Kosovo is one of the most environmentally degraded countries in Europe. It is also one of the poorest. The country lacks the capacity to conduct environmental assessments to gauge the scale of its environmental problems. It has even less capacity to understand its vulnerability to climate change and its prognosis for sustainable development. This paper describes the use of available (open) resources by the technically trained to understand environmental changes and provide a framework for developmental research that provides practical understandings of climate impacts. There tends to be a lack of awareness of the tools and scant knowledge of their use towards sustainable development. An environmental assessment of Kosovo using large and open remote-sensing data from Google Earth Engine is explained through an embedded multi-case design. Our approach used publicly available models and code walkthroughs from the book Cloud-based Remote Sensing with Google Earth Engine. The models were coded for Kosovo and the greater western Balkans region in JavaScript using Google Earth Engine open datasets to analyze environmental conditions in this region. This work demonstrates the value of free and open tool development and analysis for development of environmental sustainability. The use of open data requires careful analytical designs and the application of correct tools for specific regions and particular uses. Complex environmental conditions can muddle the data and analyses generated from open datasets. The “un-muddled” analysis performed here adds to the knowledge base of the environmental conditions within Kosovo and provides insight into regional assessment of changing climates. Models for air pollution and population exposure, groundwater monitoring with GRACE, urban environments, and deforestation viewed from multiple sensors were compiled into an environmental assessment of the scopes and scales of several environmental issues that plague Kosovo. The air pollution and population exposure model assesses the human toll of air pollution in Kosovo. Groundwater monitoring with Gravity Recovery and Climate Experiment (GRACE) appraises the health of aquifers and the security of water resources. Urban-environment analysis evaluates the changes that are occurring in urban locations in Kosovo. And the deforestation model is used to determine and evaluate the changes to several environments in Kosovo. The project will also include discussions of scalability to understand how the interconnected environmental conditions of the Balkans region can be further studies. The models, analytical frameworks, and overarching goals provide a robust strategy towards practical leveraging of remote sensed data to provide intrinsic value into developmental countries. The methods are interchangeable and replicable for climate-change analysis, sustainability decision making, and monitoring of environmental change. The urban expansion in Kosovo from 2010 till 2020 is studied with Landsat and MODIS mission data to understand the consequences of land use change. The air pollution and population exposure model employs Sentinel-5 TROPOMI and population density data to help discern air pollution levels and the human toll of environmental degradation. The groundwater monitoring application uses Gravity Recovery and Climate Experiment strives to clarify water storage capacities and trends within Kosovo’s aquifers. The forest degradation and deforestation model uses Landsat mission data to understand the changes occurring within the forests of Kosovo. The combination of these models creates a comprehensive case study of the environmental conditions within Kosovo and provides a baseline for understanding the effects of changing climates in the region. This information is crucial in developing effective strategies to address the challenges posed by climate change and to ensure a sustainable future for the region. This paper clarifies the methods used for modeling of big data sets in Google Earth Engine to generate products that can be used to assess both climate change and environmental change. We explore the frameworks for cloud computing of open-data environmental analyses by evaluating data selection and analytical techniques to provide an analytical framework for future development. Further building the cross-sectional understanding of the leverage utility of Google Earth Engine with analytical frameworks that provide utility with developing academic frameworks for resilience building and products that can traverse into government institutional knowledge building, private sector sustainable developmental gaps, public sector environmental and climate developmental strategies. The emergence of new technologies has provided opportunities for new approaches to broadly understand the impacts of global climate change and free-to-use frameworks places the capacity to understand attainable for developing countries. The use of this technology enables development of a regional understanding of climate change, its impacts, and the approaches for enhancing resilience through analysis of petabytes of open satellite data. This paper delivers a framework with which remotely sensed data can be assessed to understand how human-environment interactions in developing nations will be influenced by changing climates. These models which are all functionally different have environmental links that through development provides the future of open big data for building climate change resilience through a remote sensed top to bottom understanding of what the data means and how it can be applied.
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Speakers: Dustin Sanchez