XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/2: Health]

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia RISK ZONE MODELLING AND EARLY WARNING SYSTEM FOR VISCERAL LEISHMANIASIS (KALA-AZAR) DISEASE IN BIHAR, INDIA USING REMOTE SENSING AND GIS A. Jeyaram *, Shreekant Kesari ^, Anju Bajpai *, Gouri sankar Bhunia 5 YVN Krishna Murthy © ? Regional Remote Sensing Centre - East, National Remote Sensing Centre, Indian Space Research Organisation, Kolkata, India, ajeyaram2002 @yahoo.co.in ® Department of Vector Biology and Control, Rajendra Memorial Research Institute of Medical Sciences ICMR), Patna, India * Dy. Director (RC), National Remote Sensing Centre, ISRO, Hyderabad, India Commission VIII, WG VIIU2 KEY WORDS: Visceral Leishmaniasis, Kala-azar, vector density, Satellite data, Remote Sensing, GIS ABSTRACT: Visceral Leishmaniasis (VL) commonly known as Kala-azar is one of the most neglected tropical disease affecting approximately 200 million poorest populations ‘at risk’ in 109 districts of three endemic countries namely Bangladesh, India and Nepal at different levels. This tropical disease is caused by the protozoan parasite Leishmania donovani and transmitted by female Phlebotomus argentipes sand flies. The analysis of disease dynamics indicate the periodicity at seasonal and inter-annual temporal scale which forms the basis for development of advanced early warning system. Study area of highly endemic Vaishali district, Bihar, India has been taken for model development. A Systematic study of geo-environmental parameters derived from satellite data in conjunction with ground intelligence enabled modelling of infectious disease and risk villages. High resolution Indian satellites data of IRS LISS IV (multi-spectral) and Cartosat-1 (Pan) have been used for studying environmentally risk parameters viz. peri-domestic vegetation, dwelling condition, wetland ecosystem, cropping pattern, Normalised Difference Vegetation Index (NDVI), detailed land use etc towards risk assessment. Univariate analysis of the relationship between vector density and various land cover categories and climatic variables suggested that all the variables are significantly correlated. Using the significantly correlated variables with vector density, a seasonal multivariate regression model has been carried out incorporating geo-environmental parameters, climate variables and seasonal time series disease parameters. Linear and non-linear models have been applied for periodicity and inter- annual temporal scale to predict Man-hour-density (MHD) and ‘out-of-fit’ data set used for validating the model with reasonable accuracy. To improve the MHD predictive approach, fuzzy model has also been incorporated in GIS environment combining spatial geo-environmental and climatic variables using fuzzy membership logic. Based on the perceived importance of the geo- environmental parameters assigned by epidemiology expert, combined fuzzy membership has been calculated. The combined fuzzy membership indicate the predictive measure of vector density in each village. A Y factor has been introduced to have increasing effect in the higher side and decreasing effect in the lower side which facilitated for prioritisation of the villages. "This approach is not only to predict vector density but also to prioritise the villages for effective control measures. A software package for modelling the risk villages integrating multivariate regression and fuzzy membership analysis models have been developed to estimate MHD (vector density) as part of the early warning system. 1. INTRODUCTION Larvae 1.1 General India has 52 kala-azar endemic districts in four states of India - Bihar (31 districts with 62.3 million population), Uttar Pradesh (11 districts with 50.0 million population), West Bengal (6 districts with 11.0 million population), and Jharkhand (4 districts with 6.7 million population). Each year, Bihar alone contributes 70-80 % of the kala-azar cases. In 1992, the highest number of cases were reported (77170) after which the incidence has declined gradually. However, from 2003 to 2007 there has been a steady increase in the annual number of reported cases. In 2008, 31716 cases and 141 deaths were reported. A study in a predefined endemic focus revealed that an optimal of 8 Man-Hour-Density (MHD) which is critical : : . . : Transmit vector density was essential for P.argentipes enabling it to to Human Sandfly transmit infection from one infected host to a new host. The Bite transmission cycle of Kala-azar vector is shown in fig. 1. The sand fly is generally confined in the dwellings and occasionally goes out to take sucrose from the soft stem plants in the vicinity to digest the blood meal. In the present study, it was observed Sandfly tL Sandfty : Kala-azar Transmission Cycle — Fig. 1. Disease Transmission cycle of Kala-azar

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