Contextualizing the global relevance of local land change observations
To understand global changes in the Earth system, scientists must generalize globally from
observations made locally and regionally. In land change science (LCS), local field-based
observations are costly and time consuming, and generally obtained by researchers working
at disparate local and regional case-study sites chosen for different reasons. As a result,
global synthesis efforts in LCS tend to be based on non-statistical inferences subject to
geographic biases stemming from data limitations and fragmentation. Thus, a fundamental …
observations made locally and regionally. In land change science (LCS), local field-based
observations are costly and time consuming, and generally obtained by researchers working
at disparate local and regional case-study sites chosen for different reasons. As a result,
global synthesis efforts in LCS tend to be based on non-statistical inferences subject to
geographic biases stemming from data limitations and fragmentation. Thus, a fundamental …
Contextualizing the global relevance of local land change observations
To understand global changes in the Earth system, scientists must generalize globally from
observations made locally and regionally. In land change science (LCS), local field-based
observations are costly and time consuming, and generally obtained by researchers working
at disparate local and regional case-study sites chosen for different reasons. As a result,
global synthesis efforts in LCS tend to be based on non-statistical inferences subject to
geographic biases stemming from data limitations and fragmentation. Thus, a fundamental …
observations made locally and regionally. In land change science (LCS), local field-based
observations are costly and time consuming, and generally obtained by researchers working
at disparate local and regional case-study sites chosen for different reasons. As a result,
global synthesis efforts in LCS tend to be based on non-statistical inferences subject to
geographic biases stemming from data limitations and fragmentation. Thus, a fundamental …
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