National Parks, coffee and NTFPs: the livelihood capabilities of Adivasis in Kodagu, India

Protected Areas, as a conservation strategy, often constrain livelihood outcomes of groups that are less powerful, politically marginalized, and poor. At the same time, the poor often depend on a market economy that is volatile. Working on coffee plantations  and the collection of non-timber forest products (NTFPs) are the two major livelihood options available for the Adivasi indigenous community in Kodagu, India. The article identifies the institutional factors at global, regional, or local levels that influence the livelihood capabilities of Adivasis. While the creation of a National Park negatively influenced almost all aspects of the Adivasis' livelihood, labor demand on coffee farms, and NTFP collection rights outside the Park provided them with some alternative resources.  But deregulation of the Indian coffee market made them more vulnerable to the market economy. The social relations between Adivasis and nearby farming communities have helped them to cope with risks to their livelihoods during crises and emergencies. Key words: Livelihoods, Coffee, NTFP, Adivasis, LAMPS, Kodag

Remote sensing of land cover’s effect on surface temperatures : a case study of the urban heat island in Bangalore, India

Urbanization has substantially altered the earth’s surface, and cities’ impervious surfaces for anthropogenic activities often generate an urban heat island (UHI). This paper analyses the effects of the UHI in Bangalore, which in recent years has witnessed tremendous in-migration of people and expansion of infrastructure due to rapid growth of its information technology, biotechnology and manufacturing sectors. Temperature values extracted from the Landsat satellite’s Enhanced Thematic Mapper Plus (ETM+) thermal bands and a “Normalized Difference Vegetation Index” (NDVI) were used to ascertain the relationship between vegetation cover and temperature. Results indicate that the city core has a significantly lower mean temperature than the city’s outgrowth zones. The presence of water bodies and vegetation in the city’s core helped to maintain lower temperatures than those found in the city’s outskirts, even though within the city core temperatures varied from 1 to 7° C within different land cover classes. The continued expansion of urban infrastructure and new, residential neighborhoods which lack vegetation seem to be contributing substantially to higher temperatures in the outgrowth zones

Remote sensing of land cover’s effect on surface temperatures : a case study of the urban heat island in Bangalore, India

Urbanization has substantially altered the earth’s surface, and cities’ impervious surfaces for anthropogenic activities often generate an urban heat island (UHI). This paper analyses the effects of the UHI in Bangalore, which in recent years has witnessed tremendous in-migration of people and expansion of infrastructure due to rapid growth of its information technology, biotechnology and manufacturing sectors. Temperature values extracted from the Landsat satellite’s Enhanced Thematic Mapper Plus (ETM+) thermal bands and a “Normalized Difference Vegetation Index” (NDVI) were used to ascertain the relationship between vegetation cover and temperature. Results indicate that the city core has a significantly lower mean temperature than the city’s outgrowth zones. The presence of water bodies and vegetation in the city’s core helped to maintain lower temperatures than those found in the city’s outskirts, even though within the city core temperatures varied from 1 to 7° C within different land cover classes. The continued expansion of urban infrastructure and new, residential neighborhoods which lack vegetation seem to be contributing substantially to higher temperatures in the outgrowth zones

Inventory of Western United States Glaciers- 2020

The dataset employed for delineating glacier boundaries in the Western United States comprises a compilation of original Sentinel-2 images obtained from the European Space Agency\u27s Copernicus website. These images were instrumental in generating the glacier inventory. Additionally, the dataset includes a Python and R script specifically crafted for processing and classifying Sentinel images. The outcome of this process is represented in an ESRI shapefile, which contains an inventory of glaciers extracted from Sentinel images

Trend Analysis and Simulation of Human Vulnerability Based on Physical Factors of Riverbank Erosion Using RS and GIS

This study aims to analyze the pattern of bank erosion and simulate the physical aspects of vulnerability in the lower Meghna River, Bangladesh using remote sensing (RS) and geographic information systems (GIS). The physical factors of vulnerability were analyzed using GIS-based Structured Query Language (SQL). A questionnaire survey, GPS survey and field observation survey were conducted for collecting the primary data in the study area. The secondary data were mainly satellite image collected from the United States Geological Survey (USGS) website. Using time series Landsat images (MSS, TM and OLI-TIRS), this study analyzed 36 years of erosion and accretion process in the Mehendiganj Upazila region from 1980 to 2016. The result indicates that an enormous amount of land (4470.47 ha) was submerged by the river and average land loss rate was 124.18 ha/year. The study quantifies the number of vulnerable households beneath the present condition and how much it will be altered after a positive/negative change with the factors of vulnerability related to the households. Simulation data reveals that under the present physical condition, 43.88% of households were identified as severely vulnerable. The output of this study can be used in the classification of vulnerable households and for the improvement of the physical infrastructure development process near the erosion prone areas, also helps to mitigate environmental disaster in the developing countries

Spatial Accessibility to Hospitals Based on Web Mapping API: An Empirical Study in Kaifeng, China

The accessibility of hospital facilities is of great importance not only for maintaining social stability, but also for protecting the basic human right to health care. Traditional accessibility research often lacks consideration of the dynamic changes in transport costs and does not reflect the actual travel time of urban residents, which is critical to time-sensitive hospital services. To avoid these defects, this study considered the city of Kaifeng, China, as an empirical case, and directly acquired travel time data for two travel modes to the hospital in different time periods through web mapping API (Application Program Interface). Further, based on travel time calculations, we compared five baseline indicators. For the last indicator, we used the optimal weighted accessibility model to measure hospital accessibility for each residential area. The study discovered significant differences in the frequency and spatial distribution of hospital accessibility using public transit and self-driving modes of transportation. In addition, there is an imbalance between accessibility travel times in the study area and the number of arrivals at hospitals. In particular, different modes of transportation and different travel periods also have a certain impact on accessibility of medical treatment. The research results shed new light on the accessibility of urban public facilities and provide a scientific basis with which local governments can optimize the spatial structure of hospital resources

Perceived Human-Induced Causes of Landslide in Chattogram Metropolitan Area in Bangladesh

This study investigates Land Use Land Cover changes in the Chattogram metropolitan area, the second-largest city in Bangladesh. Using a questionnaire survey of 150 local inhabitants, the study explores perceived human-induced causes of landslides. Using time series Landsat images, this study also analyzes Land Use Land Cover changes from 1990 to 2020. The analysis reveals built-up area extended rapidly during 1990–2020. In 1990, total built-up area was 82.13 km2, which in 30 years, stood at 451.34 km2. Conversely, total vegetative area decreased rapidly. In 1990, total vegetation area was 364.31 km2, which reduced to 130.44 km2 in 2020. The survey results show that most of the respondents faced landslide therefore; it is nothing new among them. Respondents were identified several reasons for landslide like extensive rainfall, hill cutting, steep hill, weak soil texture, etc. A large number of local people opined that diverse human activities are causes of landslide in their local area and it has impacted on their livelihood. Chi-square test suggests that there are statistically significant differences between local and non-local inhabitants regarding their opinion on whether excessive hill cutting is alone responsible for landslide and whether deforestation is the sole reason for landslide. This study also used four multinomial logistic regression (MLR) to examine the effects of independent variables like gender, age, level of education, income, housing pattern and experience of facing landslide on their perception of human-induced causes of landslide. Findings show that age and experience of facing landslide are two significant predictors for the first model, explaining excessive hill cutting was alone responsible for landslide. Level of education and experience of facing landslide are found statistically significant for explaining our second model that is building infrastructures solely causes landslide. Moreover, our third model claims only deforestation can be blamed for landslide which is significantly explained by three predictors, namely gender, age and income. Finally, we found our fourth model that is landslide occurs only due to excessive sand collection is significantly explained by participant's gender, level of education, and income