Developing a science of land change: challenges and methodological issues.

By Ronald R. Rindfuss, S. Walsh, Billie L. Turner II, Jefferson Metz Fox, V. Mishra. Proceedings of the National Academy of Sciences of the United States of America, 2004

676 citations recorded by the source corpus.

Subfields: General Agricultural and Biological Sciences, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d01378408cc72d65ec6fd0c912b7f6dba44c6288

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Citations in the corpus

Assessing the accuracy of land cover change with imperfect ground reference data (2010, background): “However, numerous challenges are, or are perceived to be, encountered with the use of remote sensing for the derivation of information on land cover (Foody, 2002, 2008; Rindfuss et al., 2004; Strahler et al., 2006).”
Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Munessa-Shashemene Landscape of the Ethiopian Highlands (2013, background): “However, the magnitude of LULC change differs with the time period being examined [9], geographical location [10], slope gradient, and elevation range [11,12].”
Globalization of land use: distant drivers of land change and geographic displacement of land use (2013, background): “Although international forces were recognized, deforestation and other land changes were analyzed as domestic processes, by linking remote sensing data on land cover with socioeconomic survey data on land use decisions by agents [5,6].”
Conservation opportunities across the world's anthromes (2014, background): “Responding to a need for biogeographical frameworks that incorporate human processes, an increasing number of researchers and practitioners are promoting the use of integrative global-scale models of human–environment interactions (Rindfuss et al., 2004; Ellis et al., 2013), including ‘anthromes’ (a”
Physical and Socioeconomic Driving Forces of Land‐Use and Land‐Cover Changes: A Case Study of Wuhan City, China (2016, neutral): “Understanding the driving mechanisms of LUCC caused by a variety of driving forces is one of the major goals of global change research in recent decades [8–10].”
Linking Land Change with Driving Forces and Actors: Four Conceptual Models (2010, background): “The aim of land change science is to understand the biophysical and human causes of land use and land cover change, and the land use and land cover patterns and dynamics affecting the structure and function of the earth system (Rindfuss et al. 2004).”
Energy systems modeling for twenty-first century energy challenges (2014, background): “In land-use modeling in particular, the scale issue has been recognized and documented (Rindfuss et al., 2004; Evans and Kelley, 2004), and multi-scale models have emerged as a prominent and important method.”
Harshness in image classification accuracy assessment (2008, background): “Classification accuracy assessment is still very much a topic for further research (Rindfuss et al. 2004, Strahler et al. 2006).”
Biological Diversity in Agriculture and Global Change (2010, background): “The latter criteria suggest use of analytic frameworks combining GIS and imagery techniques along with possible integration of the LCS and LUCC approaches (1, 78).”
International wood trade and forest change: A global analysis (2011, background): “Anthropogenic changes of natural forests are in the very center of land change science, which seeks to understand how human environment relations shape land uses and covers (Rindfuss et al., 2004; Turner et al., 2007).”
The forest transition: Towards a more comprehensive theoretical framework☆ (2010, background): “These wo approaches characterized the early development of what is ow called land change science (Rindfuss et al., 2004).”
Issues in spatially explicit statistical land-use/cover change (LUCC) models: Examples from western (2007, methodology): “These problems require the use of sampling strategies that filter such dependence (Elhorst, 2001), or other more explicit correction for spatial autocorrelation (Rindfuss et al., 2004), including the use of spatial regression techniques (Anselin, 2002).”