Roadside collection of training data for cropland mapping is viable when environmental and management gradients are surveyed

International Journal of Applied Earth Observation and Geoinformation

Volumn 80, Issue , 2019, Pages 82-93

  Waldner, François ^a,b   Bellemans, Nicolas ^b   Hochman, Zvi ^a   Newby, Terence ^c   de Abelleyra, Diego ^d   Verón, Santiago R ^d   Bartalev, Sergey ^e   Lavreniuk, Mykola ^f   Kussul, Nataliia ^f   Maire, Guerric Le ^g,h,i,j   Simoes, Margareth ^k   Skakun, Sergii ^l   Defourny, Pierre ^b  

^a CSIRO   (Australia)

^b UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^c AGRICULTURAL RESEARCH COUNCIL   (South Africa)

^d INSTITUTO NACIONAL DE TECNOLOGÍA AGROPECUARIA INTA   (Argentina)

^e Space Research Institute of Russian Academy of Sciences ^*  (Russian Federation)

^f INSTITUTE OF HYDROBIOLOGY   (Ukraine)

^g CIRAD   (France)

^h UNIV MONTPELLIER   (France)

ⁱ UNIVERSITY OF CAMPINAS   (Brazil)

^j BRAZILIAN CENTER FOR RESEARCH IN ENERGY AND MATERIALS CNPEM   (Brazil)

^k STATE UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^l UNIVERSITY OF MARYLAND   (United States)

more..

Author keywords

Accuracy; Agriculture; Classification; Representativeness; Sample size; Sampling

Indexed keywords

ACCURACY ASSESSMENT; AGRICULTURAL LAND; AGRICULTURAL MANAGEMENT; DATA SET; ENVIRONMENTAL GRADIENT; LAND CLASSIFICATION; MAPPING; ROADSIDE ENVIRONMENT; SAMPLING; SURVEY;

EID: 85061348357     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2019.01.002     Document Type: Article

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