becomes more and more frequent. It allows collecting and analyzing diverse natural information relative to the same territory. Space technologies play crucial role in agricultural phenomenon analysis. For this, satellite images treatment were used to classify vegetation density and particularly agricultural areas in Setif province by making recourse to the Normalized Difference Vegetation Index (NDVI). This step was completed by mapping agricultural activities of the province by using ArcGIS.10 software in order to display an overall view and to realize spatial analysis of various themes combined between them which are chosen according to their strategic importance in different thematic maps. The synthesis map elaborately showed that geographic information system can contribute significantly to agricultural management by describing potentialities and development opportunities of production systems and agricultural sectors.

Keywords: GIS, satellite image, agriculture, NDVI, thematic map

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Authors: Meshal M. Abdullah, Rusty A. Feagin, Layla Musawi

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When humans mismanage arid landscapes, soil erosion can become a primary mechanism that leads to desertification. This study focuses on applying soil erosion models to a disturbed landscape in Umm Nigga, Kuwait, and identifying its predicted change under restoration plans, The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the Demilitarized Zone (DMZ) adjacent to Iraq, and has been fenced off to restrict public access since 1994. The central objective of this project was to utilize GIS and remote sensing to compare the MPSIAC (Modified Pacific South West Inter Agency Committee), EMP (Erosion Potential Method), and USLE (Universal Soil Loss Equation) soil erosion models and determine their applicability for arid regions such as Kuwait. Spatial analysis was used to develop the necessary datasets for factors such as soil characteristics, vegetation cover, runoff, climate, and topography. Results showed that the MPSIAC and EMP models produced a similar spatial distribution of erosion, though the MPSIAC had more variability. For the MPSIAC model, approximately 45% of the land surface ranged from moderate to high soil loss, while 35% ranged from moderate to high for the EMP model. The USLE model had contrasting results and a different spatial distribution of the soil loss, with 25% of area ranging from moderate to high erosion, and 75% ranging from low to very low. We concluded that MPSIAC and EMP were the most suitable models for arid regions in general, with the MPSIAC model best. We then applied the MPSIAC model to identify the amount of soil loss between coastal and desert areas, and fenced and unfenced sites. In the desert area, soil loss was different between fenced and unfenced sites. In these desert fenced sites, 88% of the surface was covered with vegetation and soil loss was very low, while at the desert unfenced sites it was 3% and correspondingly higher. In the coastal areas, the amount of soil loss was nearly similar between fenced and unfenced sites. These results implied that vegetation cover played an important role in reducing soil erosion, and that fencing is much more important in the desert ecosystems to protect against overgrazing. When applying the MPSIAC model predictively, we found that vegetation cover could be increased from 3% to 37% in unfenced areas, and soil erosion could then decrease by 39%. We conclude that the MPSIAC model is best to predict soil erosion for arid regions such as Kuwait.

Keywords: soil erosion, GIS, modified pacific South west inter agency committee model (MPSIAC), erosion potential method (EMP), Universal soil loss equation (USLE)

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Authors: L. Benseghir, H. Kadi-Hanifi

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Vegetation of the high steppic plains of southern Algiers region has ever been used by human occupation. The harsh climatic context characterized by long periods of drought and an ovine livestock in constant growth lead us to devote a particular attention to the biodiversity of those living environment. The diachronic study made in Tadmit (50 km south of the district of Djelfa) about the specific recording led us to notice that: The floristic recording of Tadmit is not reduced in time but fluctuate, depending on the pasture intensity, the annual rainfall and especially by the protection area of the following two years from January 2004. The forming specific recording of the station undergo significant changes from a period to another. Those changes in floristic list concern nearly 50% of the initial flora that could disappear or be replaced by new species. Finally, the alfa steppe is in a marked decline and is substituted by new facies that were privileged by the overgrazing, stranding or clearance.

Keywords: overgrazing, diachronic study, protection area, climate, desertification

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Mohammed Abaoli, Omer Kara

Abstract:

The current research has investigated the soil quality status under dryland vegetation of Yabello district, Southern Ethiopia in which we should identify the nature and extent of salinity problem of the area for further research bases. About 48 soil samples were taken from 0-30, 31-60, 61-90 and 91-120 cm soil depths by opening 12 representative soil profile pits at 1.5 m depth. Soil color, texture, bulk density, Soil Organic Carbon (SOC), Cation Exchange Capacity (CEC), Na, K, Mg, Ca, CaCO₃, gypsum (CaSO₄), pH, Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP) were analyzed. The dominant soil texture was silty-clay-loam.  Bulk density varied from 1.1 to 1.31 g/cm³. High SOC content was observed in 0-30 cm. The soil pH ranged from 7.1 to 8.6. The electrical conductivity shows indirect relationship with soil depth while CaCO₃ and CaSO₄ concentrations were observed in a direct relationship with depth. About 41% are non-saline, 38.31% saline, 15.23% saline-sodic and 5.46% sodic soils. Na concentration in saline soils was greater than Ca and Mg in all the soil depths. Ca and Mg contents were higher above 60 cm soil depth in non-saline soils. The concentrations of SO₂^-4 and HCO^-3 were observed to be higher at the most lower depth than upper. SAR value tends to be higher at lower depths in saline and saline-sodic soils, but decreases at lower depth of the non-saline soils. The distribution of ESP above 60 cm depth was in an increasing order in saline and saline-sodic soils. The result of the research has shown the direction to which extent of salinity we should consider for the Commiphora plant species we want to grow on the area. 

Keywords: commiphora species, dryland vegetation, ecological significance, soil quality, salinity problem

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Authors: Bharatendra Rai

Abstract:

Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

Procedia PDF Downloads 325

Authors: A B M Enamol Hassan

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The forest storing up in Bangladesh is of deep concern to policy analysts because of increasing encroachment that results in deforestation and degradation of the ecosystem. To address these problems, forest-dependent people, as responsible for encroachment, could be involved in the co-management process along with other local stakeholders through a participatory approach. On the basis of this premise, this paper conceptualizes and empirically assesses the integration of all stakeholders in the co-management process through two lenses such as participation and collaboration. The study also analyzed the issues of sustainability in local communities along with examining constraints that limit the processes of integration. The study used a qualitative research method, which included face-to-face interviews with semi-structured questionnaires and field notes following the purposive sampling technique focusing on Comilla Sadar South Upazila (CSSU), Bangladesh. The findings of this paper reveal beneficiaries, Bangladesh Forest Department (BFD) and Union Parishad (UP), come together as leading actors, while NGOs and business entrepreneurs are ignored in the co-management process of social forestry. However, integrated management contributes to the strength of community sustainability, although it has some major limitations causing the matter of concerns among the local communities and policy analysts.

Keywords: integration, participation, collaboration, stakeholders, community sustainability

Procedia PDF Downloads 151