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Article ; Online: Cropland expansion in Ecuador between 2000 and 2016.

José I Ochoa-Brito / Aniruddha Ghosh / Robert J Hijmans

PLoS ONE, Vol 18, Iss 9, p e

2023 Volume 0291753

Abstract: We describe changes in the cropland distribution for physiographic and bioregions of continental Ecuador between 2000 and 2016 using Landsat satellite data and government statistics. The cloudy conditions in Ecuador are a major constraint to satellite ... ...

Abstract	We describe changes in the cropland distribution for physiographic and bioregions of continental Ecuador between 2000 and 2016 using Landsat satellite data and government statistics. The cloudy conditions in Ecuador are a major constraint to satellite data analysis. We developed a two-stage cloud filtering algorithm to create cloud-free multi-temporal Landsat composites that were used in a Random Forest model to identify cropland. The overall accuracy of the model was 78% for the Coast region, 86% for the Andes, and 98% for the Amazon region. Cropland density was highest in the coastal lowlands and in the Andes between 2500 and 4400 m. During this period, cropland expansion was most pronounced in the Páramo, Chocó Tropical Rainforests, and Western Montane bioregions. There was no cropland expansion detected in the Eastern Foothill forests bioregion. The satellite data analysis further showed a small contraction of cropland (4%) in the Coast physiographic region, and cropland expansion in the Andes region (15%), especially above 3500m, and in the Amazon region (57%) between 2000 and 2016. The government data showed a similar contraction for the Coast (7%) but, in contrast with the satellite data, they showed a large agricultural contraction in the Andes (39%) and Amazon (50%). While the satellite data may be better at estimating relative change (trends), the government data may provide more accurate absolute numbers in some regions, especially the Amazon because separating pasture and tree crops from forest with satellite data is challenging. These discrepancies illustrate the need for careful evaluation and comparison of data from different sources when analyzing land use change.
Keywords	Medicine ; R ; Science ; Q
Subject code	910
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Intermediate Value Theorem and Decision-Making in Psychology and Economics

Aniruddha Ghosh / Mohammed Ali Khan / Metin Uyanik

Games, Vol 13, Iss 4, p

An Expositional Consolidation

2022 Volume 51

Abstract: On taking the intermediate value theorem (IVT) and its converse as a point of departure, this paper connects the intermediate value property (IVP) to the continuity postulate typically assumed in mathematical economics, and to the solvability axiom ... ...

Abstract	On taking the intermediate value theorem (IVT) and its converse as a point of departure, this paper connects the intermediate value property (IVP) to the continuity postulate typically assumed in mathematical economics, and to the solvability axiom typically assumed in mathematical psychology. This connection takes the form of four portmanteau theorems, two for functions and the other two for binary relations, that give a synthetic and novel overview of the subject. In supplementation, the paper also surveys the antecedent literature both on the IVT itself, as well as its applications in economic and decision theory. The work underscores how a humble theorem, when viewed in a broad historical frame, bears the weight of many far-reaching consequences; and testifies to a point of view that the apparently complicated can sometimes be under-girded by a most basic and simple execution.
Keywords	intermediate value theorem ; intermediate value property ; solvability ; continuity ; wold-continuity ; archimedeanity ; Technology ; T ; Social Sciences ; H
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identifying Dry-Season Rice-Planting Patterns in Bangladesh Using the Landsat Archive

Aaron M. Shew / Aniruddha Ghosh

Remote Sensing, Vol 11, Iss 10, p

2019 Volume 1235

Abstract: In many countries, in situ agricultural data is not available and cost-prohibitive to obtain. While remote sensing provides a unique opportunity to map agricultural areas and management characteristics, major efforts are needed to expand our ... ...

Abstract	In many countries, in situ agricultural data is not available and cost-prohibitive to obtain. While remote sensing provides a unique opportunity to map agricultural areas and management characteristics, major efforts are needed to expand our understanding of cropping patterns and the potential for remotely monitoring crop production because this could support predictions of food shortages and improve resource allocation. In this study, we demonstrate a new method to map paddy rice using Google Earth Engine (GEE) and the Landsat archive in Bangladesh during the dry (boro) season. Using GEE and Landsat, dry-season rice areas were mapped at 30 m resolution for approximately 90,000 km 2 annually between 2014 and 2018. The method first reconstructs spectral vegetation indices (VIs) for individual pixels using a harmonic time series (HTS) model to minimize the effect of any sensor inconsistencies and atmospheric noise, and then combines the time series indices with a rule-based algorithm to identify characteristics of rice phenology to classify rice pixels. To our knowledge, this is the first time an annual pixel-based time series model has been applied to Landsat at the national level in a multiyear analysis of rice. Findings suggest that the harmonic-time-series-based vegetation indices (HTS-VIs) model has the potential to map rice production across fragmented landscapes and heterogeneous production practices with comparable results to other estimates, but without local management or in situ information as inputs. The HTS-VIs model identified 4.285, 4.425, 4.645, 4.117, and 4.407 million rice-producing hectares for 2014, 2015, 2016, 2017, and 2018, respectively, which correlates well with national and district estimates from official sources at an average R-squared of 0.8. Moreover, accuracy assessment with independent validation locations resulted in an overall accuracy of 91% and a kappa coefficient of 0.83 for the boro/non-boro stable rice map from 2014 to 2018. We conclude with a discussion of potential ...
Keywords	Bangladesh ; boro rice ; time series ; food security ; Landsat ; Google Earth Engine ; Science ; Q
Subject code	333
Language	English
Publishing date	2019-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Modeling of Thermel Transport for GMAW

Aniruddha Ghosh

Mathematical Problems in Engineering, Vol

2012 Volume 2012

Keywords	Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Mathematics ; DOAJ:Mathematics and Statistics ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Technology ; T ; DOAJ:General and Civil Engineering ; DOAJ:Technology and Engineering
Language	English
Publishing date	2012-01-01T00:00:00Z
Publisher	Hindawi Publishing Corporation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Amphibian collapses increased malaria incidence in Central America

Michael R Springborn / Joakim A Weill / Karen R Lips / Roberto Ibáñez / Aniruddha Ghosh

Environmental Research Letters, Vol 17, Iss 10, p

2022 Volume 104012

Abstract: Biodiversity in ecosystems plays an important role in supporting human welfare, including regulating the transmission of infectious diseases. Many of these services are not fully-appreciated due to complex environmental dynamics and lack of baseline data. ...

Abstract	Biodiversity in ecosystems plays an important role in supporting human welfare, including regulating the transmission of infectious diseases. Many of these services are not fully-appreciated due to complex environmental dynamics and lack of baseline data. Multicontinental amphibian decline due to the fungal pathogen Batrachochytrium dendrobatidis (Bd) provides a stark example. Even though amphibians are known to affect natural food webs—including mosquitoes that transmit human diseases—the human health impacts connected to their massive decline have received little attention. Here we leverage a unique ensemble of ecological surveys, satellite data, and newly digitized public health records to show an empirical link between a wave of Bd-driven collapse of amphibians in Costa Rica and Panama and increased human malaria incidence. Subsequent to the estimated date of Bd-driven amphibian decline in each ‘county’ (canton or distrito), we find that malaria cases are significantly elevated for several years. For the six year peak of the estimated effect, the annual expected county-level increase in malaria ranges from 0.76 to 1.1 additional cases per 1000 population. This is a substantial increase given that cases country-wide per 1000 population peaked during the timeframe of our study at approximately 1.5 for Costa Rica and 1.1 for Panama. This previously unidentified impact of biodiversity loss illustrates the often hidden human welfare costs of conservation failures. These findings also show the importance of mitigating international trade-driven spread of similar emergent pathogens like Batrachochytrium salamandrivorans .
Keywords	infectious disease ; ecosystem services ; malaria ; amphibian chytrid fungus ; biodiversity ; event-study ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350 ; Science ; Q ; Physics ; QC1-999
Subject code	333
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	IOP Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Agricultural intensification was associated with crop diversification in India (1947-2014).

Jamey C Smith / Aniruddha Ghosh / Robert J Hijmans

PLoS ONE, Vol 14, Iss 12, p e

2019 Volume 0225555

Abstract: Declines in agricultural biodiversity associated with modern farming practices may negatively affect the sustainability of agro-ecosystems, but formal knowledge of historical variation in spatio-temporal variation of agro-biodiversity is limited. We used ...

Abstract	Declines in agricultural biodiversity associated with modern farming practices may negatively affect the sustainability of agro-ecosystems, but formal knowledge of historical variation in spatio-temporal variation of agro-biodiversity is limited. We used time series of national (1947-2014) and district-level (1956-2008) crop distribution data for India to show that despite strong agricultural intensification after 1960, the average crop species diversity at the district level was stable, but increased at the country-level. While there was a decline in diversity in the major rice and wheat producing regions of northwestern India, associated with intensification of the production of these crops, diversity in western and southern India increased due to expansion of oilseeds and horticultural crops that replaced millet and sorghum. These opposite, but related, trends in crop-level diversity at the sub-national level partially canceled each other out at national level, but there nevertheless was a noticeable increase in overall crop diversity in India during this time period. Our results illustrate how patterns of change in crop diversity need to be considered at different levels of aggregation, and how a decrease in diversity associated with intensification and specialization in one area, may be associated with increased diversity elsewhere, and that support for intensive agriculture with relatively low crop diversity in some regions may be associated with an increase in crop diversity in other regions and at a higher level of aggregation.
Keywords	Medicine ; R ; Science ; Q
Subject code	333 ; 571
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Satellite-Based Observations Reveal Effects of Weather Variation on Rice Phenology

Hongfei Wang / Aniruddha Ghosh / Bruce A. Linquist / Robert J. Hijmans

Remote Sensing, Vol 12, Iss 1522, p

2020 Volume 1522

Abstract: Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over ...

Abstract	Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over large areas through field observations. The use of satellite remote sensing data has made phenology data collection easier, although the quality and the utility of such data to understand agro-ecosystem function have not been widely studied. Here, we evaluated satellite data-based estimates of rice phenological stages in California, USA by comparing them with survey data and with predictions by a temperature-driven phenology model. We then used the satellite data-based estimates to quantify the crop phenological response to changes in weather. We used time-series of MODIS satellite data and PhenoRice, a rule-based rice phenology detection algorithm, to determine annual planting, heading and harvest dates of paddy rice in California between 2002 and 2017. At the state level, our satellite-based estimates of rice phenology were very similar to the official survey data, particularly for planting and harvest dates (RMSE = 3.8–4.0 days). Satellite based observations were also similar to predictions by the DD10 temperature-driven phenology model. We analyzed how the timing of these phenological stages varied with concurrent temperature and precipitation over this 16-year time period. We found that planting was earlier in warm springs (−1.4 days °C −1 for mean temperature between mid-April and mid-May) and later in wet years (5.3 days 100 mm -1 for total precipitation from March to April). Higher mean temperature during the pre-heading period of the growing season advanced heading by 2.9 days °C −1 and shortened duration from planting to heading by 1.9 days °C −1 . The entire growing season was reduced by 3.2 days °C −1 because of the increased temperature during the rice season. Our findings confirm that satellite data can be an effective way to estimate variations in rice phenology and can provide critical information that can be used to improve understanding of agricultural responses to weather variation.
Keywords	crop phenology ; remote sensing ; weather variation ; rice ; California ; Science ; Q
Subject code	333
Language	English
Publishing date	2020-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Evaluating the quality of remote sensing products for agricultural index insurance.

Benson K Kenduiywo / Michael R Carter / Aniruddha Ghosh / Robert J Hijmans

PLoS ONE, Vol 16, Iss 10, p e

2021 Volume 0258215

Abstract: Agricultural index insurance contracts increasingly use remote sensing data to estimate losses and determine indemnity payouts. Index insurance contracts inevitably make errors, failing to detect losses that occur and issuing payments when no losses ... ...

Abstract	Agricultural index insurance contracts increasingly use remote sensing data to estimate losses and determine indemnity payouts. Index insurance contracts inevitably make errors, failing to detect losses that occur and issuing payments when no losses occur. The quality of these contracts and the indices on which they are based, need to be evaluated to assess their fitness as insurance, and to provide a guide to choosing the index that best protects the insured. In the remote sensing literature, indices are often evaluated with generic model evaluation statistics such as R2 or Root Mean Square Error that do not directly consider the effect of errors on the quality of the insurance contract. Economic analysis suggests using measures that capture the impact of insurance on the expected economic well-being of the insured. To bridge the gap between the remote sensing and economic perspectives, we adopt a standard economic measure of expected well-being and transform it into a Relative Insurance Benefit (RIB) metric. RIB expresses the welfare benefits derived from an index insurance contract relative to a hypothetical contract that perfectly measures losses. RIB takes on its maximal value of one when the index contract offers the same economic benefits as the perfect contract. When it achieves none of the benefits of insurance it takes on a value of zero, and becomes negative if the contract leaves the insured worse off than having no insurance. Part of our contribution is to decompose this economic well-being measure into an asymmetric loss function. We also argue that the expected well-being measure we use has advantages over other economic measures for the normative purpose of insurance quality ascertainment. Finally, we illustrate the use of the RIB measure with a case study of potential livestock insurance contracts in Northern Kenya. We compared 24 indices that were made with 4 different statistical models and 3 remote sensing data sources. RIB for these indices ranged from 0.09 to 0.5, and R2 ranged from 0.2 to ...
Keywords	Medicine ; R ; Science ; Q
Subject code	330
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Leveraging Digital Tools and Crowdsourcing Approaches to Generate High-Frequency Data for Diet Quality Monitoring at Population Scale in Rwanda

Rhys Manners / Julius Adewopo / Marguerite Niyibituronsa / Roseline Remans / Aniruddha Ghosh / Marc Schut / Seth Gogo Egoeh / Regina Kilwenge / Anna Fraenzel

Frontiers in Sustainable Food Systems, Vol

2022 Volume 5

Abstract: Diet quality is a critical determinant of human health and increasingly serves as a key indicator for food system sustainability. However, data on diets are limited, scattered, often project-dependent, and current data collection systems do not support ... ...

Abstract	Diet quality is a critical determinant of human health and increasingly serves as a key indicator for food system sustainability. However, data on diets are limited, scattered, often project-dependent, and current data collection systems do not support high-frequency or consistent data flows. We piloted in Rwanda a data collection system, powered by the principles of citizen science, to acquire high frequency data on diets. The system was deployed through an unstructured supplementary service data platform, where respondents were invited to answer questions regarding their dietary intake. By combining micro-incentives with a normative nudge, 9,726 responses have been crowdsourced over 8 weeks of data collection. The cost per respondent was < $1 (system set-up, maintenance, and a small payment to respondents), with interactions taking <15 min. Exploratory analyses show that >70% of respondents consume tubers and starchy vegetables, leafy vegetables, fruits, legumes, and wholegrains. Women consumed better quality diets than male respondents, revealing a sex-based disparity in diet quality. Similarly, younger respondents (age ≤ 24 years) consumed the lowest quality diets, which may pose significant risks to their health and mental well-being. Middle-income Rwandans were identified to have consumed the highest quality diets. Long-term tracking of diet quality metrics could help flag populations and locations with high probabilities of nutrition insecurity, in turn guiding relevant interventions to mitigate associated health and social risks.
Keywords	citizen science ; dietary patterns ; digital data collection ; USSD ; Rwanda ; Nutrition. Foods and food supply ; TX341-641 ; Food processing and manufacture ; TP368-456
Subject code	360
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Psychiatric sequelae of traumatic brain injury (TBI)

Ambarish Ghosh / Birva Desai / Arghya Halder / Aniruddha Ghosh / Priyanka Das / Daniel Saldanha

Asian Journal of Medical Sciences, Vol 11, Iss 5, Pp 77-

2020 Volume 82

Abstract: Background: Traumatic brain injury (TBI), a leading cause of morbidity and mortality worldwide, is an alteration in brain function, caused by an external force. With rapid surge in urbanization, motorization and economic liberalization in India, risk of ... ...

Abstract	Background: Traumatic brain injury (TBI), a leading cause of morbidity and mortality worldwide, is an alteration in brain function, caused by an external force. With rapid surge in urbanization, motorization and economic liberalization in India, risk of TBI is increased, raising a cause for concern about its neurological as well as psychiatric sequelae. Aims and Objectives: This study was planned to understand the magnitude of the problem which could give us insights to manage/ rehabilitate it in a more comprehensive manner. Materials and Methods: The current study included 50 patients aged 18-60 years at DY Patil Medical College, Pune. GCS scores were noted for severity of TBI. Patients were assessed through MMSE, BCRS, HAM-A & BDI. Results: On GCS, 20% cases had severe head injury; 22% moderate and 58% had mild. On MMSE initially, at six months and one year; 26.19%, 21.88% & 11.1% cases had cognitive impairment respectively. On BCRS, 38.10%, 34.4% & 37.10% cases had cognitive deterioration initially, at six month & at one year respectively. On HAM-A, mild & moderate to severe anxiety was found in 64.3% & 35.7% cases respectively. On BDI, initially 7.14% cases had depression, 25% at six months and 37.05% after one year. No statistically significant change was seen in BCRS score during follow up. Comparison of the mean scores at first interview and at six months demonstrated statistically significant (P-value p<0.005) differences in MMSE as well as BDI. Conclusion: TBI is associated with n increased risk of psychiatric disorders and may need psychiatric interventions later.
Keywords	cognitive deficits ; depression ; anxiety ; psychiatric sequelae ; traumatic brain injury ; Medicine ; R
Subject code	150
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Manipal College of Medical Sciences, Pokhara
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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