Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis

Policy analyses of agricultural and environmental systems are often limited due to data constraints. Measurement campaigns can be costly, especially when the area of interest includes oceans, forests, agricultural regions or other dispersed spatial domains. Satellite based remote sensing offers a wa...

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Main Author: Welle, Paul
Format: Others
Published: Research Showcase @ CMU 2017
Subjects:
Online Access:http://repository.cmu.edu/dissertations/1012
http://repository.cmu.edu/cgi/viewcontent.cgi?article=2051&context=dissertations
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spelling ndltd-cmu.edu-oai-repository.cmu.edu-dissertations-20512017-08-22T03:23:41Z Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis Welle, Paul Policy analyses of agricultural and environmental systems are often limited due to data constraints. Measurement campaigns can be costly, especially when the area of interest includes oceans, forests, agricultural regions or other dispersed spatial domains. Satellite based remote sensing offers a way to increase the spatial and temporal resolution of policy analysis concerning these systems. However, there are key limitations to the implementation of satellite data. Uncertainty in data derived from remote-sensing can be significant, and traditional methods of policy analysis for managing uncertainty on large datasets can be computationally expensive. Moreover, while satellite data can increasingly offer estimates of some parameters such as weather or crop use, other information regarding demographic or economic data is unlikely to be estimated using these techniques. Managing these challenges in practical policy analysis remains a challenge. In this dissertation, I conduct five case studies which rely heavily on data sourced from orbital sensors. First, I assess the magnitude of climate and anthropogenic stress on coral reef ecosystems. Second, I conduct an impact assessment of soil salinity on California agriculture. Third, I measure the propensity of growers to adapt their cropping practices to soil salinization in agriculture. Fourth, I analyze whether small-scale desalination units could be applied on farms in California in order mitigate the effects of drought and salinization as well as prevent agricultural drainage from entering vulnerable ecosystems. And fifth, I assess the feasibility of satellite-based remote sensing for salinity measurement at global scale. Through these case studies, I confront both the challenges and benefits associated with implementing satellite based-remote sensing for improved policy analysis. 2017-08-01T07:00:00Z text application/pdf http://repository.cmu.edu/dissertations/1012 http://repository.cmu.edu/cgi/viewcontent.cgi?article=2051&context=dissertations Dissertations Research Showcase @ CMU Economics Policy Remote Sensing
collection NDLTD
format Others
sources NDLTD
topic Economics
Policy
Remote Sensing
spellingShingle Economics
Policy
Remote Sensing
Welle, Paul
Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
description Policy analyses of agricultural and environmental systems are often limited due to data constraints. Measurement campaigns can be costly, especially when the area of interest includes oceans, forests, agricultural regions or other dispersed spatial domains. Satellite based remote sensing offers a way to increase the spatial and temporal resolution of policy analysis concerning these systems. However, there are key limitations to the implementation of satellite data. Uncertainty in data derived from remote-sensing can be significant, and traditional methods of policy analysis for managing uncertainty on large datasets can be computationally expensive. Moreover, while satellite data can increasingly offer estimates of some parameters such as weather or crop use, other information regarding demographic or economic data is unlikely to be estimated using these techniques. Managing these challenges in practical policy analysis remains a challenge. In this dissertation, I conduct five case studies which rely heavily on data sourced from orbital sensors. First, I assess the magnitude of climate and anthropogenic stress on coral reef ecosystems. Second, I conduct an impact assessment of soil salinity on California agriculture. Third, I measure the propensity of growers to adapt their cropping practices to soil salinization in agriculture. Fourth, I analyze whether small-scale desalination units could be applied on farms in California in order mitigate the effects of drought and salinization as well as prevent agricultural drainage from entering vulnerable ecosystems. And fifth, I assess the feasibility of satellite-based remote sensing for salinity measurement at global scale. Through these case studies, I confront both the challenges and benefits associated with implementing satellite based-remote sensing for improved policy analysis.
author Welle, Paul
author_facet Welle, Paul
author_sort Welle, Paul
title Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
title_short Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
title_full Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
title_fullStr Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
title_full_unstemmed Remotely Sensed Data for High Resolution Agro-Environmental Policy Analysis
title_sort remotely sensed data for high resolution agro-environmental policy analysis
publisher Research Showcase @ CMU
publishDate 2017
url http://repository.cmu.edu/dissertations/1012
http://repository.cmu.edu/cgi/viewcontent.cgi?article=2051&context=dissertations
work_keys_str_mv AT wellepaul remotelysenseddataforhighresolutionagroenvironmentalpolicyanalysis
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