کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
84335 158875 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling the spatial distribution of crop sequences at a large regional scale using land-cover survey data: A case from France
ترجمه فارسی عنوان
مدل سازی توزیع فضایی توالی های زراعی در یک مقیاس بزرگ منطقه ای با استفاده از داده های نظرسنجی زمین: یک پرونده از فرانسه
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• Mining crop sequences in land survey dataset with hidden Markov models.
• Estimation of the crop sequence probabilities without a priori using survey data.
• District clustering based on the similarity of occurrence of crop sequences.
• Cluster description in terms of 21 groups belonging to four cropping systems.

Assessing the environmental impacts of agricultural production systems requires spatially explicit information regarding cropping systems. Projecting changes in agricultural land use that are caused by changes in land management practices for analyzing the performance of land activity-related policies, such as agricultural policies, also requires this type of data for model inputs. Crop sequences, which are vital and widely adopted agricultural practices, are difficult to directly detect at a regional scale. This study presents innovative stochastic data mining that was aimed at describing the spatial distribution of crop sequences at a large regional scale. The data mining is performed by hidden Markov models and an unsupervised clustering analysis that processes sequentially observed (from 1992 to 2003) land-cover survey data on the French mainland named Teruti. The 2549 3-year crop sequences were first identified as major crop sequences across the entire territory, which included 406 (merged) agricultural districts, using hidden Markov models. The 406 (merged) agricultural districts were then grouped into 21 clusters according to the similarity of the probabilities of occurrences of major 3-year crop sequences using hierarchical clustering analysis. Four cropping systems were further identified: vineyard-based cropping systems, maize monoculture and maize/wheat-based cropping systems, temporary pasture and maize-based cropping systems and wheat and barley-based cropping systems. The modeling approach that is presented in this study provides a tool to extract large-scale cropping patterns from increasingly available time series data on land-cover and land-use. With this tool, users can (a) identify the homogeneous zones in terms of fixed-length crop sequences across a large territory, (b) understand the characteristics of cropping systems within a region in terms of typical crop sequences, and (c) identify the major crop sequences of a region according to the probabilities of occurrences.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 102, March 2014, Pages 51–63
نویسندگان
, , , ,