U. Avdan, Gordana Kaplan, Zehra Yiğit Avdan, Dilek Küçük Matcı, F. Erdem, Ece Tuğba Mızık, Ilknur Demirtas
{"title":"PlanetScope遥感土壤电导率与地面实测数据在小麦和甜菜产量中的比较","authors":"U. Avdan, Gordana Kaplan, Zehra Yiğit Avdan, Dilek Küçük Matcı, F. Erdem, Ece Tuğba Mızık, Ilknur Demirtas","doi":"10.3390/iecag2021-09741","DOIUrl":null,"url":null,"abstract":"Soil salinity is a major threat to the continuity of sustainable agriculture and food provision and the soil structure deterioration. In this context, determining, reducing and managing soil salinity is very important for creating sustainable modern agriculture. Determining soil salinity is generally carried out in the laboratory environment and devices used in land plots. Remote sensing is one of the important methods used for precise estimation and mapping of salinity. With remote sensing technology, soil salinity maps for large areas can be obtained with low cost and low effort. This study aims to compare remote sensing soil electrical conductivity from PlanetScope and ground measured data in wheat and beet fields in the farming areas of Alpu, Turkey. For that reason, electrical conductivity was measured at several points in wheat and beet fields using in-situ measurements and compared with various soil salinity indices from PlanetScope imagery acquired on the same day. Linear regression analysis was carried out to correlate the electrical conductivity data with their corresponding soil salinity spectral index values. The results show a high correlation (R2 = 0.84) between soil salinity in wheat fields and some of the used indices. This study strengthens the idea that soil salinity maps can be obtained fast and accurately for large areas using remote sensing technology.","PeriodicalId":400770,"journal":{"name":"Biology and Life Sciences Forum","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Comparison of Remote Sensing Soil Electrical Conductivity from PlanetScope and Ground Measured Data in Wheat and Beet Yields\",\"authors\":\"U. Avdan, Gordana Kaplan, Zehra Yiğit Avdan, Dilek Küçük Matcı, F. Erdem, Ece Tuğba Mızık, Ilknur Demirtas\",\"doi\":\"10.3390/iecag2021-09741\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Soil salinity is a major threat to the continuity of sustainable agriculture and food provision and the soil structure deterioration. In this context, determining, reducing and managing soil salinity is very important for creating sustainable modern agriculture. Determining soil salinity is generally carried out in the laboratory environment and devices used in land plots. Remote sensing is one of the important methods used for precise estimation and mapping of salinity. With remote sensing technology, soil salinity maps for large areas can be obtained with low cost and low effort. This study aims to compare remote sensing soil electrical conductivity from PlanetScope and ground measured data in wheat and beet fields in the farming areas of Alpu, Turkey. For that reason, electrical conductivity was measured at several points in wheat and beet fields using in-situ measurements and compared with various soil salinity indices from PlanetScope imagery acquired on the same day. Linear regression analysis was carried out to correlate the electrical conductivity data with their corresponding soil salinity spectral index values. The results show a high correlation (R2 = 0.84) between soil salinity in wheat fields and some of the used indices. This study strengthens the idea that soil salinity maps can be obtained fast and accurately for large areas using remote sensing technology.\",\"PeriodicalId\":400770,\"journal\":{\"name\":\"Biology and Life Sciences Forum\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biology and Life Sciences Forum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/iecag2021-09741\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biology and Life Sciences Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/iecag2021-09741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Remote Sensing Soil Electrical Conductivity from PlanetScope and Ground Measured Data in Wheat and Beet Yields
Soil salinity is a major threat to the continuity of sustainable agriculture and food provision and the soil structure deterioration. In this context, determining, reducing and managing soil salinity is very important for creating sustainable modern agriculture. Determining soil salinity is generally carried out in the laboratory environment and devices used in land plots. Remote sensing is one of the important methods used for precise estimation and mapping of salinity. With remote sensing technology, soil salinity maps for large areas can be obtained with low cost and low effort. This study aims to compare remote sensing soil electrical conductivity from PlanetScope and ground measured data in wheat and beet fields in the farming areas of Alpu, Turkey. For that reason, electrical conductivity was measured at several points in wheat and beet fields using in-situ measurements and compared with various soil salinity indices from PlanetScope imagery acquired on the same day. Linear regression analysis was carried out to correlate the electrical conductivity data with their corresponding soil salinity spectral index values. The results show a high correlation (R2 = 0.84) between soil salinity in wheat fields and some of the used indices. This study strengthens the idea that soil salinity maps can be obtained fast and accurately for large areas using remote sensing technology.