Cultivated Area Research Articles

Gender Stereotype in Tess of The D’urbervilles by Thomas Hardy and The Great Gatsby by F. Scott Fitzgerald

This study focused on gender stereotypes in Thomas Hardy’s Tess of the D’Urbervilles (1891) and F. Scott Fitzgerald’s The Great Gatsby (1925). The objectives of the study were to: examine the portrayal of masculinity-femininity stereotype; examine the language used in gender stereotype and analyse the impact of traditional gender stereotype on the female characters. The study used the feminist theory to examine gender stereotype in the two male–authored novels to show how they have positioned and portrayed women in their literature in the Victorian period both in England and America The literary analysis was to ascertain whether or not the gender stereotype was a global notion in literature or a misrepresentation of the women not as persons but as sexualized figures. Gender stereotype in these novels was examined using the descriptive research design and data was collected using literary analysis. The findings indicated that both novels portrayed the female gender with discrimination, injustice, dishonesty and exploitatively. This was done with the use of symbolism, imagery, similes and metaphor. The conclusion drawn points to the fact that the quest for a masculine identity is a common theme as male characters are seen struggling to become real men with traits such as: power, strength and robustness whereas female characters were portrayed as sexualized figure used for social status in the male dominated societies. With regard to language stereotype, the male characters employed language to paint negative image in line with the accepted image in the male dominated society. The researchers recommend that detailed and comprehensive studies be conducted in the area of gender and culture and gender and literature in the novel as a genre generally

Intensifying droughts render more Sahel drylands unsuitable for cultivation

Two-fifth of the world's population will be confronted by dire land and water shortage for food production by 2050. Here we provide nuanced insights into the Sahel dryland dynamics and rationale behind its underperforming croplands amid climate extremes. We develop a gridded multi-criteria drought index for the growing season (June-October) and analyse its spatial and temporal degree of uniformity to designate the drought, climate and cultivable zones. Evidence is drawn from Sahelian Sudan, representing 1.03 million km2 of the African Sahel, during 1940–2020. Results show that cultivation of marginal lands has persisted apace. The peak areas of these marginal lands explain ∼50 % of the variations in crop yield, considering the two staple crops, sorghum and millet. Furthermore, the low yields mismatch the steadily growing planted areas of these crops. Compared to wet conditions, droughts expand (shrink) the median size of hyper-arid (arid) area by 466 % (46 %), limiting farming opportunities for 3.5–35.8 % of the croplands. The northernmost borderline of the arid zone determines the rainfed suitability, but potentially cultivable arid areas require contingency risk-reduction plans. Conversely, semi-arid and dry sub-humid zones reveal areas endowed with uniform climate. Skillful climate forecasting should thus guide policymaking towards sustainable agriculture therein. The paper suggests paths towards more effective agricultural policy interventions. Agricultural production entails the Sahel drought being defined in terms of agricultural impacts instead of meteorological conditions. Land use planners and inhabitants must relieve the plight of misconceiving and overlooking the fact of intrinsic interannual rainfall variability. Determining what a dangerous drought is for the Sahel agriculture sector or system is crucial. Sahel farming systems should opt for highly flexible agricultural practices based on the above-identified cultivable areas.

Exploring Iranian ESP teachers’ emotion labor: a critical perspective

Despite the growth of research on English for specific purposes (ESP) teachers over the past two decades, the scope of research that focally examines ESP teachers’ emotions is limited. The present study explored 10 Iranian ESP teachers’ emotion labor. Collecting data from questionnaires, narrative frames, and semi-structured interviews, we show how contextual discourses, policies, and expectations of ESP instruction interact with the teacher participants across four areas of pedagogy, assessment, materials, and curriculum and culture. Our findings indicated that content featured as a significant factor in the teachers’ emotions, agency, and identity directly, indirectly, and specifically through content-related discourses and participants. More specifically, it is not necessarily the content itself that along with language shape ESP teachers’ professional sense-making; rather, the way content manifolds in institutional work and interacts with language through various contextualities, modalities, and participants functions more profoundly in ESP teachers’ work. We provide implications for ESP teachers to draw on their collegial potentials to form communities of practice that positively contribute to their professional growth and transform their negative emotions into mutual emotionality.

Spectral indices with different spatial resolutions in recognizing soybean phenology.

The aim of the present research was to evaluate the efficiency of different vegetation indices (VI) obtained from satellites with varying spatial resolutions in discriminating the phenological stages of soybean crops. The experiment was carried out in a soybean cultivation area irrigated by central pivot, in Balsas, MA, Brazil, where weekly assessments of phenology and leaf area index were carried out. Throughout the crop cycle, spectral data from the study area were collected from sensors, onboard the Sentinel-2 and Amazônia-1 satellites. The images obtained were processed to obtain the VI based on NIR (NDVI, NDWI and SAVI) and RGB (VARI, IV GREEN and GLI), for the different phenological stages of the crop. The efficiency in identifying phenological stages by VI was determined through discriminant analysis and the Algorithm Neural Network-ANN, where the best classifications presented an Apparent Error Rate (APER) equal to zero. The APER for the discriminant analysis varied between 53.4% and 70.4% while, for the ANN, it was between 47.4% and 73.9%, making it not possible to identify which of the two analysis techniques is more appropriate. The study results demonstrated that the difference in sensors spatial resolution is not a determining factor in the correct identification of soybean phenological stages. Although no VI, obtained from the Amazônia-1 and Sentinel-2 sensor systems, was 100% effective in identifying all phenological stages, specific indices can be used to identify some key phenological stages of soybean crops, such as: flowering (R1 and R2); pod development (R4); grain development (R5.1); and plant physiological maturity (R8). Therefore, VI obtained from orbital sensors are effective in identifying soybean phenological stages quickly and cheaply.

Nutrient Distribution Patterns in Soil Across Various Locations in Muzaffarnagar and Ghaziabad Districts of Uttar Pradesh under a Rice-Sugarcane Cropping Sequence

A study was conducted to evaluate the macro and micronutrient levels in the soil under the sugarcane-wheat cropping sequence and its relationship with soil characteristics. Understanding the nutrient status is vital for the efficient application of fertilizers, as widespread deficiencies in both macro and micronutrients are being reported in the soils of Uttar Pradesh. The rice-sugarcane cropping sequence is a prominent practice in the northwestern plains of Uttar Pradesh and Uttarakhand, covering 10-11% of the net cultivated area in these regions. Over recent years, sugarcane and wheat yields have plateaued in these areas due to declining factor productivity. Soil samples were collected from depths of 0-15 cm, 15-30 cm, and 30-45 cm at four locations in the Muzaffarnagar and Ghaziabad districts under the rice-sugarcane sequence. The available zinc content in the surface soil (0-15 cm) ranged from 0.605 to 0.883 mg/kg, and in the sub-surface soil (30-45 cm), it varied between 0.111 to 0.629 mg/kg, with an average of 0.083 mg/kg in surface soil and 0.435 mg/kg in sub-surface soil. A correlation analysis between various soil properties across different locations at three soil depths (0-15 cm, 15-30 cm, and 30-45 cm) was also conducted. The findings indicated that the soils are generally low in nitrogen, low to medium in phosphorus and potassium, and sufficiently supplied with copper, iron, manganese, and zinc in the surface layer. Future research on nutrient distribution in these areas will help advance precision agriculture, improve fertilizer management, and boost crop productivity while minimizing environmental harm. This research will contribute to sustainable soil management, economic benefits for farmers, and provide valuable insights for regional agricultural policies, further supporting food security.

Using Pseudo-Color Maps and Machine Learning Methods to Estimate Long-Term Salinity of Soils

Soil salinity assessment methods based on remote sensing data are a common topic of scientific research. However, the developed methods, as a rule, estimate relatively small areas of the land surface at certain moments of the season, tied to the timing of ground surveys. Considerable variability of weather conditions and the state of the earth surface makes it difficult to assess the salinity level with the help of remote sensing data and to verify it within a year. At the same time, the assessment of salinity on the basis of multiyear data allows reducing the level of seasonal fluctuations to a considerable extent and revealing the statistically stable characteristics of cultivated areas of land surface. Such an approach allows, in our opinion, the processes of mapping the salinity of large areas of cultivated lands to be automated considerably. The authors propose an approach to assess the salinization of cultivated and non-cultivated soils of arid zones on the basis of long-term averaged values of vegetation indices and salinity indices. This approach allows revealing the consistent relationships between the characteristics of spectral indices and salinization parameters. Based on this approach, this paper presents a mapping method including the use of multiyear data and machine learning algorithms to classify soil salinity levels in one of the regions of South Kazakhstan. Verification of the method was carried out by comparing the obtained salinity assessment with the expert data and the results of laboratory tests of soil samples. The percentage of “gross” errors of the method, in other words, errors when the predicted salinity class differs by more than one position compared to the actual one, is 22–28% (accuracy is 0.78–0.72). The obtained results allow recommending the developed method for the assessment of long-term trends of secondary salinization of irrigated arable land in arid areas.

Classification of Agricultural Crops with Random Forest and Support Vector Machine Algorithms Using Sentinel-2 and Landsat-8 Images

Monitoring crop development and mapping cultivated areas are important for reducing risks to food security due to climate change. Remote sensing techniques contribute significantly to the efficient and effective management of agricultural production. In this study, agricultural fields (sunflower, wheat, maize, oat, chickpea, sugar beet, alfalfa, onion, fallow) and other fields (non-agricultural, pasture, lake) were identified by using Random Forest (RF) and Support Vector Machines (SVM) machine learning algorithms with Sentinel-2 and Landsat-8 images in the area covering Polatlı, Haymana and Gölbaşı districts of Ankara province Multi-temporal images were used to distinguish winter and summer crops, taking into account crop development periods. As a result of classification; the overall accuracy of RF and SVM models with S2 images are 89.5% and 84.6% and kappa coefficients are 0.88 and 0.83, while the overall accuracy of RF and SVM models with L8 images are 79% and 78.1% and kappa coefficients are 0.76 and 0.75. RF model was found to have higher prediction accuracy than SVM. Sentinel-2 imagery has a higher accuracy in all classes compared to Landsat-8, indicating that Sentinel-2 imagery with its high temporal and spatial resolution is more suitable and has a great potential for agricultural crop pattern detection.

Green architecture in tourism sustainable development a case study at Laweyan, Indonesia

ABSTRACT The degradation of local culture is often a consequence of tourist kampung development. However, Laweyan stands out as an example where a tourist village was developed while successfully preserving both the environment and local culture. The research aims to formulate a strategy that promotes a green environment by exploring the potential characteristics of local cultural heritage and emphasizing sustainable preservation. By utilizing an exploratory descriptive method and analyzing the potential and characteristics of the area, the study identified several strategies for developing cultural heritage areas in tourism kampung. These strategies include promoting green communities, establishing green open spaces and infrastructure, implementing green waste management, adopting green transportation, prioritizing green water practices, incorporating green building techniques, and utilizing green energy sources. The implementation of green architecture is one of the key factors for success in sustainable village development. The concept of green architecture involves integrating building design and the environment with the aim of maintaining a balance between quality development and environmental preservation. The successful implementation of these strategies relies on a collaborative social approach that raises awareness and encourages active participation from both the community and the government in preserving the authenticity of the local culture.

The Role of Creative Communities in Supporting Development of Urban Heritage Tourism Kota Tua Jakarta

Kota Tua Jakarta or Jakarta’s Old City is a Cultural Heritage Area as well as a National Vital Object. This area is managed by the DKI Jakarta Provincial Government as a historical tourist destination. The increase in tourist visits to this area is caused by various things, one of which is the existence of tourist attractions developed by the local creative community. The role of the creative community has not been identified thoroughly. This study aims to explain the role of the creative community as a supporting tourist attraction in Kota Tua area. In addition, identifying this role is also important to help the government plan regulations that have an impact on optimizing tourism potential. This study was conducted using a qualitative method with descriptive data presentation. The results of the study show that the creative community also plays a role in developing tourism in Kota Tua ​​Jakarta. The role of the creative community is not only in providing new experiences, but also in being able to enliven the attractive atmosphere in the area of ​​cultural heritage sites that have developed into tourist destinations. The creative community has also become a tourism identity in the Kota Tua ​​Jakarta, apart from the physical side of the interesting colonial-style building architecture.

Integrating S1A microwave remote sensing and DSSAT CROPGRO simulation model for groundnut area and yield estimation

This study sought to corroborate microwave remote sensing and simulation models to efficiently delineate groundnut cultivation area and to estimate the yield by integration. Near real-time information on crop acreage and yield estimation is essential for making policy decisions. S1A SAR data were downloaded for entire crop growth period of groundnut during Kharif monsoon seasons (June – October) of 2019 and 2020 and were processed using MAPSCAPE RIICE software to extract groundnut cultivated area in the study districts of Tamil Nadu. Spectral dB curve groundnut generated using multi-date Sentinel 1 A SAR data showed a minimum at sowing, reached a peak at the pod development stage and decreased after that towards maturity. Groundnut area map was generated with a classification accuracy of 85.2 and 84.8 per cent with a kappa coefficient of 0.70, and total groundnut area of 104343 and 116199 ha was mapped during Kharif monsoon season 2019 and 2020, respectively. The mean agreement of 75.01 and 84.94 per cent was observed between DSSAT model simulated LAI and observed LAI at thirty monitoring locations in the study area during Kharif monsoon season 2019 and 2020, respectively, whereas agreement for yield was 82.11 and 83.70 per cent with RMSE of less than 20 per cent. Spatial distribution of groundnut LAI and yield was estimated by assimilating dB from satellite image and from DSSAT model, respectively. The estimated mean spatial LAI was 2.81 and 3.52, whereas mean spatial pod yield was 2124 and 2195 Kg ha−1 during Kharif monsoon season 2019 and 2020, respectively with RMSE of less than 20 per cent and R2 for integrating satellite products and simulation model for spatial estimates during both the year was >0.70, it shows the fitness of products towards increased accuracy of estimation.

Jesuits, Jansenists, and the Culture Wars

Abstract This introductory article explores the relevance of studying the Jesuit-Jansenist conflict in early modern France against the broader background of modernity as such and its inherent problems with fragmentation, isolation, and polarization in all areas of culture. It begins with a reference to the particular use of the study of early modernity and its religious and sociopolitical problems by the two prominent dissidents of the twentieth century, Leszek Kołakowski (1927–2009) and Jan Patočka (1907–77), in order to draw some potential parallels between the contemporary “culture wars” and the conflict between the Jesuits and the Jansenists. The contributions, stemming from a conference held at Adam Mickiewicz University in Poznań in March 2023, celebrating the four-hundredth anniversary of the birth of Blaise Pascal, shed light on various aspects of classical culture, education, tradition, and innovation in the areas of theatre, music, and philosophy in seventeenth-century France.

Organic Farming for Sustainable Agriculture: Future Outlook and Options

Organic products are grown under a system of agriculture without using chemical fertilizers and pesticides, with an environmentally and socially responsible approach, and provide healthy food. It is developing rapidly and is practised in more than 120 countries. In 2022-23, the total area under the organic certification process (registered under the National Programme for Organic Production) is 10.17 million ha. This includes 5.39 million ha of cultivable area and another 4.8 million hectares for wild harvest collection. Madhya Pradesh has covered the most significant area under organic certification. In contrast, India produced around 2.9 million MT of certified organic products, which include all varieties of food products, namely Oil Seeds, fibre, Sugar cane, Cereals and millets, Cotton, Pulses, Aromatic and Medicinal Plants, Tea, Coffee, Fruits, Spices, Dry Fruits, Vegetables, Processed foods etc. The production is not limited to the edible sector; it produces organic cotton fiber, functional food products, etc. Among different states, Madhya Pradesh is the largest producer. In terms of exports, the total value was 0.31 million Mt. The organic food export realisation was around Rs. 5525.18 Crore (708.33 million USD). Products are exported to the USA, European Union, Canada, Great Britain, Switzerland, Turkey, Australia, Ecuador, the Korean Republic, Vietnam, Japan, etc. The objectives of organic farming ensure that food production has high nutritional value in adequate quantities and preserves and enhances the long-term fertility of soils.

Preliminary Study on the Relationship between Location, Infrastructure, and Transportation of Productive Malaysia Cocoa Farmers (PMCF) towards Work Performances in Sarawak, Malaysia

Malaysian cocoa production relied on cocoa farmers since 2006 because they were the major holder (81.4%) of the cocoa cultivation area. As for Sarawak, 100% of cocoa production was from cocoa farmers. Sarawak used to produce 21,200 metric tons of dried cocoa beans in 1990. The government also has spent more on training and fertilizer for cocoa farmers to increase PMCF productivity. However, the production keeps gradually decreasing yearly. In 2021, Sarawak only produced 59 metric tons of dried cocoa beans and the productivity decreased by 10% to 0.19 metric/ton/ha/year compared to 2019 productivity (MCB, 2022). In order to strategies the long-term improvement of cocoa production, this study aims to define the relationship between location, infrastructure, and transportation toward the work performance of Sarawak PMCF. Driven by Iceberg Model, the objectives of this preliminary study are to determine i) the location, infrastructure, and transportation towards work performance levels ii) the relationship between location, infrastructure, and transportation with work performance iii) the most factors (IVs) that contribute more toward work performances. A total number of 35 respondents were involved in this purposive data collection which is only 30% of the sample population of the preliminary study which was 105 PMCF. The sample procedure used the approach of random sampling technique. These 35 respondents were selected involving 3.6% of respondents for each zone population of Sarawak rural areas namely the Northern, Middle, and Southern Coastal Zone. The data was r by IBM SPSS version 25.0. The data were tested by using Exploratory Factor Analysis (EFA) and then analyzed by descriptive, correlation, and regression analysis to answer all objectives. The study found all the variables showed moderate-level indicators. The variables that showed moderate and positive correlation were location and infrastructure. In contrast, location is the most contributing factor to the work performance of PMCF in Sarawak.

Assessing the Impacts of Climate Change on Geographical Distribution of Tea (Camellia sinensis L.) in Kenya with Maximum Entropy Model

Climate change has been disturbing the present species distribution ranges, resulting in the shifting of cultivation areas and decreases in production and quality. Tea (Camellia sinensis L.), which seeks optimum climatic resources, is a key cash crop economically in Kenya. In this study, the shifting of tea suitability was projected with the MaxEnt model under the SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) climate scenarios for the 2050s and 2090s relative to the 1970–2000 distribution. Analysis under the current climatic condition showed that the proportions of optimal and medium- and marginal-suitable areas were 2%, 3%, and 24% of the total area, respectively, and located in south-western (SW), central, and north-eastern (NE) Kenya and, to some extent, in the Rift Valley. It was projected that the potential suitable tea-growing areas would migrate from the western areas to the central, eastern, and north-eastern highlands in Kenya. It was detected that the precipitation of the driest period (July), precipitation of the wettest quarter (April, May, and June), and annual temperature range could be the main climatic factors determining the shift in tea distribution. Compared to the current distribution (29%), the climatically suitable areas for tea production could reach 32.58% of Kenya’s land area under the SSP1-2.6 scenarios in the 2050s and 35.08% in the 2090s under the SSP5-8.5 scenario. On the contrary, it was found that the optimal climate-suitable habitats were projected to shrink by 2% and 1% in the 2050s and 2090s under all scenarios on the west side of the Great Rift Valley compared to the current distribution. In comparison, the sizes of medium- and marginal-suitable habitats would increase by 1% and 3%, respectively. The findings indicated that unless adaptive climate actions are taken, climate change could reduce the tea planting areas in western Kenya. Meanwhile, climate suitability was projected to expand upward on the east side of the Rift Valley, enhancing the potential distribution of tea. The developed climate information could be used to design and implement adaptation interventions in the lower elevation areas. Finally, we highlight that the available scientific literature on the climate suitability of tea in Kenya should be broadened by adding non-climatic factors.

Take a handful of nuts in a bowl! Turned wooden vessel with hazelnuts from Czarnówko against the background of other finds from cemeteries of the Wielbark culture

Abstract In 2009, during research of a cemetery of the Wielbark culture in Czarnówko (Lębork District, Pomerania), an inhumation grave was discovered, which contained the remains of a wooden bowl with copper alloy fittings. Inside it, several hazelnuts were preserved. This vessel, in the light of the analysis carried out, was made of alder wood using a turning technique. Discoveries of this type are not only rare in the area of the Wielbark culture, but also in the rest of Central European Barbaricum. This article presents the results of the archaeobotanical research and demonstrates the bowl in the broader context of Roman Period discoveries.

Alterations in Suitable Cultivation Area for Scutellaria baicalensis under Future Climatic Scenarios in China: Geodetector-Based Prediction

The dried roots of Scutellaria baicalensis (S. baicalensis) have been widely used as a traditional medicine. Recently, climate change and human activities have caused the degeneration of its wildlife habitat. However, there is rare knowledge on the effect and interactive effect of different variables on the spatial heterogeneity of S. baicalensis and how the pattern of suitable cultivation area in China would shift in response to climate change. Based on the Geodetector and Habitat Suitability Index (HSI) method, we proposed an assessment model to identify the critical environmental variable(s) affecting the distribution of suitable cultivation area for S. baicalensis in China and to project its shift under climate change. The results showed that soil and mean annual temperature are two determining variables in its spatial heterogeneity in China. Compared to 1981–2010, future climate change may result in a decrease in its suitable area, and yet may result in an increase in the extremely suitable area (about 1.00–1.35 million km2). S. baicalensis in the southern and northwestern part of its current distribution and the southwestern part and small area of northern China may experience expansion during the 21st century, while S. baicalensis in southern China, the Huang-Huai-Hai plain, and the midwest of northwestern China may experience contractions. Meanwhile, climate warming is expected to shift its distribution northwest through an expansion at the northern (at least 84 km) and western (at least 62 km) boundary and contraction at the southern (at least 529 km) boundary, respectively. These results could provide valuable information to policy-makers for the conservation and scientific introduction of S. baicalensis.

Application of fallout radionuclide—137Cs for estimating soil erosion in steep hillslopes with diverse land use of North-western Indian Himalayas

Hilly and mountainous regions are significantly impacted by soil erosion, primarily due to rainfall-runoff processes occurring on the hillslope scale. Assessing soil erosion is crucial for quantifying the loss of soil carbon and nutrients, which diminishes the potential of soil ecosystem services and is critical for mitigating the impacts of climate change on food security. However, the Himalayan landscape poses serious challenges for assessing soil erosion due to its steep and rugged terrain, which hinders the use of conventional and modelling methods. The fallout radionuclide—137Cs has been extensively utilized as an environmental marker for investigating soil redistribution processes. Despite its potential, there is a notable lack of 137Cs-based soil erosion studies in the Himalayan region. In this context, we assessed the applicability of the fallout radionuclide—137Cs method in quantifying soil erosion rates and identifying erosion hotspots on two hillslopes of the Higher Himalayas. On the hillslope scale, we observed that soil erosion rates vary based on slope gradient and land use/land cover. Forested areas exhibited the lowest soil erosion rates compared to cultivated areas, while flat hillslope positions experienced lower erosion rates than steeper positions. The average net erosion rate for the Harsil hillslope varied among different hillslope positions, ranging from – 2.9 to – 15.6 t ha−1 yr−1. Similarly, in the Gangnani hillslope, the net erosion rates varied across different positions, ranging from – 5.6 to – 39 t ha−1 yr−1. Our findings confirm that the middle and lower hillslope positions are the most critical source areas with higher soil erosion rates, while hillslope positions with forest cover demonstrate the lowest erosion rates, identified as helpful in controlling soil erosion. The study has demonstrated the applicability of FRN as a soil erosion measurement method in the complex, rugged, and steep terrain of the Himalayas, highlighting the need for targeted conservation efforts to mitigate soil erosion and preserve ecosystem integrity.

Assessment of Soil Physico-chemical Properties in Sugarcane Cultivation Areas of Navsari District, Gujarat, India

Sentinel 2 satellite data from the year 2021 were acquired from the Copernicus site to identify the sugarcane producing area in the Navsari district. Hybrid classification approach i.e., supervised and unsupervised with ground truth data were applied using ERDAS IMAGINE software. After image classification, 2.5 km x 2.5 km grid was prepared in Q-GIS software which along with classified sugarcane area were overlapped for site identification. Then, random soil surface and sub-surface samples were collected with reference from grid of intensive sugarcane growing area. The particle density (2.10 to 2.76 g cm-3 with the mean value of 2.58 g cm-3) and bulk density (1.10 to 1.68 g cm-3 with the mean value of 1.33 g cm-3) of surface soil were found to be lower than sub-surface soil (2.18 to 2.79 g cm-3 and 1.15 to 1.68 g cm-3 with the mean value of 2.62 g cm-3 and 1.42 g cm-3 respectively) while porosity (31.60 to 59.26% with the mean value of 48.39%) and maximum water holding capacity (22.77 to 51.92% with the mean value of 39.60%) of surface soil were found to be higher than sub-surface soil (29.54 to 57.71% and 20.98 to 48.91% with the mean value of 45.60% and 36.81% respectively). The pH of soil surface showed range from 6.08 to 8.37 while pH of soil sub-surface noted range of 6.00 to 8.50. The electrical conductivity of surface and sub-surface soil showed the range of 0.011 to 1.580 dS m-1 and 0.010 to 1.586 dS m-1. The soil organic carbon of surface soil ranged from 0.06 to 0.89% while that of sub-surface soil varied from 0.02 to 0.85%.

The Influence of Cultural Heritage Status on the Quality of Life of Slum Settlement Community

Surabaya is a fast-growing city facing challenges in infrastructure development, posing a threat to cultural heritage and historic areas. The Kalimas area has been abandoned, negatively impacting the environment. Cultural heritage is valuable as it instills pride, holds significance in civilization, and can improve the quality of life (QOL). The World Health Organization (WHO) defines the quality of life as an individual's perception of differences in life based on culture and the surrounding environment. This study aims to determine the impact of physical conditions in slum settlements on the QOL of the community and identify the slum settlement variables that can improve residents' QOL. The study uses a quantitative approach with analytical techniques such as literature review and multiple linear regression to analyze land characteristics, socio-economic factors, and physical characteristics. QOL is measured using the WHOQOL questionnaire. The data collection methods include secondary data from the Department of Housing, Settlement Areas and Land, and Bappedalitbang of Surabaya City, as well as primary data from observations, questionnaires, and interviews with the research sample. The results indicate that slum settlement variables significantly affect four domains of QOL: physical health, psychology, environment, and social relationships. However, physical characteristics partially do not affect the psychological, environmental, and social relationship domains.

Contemporary Demands of Scenes in Urban Historic Conservation Areas: A Case Study of Subjective Evaluations from Foshan, China

A historic area situated within contemporary urban space must adapt to modern lifestyles and aesthetic sensibilities to sustain its vitality and facilitate effective heritage transmission. A key criterion for evaluating adaptation is its ability to fulfill people’s ‘demands’ for it. This paper focuses on people’s demands as its core, employing the post-occupancy evaluation theory and the scene theory to develop a subjective evaluation framework for scenes within urban historic conservation areas. An application case study uses the typical historical area of Foshan, China, as an evaluation framework. The discussion encompasses spatial vitality, extraction of scene elements, construction of an indicator set, satisfaction evaluation, and differences in evaluations across areas and individual indicators. The research findings reveal several key points: (1) People’s attention and demands regarding scene elements in urban historic conservation areas are multifaceted. (2) There is a high degree of tolerance among people towards urban historic conservation areas, with varying preferences for different areas. (3) The approach to area protection and development needs diversification. (4) People’s overall perception of an area is influenced by various elements within the scenes. The application of this evaluation framework can aid in understanding people’s “demands” and their underlying reasons while also providing assistance for future optimization efforts related to urban historic conservation areas. Furthermore, the subjective evaluation framework has potential applicability for research into other historical cultural street areas.