Corpus ID: 218478396

An application to India

@inproceedings{Vogel2018AnAT,
  title={An application to India},
  author={Kathryn Baragwanath Vogel and Ran Goldblatt and Gordon Hanson and Amit K. Khandelwal},
  year={2018}
}
We propose a methodology for defining urban markets based on builtup landcover classified from daytime satellite imagery. Compared to markets defined using minimum thresholds for nighttime light intensity, daytime imagery identify an order of magnitude more markets, capture more of India’s urban population, are more realistically jagged in shape, and reveal more variation in the spatial distribution of economic activity. We conclude that daytime satellite data are a promising source for the… Expand
Rising Health Expenditure Due to Non-Communicable Diseases in India: An Outlook
TLDR
The health scenario of India in the wake of the growing pace of non-communicable diseases such as diabetes and hypertension among Indian population is explored using data from health and morbidity survey of the National Sample Survey Organisation (2004) and about the resource needed to tackle this growing health risk is notified. Expand
How successful are banking sector reforms in emerging market economies? Evidence from impact of monetary policy on levels and structures of firm debt in India
ABSTRACT Many emerging markets have undertaken significant financial sector reforms, especially in their banking sectors, that are critical for both financial development and real economic activity.Expand

References

SHOWING 1-10 OF 68 REFERENCES
Detecting the Boundaries of Urban Areas in India: A Dataset for Pixel-Based Image Classification in Google Earth Engine
TLDR
A new dataset is presented, consisting of 21,030 polygons from across the country that were manually classified as “built-up” or “not built-up,” which is used for supervised image classification and detection of urban areas in India and has potential use in GEE for temporal large-scale analysis of the urbanization process. Expand
Using Landsat and nighttime lights for supervised pixel-based image classification of urban land cover
TLDR
An efficient and low-cost machine-learning approach for pixel-based image classification of built-up areas at a large geographic scale using Landsat data is presented, which combines nighttime-lights data and Landsat 8 and overcomes the lack of extensive ground-reference data. Expand
A cluster-based method to map urban area from DMSP/OLS nightlights
Abstract Accurate information on urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/OperationalExpand
Delineating Urban Areas Using Building Density
TLDR
A new dartboard methodology to delineate urban areas using detailed information about building location is developed, which is implemented using a map of all buildings in France and compares actual building density after smoothing to counterfactual smoothed building density computed after randomly redistributing buildings. Expand
Mapping sub-pixel urban expansion in China using MODIS and DMSP/OLS nighttime lights
Abstract Urbanization accelerated rapidly in China during the first decade of the 21st century, largely at the expense of agricultural lands. To improve available regional information related to theExpand
Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data
TLDR
This study endeavours to illuminate the process of urbanization in India using Defence Meteorological Satellites Program – Operational Linescan System (DMSP-OLS) night time lights (NTLs) and SPOT vegetation (VGT) dataset for the period 1998–2008. Expand
Scaling up to National/Regional Urban Extent Mapping Using Landsat Data
  • G. Trianni, G. Lisini, +4 authors P. Gamba
  • Geography, Computer Science
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • 2015
TLDR
This paper describes a methodology to extract a consistent human settlement extent layer using Landsat data and its implementation in the Google Earth Engine platform, allowing to check their evolution at 30-m spatial resolution. Expand
Detecting Change in Urban Areas at Continental Scales with MODIS Data
Abstract Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansionExpand
Analysis of urban growth and estimating population density using satellite images of nighttime lights and land-use and population data
We investigated the spatiotemporal dynamics of urban expansion in Japan from 1990 to 2006 by using gridded land-use data, population census data, and satellite images of nighttime lights. First, weExpand
Cities in Bad Shape : Urban Geometry in India ∗
The spatial layout of cities is an important feature of urban form, highlighted by urban planners but overlooked by economists. This paper investigates the causal economic implications of city shapeExpand
...
1
2
3
4
5
...