Remote Sensing Technologies: Implications for Agricultural and Resource Economics

Howitt, Richard E.; Karp, Larry S.; Rausser, Gordon C.

doi:10.1007/978-3-030-77760-9_9

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…Last, the sixth is satellite services and maintenance. By expanding the scope of satellites to include quantum communication and remote sensing capabilities ( 44 ), the potential to strengthen the secure data and observation industry would unlock new economic opportunities. With the proliferation of satellites, servicing and debris regulations will also need to emerge ( 1 , 45 , 46 ).…”

Section: Research Cluster Synthesismentioning

confidence: 99%

Public–private partnerships in fostering outer space innovations

Rausser,

Choi,

Bayen

2023

Proc. Natl. Acad. Sci. U.S.A.

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As public and private institutions recognize the role of space exploration as a catalyst for economic growth, various areas of innovation are expected to emerge as drivers of the space economy. These include space transportation, in-space manufacturing, bioproduction, in-space agriculture, nuclear launch, and propulsion systems, as well as satellite services and their maintenance. However, the current nature of space as an open-access resource and global commons presents a systemic risk for exuberant competition for space goods and services, which may result in a “tragedy of the commons” dilemma. In the race among countries to capture the value of space exploration, NASA, American research universities, and private companies can avoid any coordination failures by collaborating in a public–private research and development partnership (PPRDP) structure. We present such a structure founded upon the principles of polycentric autonomous governance, which incorporate a decentralized autonomous organization framework and specialized research clusters. By advancing an alignment of incentives among the specified participatory members, PPRDPs can play a pivotal role in stimulating open-source research by creating positive knowledge spillover effects and agglomeration externalities as well as embracing the nonlinear decomposition paradigm that may blur the distinction between basic and applied research.

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Section: Research Cluster Synthesismentioning

confidence: 99%

Public–private partnerships in fostering outer space innovations

Rausser,

Choi,

Bayen

2023

Proc. Natl. Acad. Sci. U.S.A.

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“…The second category of supply-side interventions is increasing the capacity of law enforcement agencies. Unmanned aerial vehicles ( Jones et al 2006) or remote sensing technologies (Howitt et al 2022) are modern technological solutions that can be employed to monitor and protect wildlife from harm. These techniques can be used in conjunction with demand-side interventions.…”

Section: Supply-side Interventionsmentioning

confidence: 99%

The Economics of Wildlife Trade and Consumption

Prasad

Rausser

Zilberman

2022

Annu. Rev. Resour. Econ.

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The global wildlife trade dates to antiquity. Recently, its harms to endangered species, animal welfare, and public health have become critical to address. The complexities of the wildlife trade are numerous, including the fact that much of the economic activity is illegal and unobserved. We find that wildlife products are used for sustenance, signaling status, medicine, and entertainment. There is vast heterogeneity in products and species traded. Supply chains extend from biodiverse, low-income regions to richer countries or urban centers. Empirically, we use data findings from the literature to rank countries in terms of intensity of the wildlife trade and identify factors that contribute to wildlife trade. We also identify supply-side and demand-side interventions that can control abuse in wildlife trade. Innovative techniques for observation, econometric analysis, and enforcement are sorely needed to support effective policies to preserve the world's wildlife. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration

Li,

Cui,

et al. 2024

Remote Sensing

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Understanding and monitoring soil organic carbon (SOC) stocks is crucial for ecosystem carbon cycling, services, and addressing global environmental challenges. This study employs the BERTopic model and bibliometric trend analysis exploration to comprehensively analyze global SOC estimates. BERTopic, a topic modeling technique based on BERT (bidirectional encoder representatives from transformers), integrates recent advances in natural language processing. The research analyzed 1761 papers on SOC and remote sensing (RS), in addition to 490 related papers on machine learning (ML) techniques. BERTopic modeling identified nine research themes for SOC estimation using RS, emphasizing spectral prediction models, carbon cycle dynamics, and agricultural impacts on SOC. In contrast, for the literature on RS and ML it identified five thematic clusters: spatial forestry analysis, hyperspectral soil analysis, agricultural deep learning, the multitemporal imaging of farmland SOC, and RS platforms (Sentinel-2 and synthetic aperture radar, SAR). From 1991 to 2023, research on SOC estimation using RS and ML has evolved from basic mapping to topics like carbon sequestration and modeling with Sentinel-2A and big data. In summary, this study traces the historical growth and thematic evolution of SOC research, identifying synergies between RS and ML and focusing on SOC estimation with advanced ML techniques. These findings are critical to global ecosystem SOC assessments and environmental policy formulation.

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Remote Sensing Technologies: Implications for Agricultural and Resource Economics

Cited by 3 publications

References 28 publications

Public–private partnerships in fostering outer space innovations

Public–private partnerships in fostering outer space innovations

The Economics of Wildlife Trade and Consumption

Soil Organic Carbon Estimation via Remote Sensing and Machine Learning Techniques: Global Topic Modeling and Research Trend Exploration

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