Evaluating PlanetScope and UAV Multispectral Data for Monitoring Winter Wheat and Sustainable Fertilization Practices in Mediterranean Agroecosystems

被引:0
|
作者
Moletto-Lobos, Italo [1 ]
Cyran, Katarzyna [1 ]
Orden, Luciano [2 ,3 ]
Sanchez-Mendez, Silvia [2 ]
Franch, Belen [1 ,4 ]
Kalecinski, Natacha [4 ]
Andreu-Rodriguez, Francisco J. [2 ]
Mira-Urios, Miguel a. [2 ]
Saez-Tovar, Jose A. [2 ]
Guillevic, Pierre C. [5 ]
Moral, Raul [2 ]
机构
[1] Univ Valencia, Global Change Unit, Image Proc Lab, Paterna 46980, Spain
[2] Univ Miguel Hernandez, Inst Invest & Innovac Agrolimentaria & Agroambient, Carretera Carretera Beniel Km 3-2, Orihuela 03312, Spain
[3] Univ Nacl UNS, Dept Agron, San Andres 800, RA-8000 Buenos Aires, Argentina
[4] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[5] Planet Labs Germany GmbH, Kurfurstendamm 22, D-10719 Berlin, Germany
关键词
remote sensing; satellite; UAV; organo-mineral fertilization; extensive crops; vegetation monitoring; phenology; yield prediction; LEAF-AREA INDEX; GROWING DEGREE-DAYS; VEGETATION INDEX; NORTH CHINA; CROP YIELD; RED; TILLAGE; EVENTS; GROWTH; TOOL;
D O I
10.3390/rs16234474
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Cereal crops play a critical role in global food security, but their productivity is increasingly threatened by climate change. This study evaluates the feasibility of using PlanetScope satellite imagery and a UAV equipped with the MicaSense RedEdge multispectral imaging sensor in monitoring winter wheat under various fertilizer treatments in a Mediterranean climate. Eleven fertilizer treatments, including organic-mineral fertilizer (OMF) pellets, were tested. The results show that conventional inorganic fertilization provided the highest yield (8618 kg ha(-)1), while yields from OMF showed a comparable performance to traditional fertilizers, indicating their potential for sustainable agriculture. PlanetScope data demonstrated moderate accuracy in predicting canopy cover (R2 = 0.68), crop yield (R2 = 0.54), and grain quality parameters such as protein content (R2 = 0.49), starch (R2 = 0.56), and hectoliter weight (R2 = 0.51). However, its coarser resolution limited its ability to capture finer treatment-induced variability. MicaSense, despite its higher spatial resolution, performed poorly in predicting crop components, with R2 values below 0.35 for yield and protein content. This study highlights the complementary use of remote sensing technologies to optimize wheat management and support climate-resilient agriculture through the integration of sustainable fertilization strategies.
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页数:23
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