Availability of practical and reliable methods for monitoring prac-tice of tillage will reduce uncertainty in ecosystem models and permit identi ?cation of areas at risk for soil erosion and nutrient losses.Re-mote sensing is an ef ?cient and cost-effective way to obtain informa-tion concerning CRC/tillage practices.Mapping tillage practices using single-date images could be problematic unless the area has very nar-row window of planting dates.Watts et al.(2011)showed that incor-porating high temporal datasets can improve mapping accuracy of conservation tillage.Our study supports the ?ndings by Watts et al.(2011)that temporal resolution plays a signi ?cant role in mapping CRC/tillage practices accurately.Multi-temporal analyses (minNDTI and PC methods)are able to classify tillage categories and predict CRC along a continuum more accurately.Time-series of Landsat imag-ery have the potential to map CRC at broad scales and ?ll the tempo-ral data gaps in the observation of tillage practices.The Landsat Data Continuity Mission (LDCM)will provide the opportunity for continu-ously mapping the Earth's continental surface.The Hyperspectral In-frared Imager (HyspIRI)mission will provide another opportunity for mapping crop residue with the global coverage and 60meter spa-tial resolution.However,a 19-day revisit time of HyspIRI may not be short enough to provide two to three cloud-free images during plant-ing season.Future remote sensing platforms should consider im-provement of temporal resolution for crop residue detection.
Table 4
Error matrix for three residue cover classes using simple linear regression for all dataset.
Classi ?cation data
Reference data CRC b 30%
30%b CRC b 70%CRC >70%Total User accuracy CRC b 30%
190019100%30%b CRC b 70%31321872%CRC >70%01252696%
Total
22142763
Producer's accuracy
86%
93%
93%
Overall accuracy:90%;Kappa coef ?cient:85%.Bold data are the number of pixels correctly assigned to each class.
C R C %
Percentage Change %
Fig.8.The correlation between crop residue cover (CRC)and percentage change (PC)of NDTI (n =63).Green dots:correctly classi ?ed as CRC >70%(PC b 40%);blue dots:correctly classi ?ed as 30%b CRC b 70%(40%b PC b 70%);orange dots:correctly classi ?ed as CRC b 30%(PC >70%);red dots:misclassi ?cation.(For interpretation of the refer-ences to color in this ?gure legend,the reader is referred to the web version of this article.)
Table 5
Error matrix for three residue cover classes using the percentage change method.Classi ?cation data
Reference data CRC b 30%
30%b CRC b 70%CRC >70%Total User accuracy CRC b 30%
210021100%30%b CRC b 70%11231675%CRC >70%02242692%
Total
22142763
Producer's accuracy
95%
86%
89%
Overall accuracy:90%;Kappa coef ?cient:85%.Bold data are the number of pixels correctly assigned to each class.
Table 6
Summary of Landsat 5TM and 7ETM+scenes available for Central Indiana.Year Image acquisition date
Total images ξ201030-Mar ?,15-Apr ?,9-May,25-May,10-Jun 520094-Apr,12-Apr ?,22-May,23-Jun 4200730-Mar,15-Apr,1-May,2-Jun
420064-Apr ?,28-Apr,6-May ?,22-May ?,30-May 5200524-Mar,9-Apr,25-Apr,11-May,27-May 5200414-Apr ?,8-May,1-Jun ?,
3200312-Apr ?,28-Apr ?,6-May,22-May,23-Jun 5200225-Apr ?,3-May,20-Jun
3200121-Mar ?,14-Apr,30-Apr,8-May ?,9-Jun ?,17-Jun 6200026-Mar,27-Apr,13-May,29-May,6-Jun ?51999
24-Mar,25-Apr,11-May,27-May
4
*Images from Landsat 7ETM+archive.ξ
Total:total number of images;the average cloud cover of all the images is 7.43%.
182 B.Zheng et al./Remote Sensing of Environment 117(2012)177–183
Acknowledgements
This project was funded by the Graduate Research Development Program(GRDP)at Virginia Tech and Virginia Tech Geography Department's Sidman P.Poole Scholarship.The authors would like to thank the remote sensing team from IUPUI and Kai Wang for assist-ing data collection.
References
Agresti,A.(1996).An introduction to categorical data analysis.New York,N.Y.:Wiley. Baker,N.T.(2011).Tillage practices in the Conterminous United States,1989–2004-datasets aggregated by watershed.United State Geological Survey Data Series,573.(pp.13). Biard,F.,&Baret,F.(1997).Crop residue estimation using multiband re?ectance.Remote Sensing of Environment,59,530–536.
CTIC(2010).National survey of conservation tillage practices.West Lafayette,IN: Conservation Technology Information Center Retrieved February,2010,from.
58bd8d2b482fb4daa58d4bea/pdf/TillageDe?nitions.pdf. Daughtry,C.S.T.(2001).Discriminating crop residues from soil by shortwave infrared re?ectance.Agronomy Journal,93,125–131.
Daughtry,C.S.T.,Doraiswamy,P.C.,Hunt,E.R.,Jr.,Stern,A.J.,McMurtrey,J.E.,III,& Prueger,J.H.(2006).Remote sensing of crop residue cover and soil tillage intensity.
Soil and Tillage Research,91,101–108.
Daughtry,C.S.T.,&Hunt,E.R.,Jr.(2008).Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover.Remote Sensing of Environment,112(4),1647–1657.
Daughtry,C.S.T.,Hunt,E.R.,Jr.,Doraiswamy,P.C.,&McMurtrey,J.E.,III(2005).Remote sensing the spatial distribution of crop residues.Agronomy Journal,97,864–871. Daughtry,C.S.T.,McMurtrey,J.E.,III,Chappelle,E.W.,Dulaney,W.P.,Irons,J.R.,& Satterwhite,M.B.(1995).Potential for discriminating crop residues from soil by re?ectance and?uorescence.Agronomy Journal,87,165–171.
Foody,G.M.(2004).Thematic map comparison:Evaluating the statistical signi?cance of differences in classi?cation accuracy.Photogrammetric Engineering and Remote Sensing,70,627–633.
Gausman,H.W.,Gerbermann,A.H.,Wiegand,C.L.,Leamer,R.W.,Rodriguez,R.R.,& Noriega,J.R.(1975).Re?ectance differences between crop residues and bare soils.Soil Science Society of America Journal,39,752–755.
Gowda,P.H.,Dalzell,B.J.,Mulla,D.J.,&Kollman,F.(2001).Mapping tillage practices with landstat thematic mapper based logistic regression models.Journal of Soil and Water Conservation,56,91–96.
Gowda,P.H.,Mulla,D.J.,&Dalzell,B.J.(2003).Examining the targeting of conservation tillage practices to steep vs.?at landscapes in the Minnesota River Basin.Journal of Soil and Water Conservation,58,53–57.
Indiana Crop and Weather Report(2010).USDA National Agricultural Statistics Service.
West Lafayette,60.Retrieved September,2011,from.58bd8d2b482fb4daa58d4bea/ Statistics_by_State/Indiana/Publications/Crop_Progress_&_Condition/2010/index10.asp. Jarecki,M.K.,Lal,R.,&James,R.(2005).Crop management effects on soil carbon sequestration on selected farmers'?elds in northeastern Ohio.Soil and Tillage Research,81,265–276.Masek,J.G.,Vermote,E.F.,Saleous,N.E.,Wolfe,R.,Hall,F.G.,Huemmrich,K.F.,et al.
(2006).A Landsat surface re?ectance dataset for North America,1990–2000.IEEE Geoscience and Remote Sensing Letters,3,68–72.
McNairn,H.,&Protz,R.(1993).Mapping corn residue cover on agricultural?elds in Oxford County,Ontario,using Thematic Mapper.Canadian Journal of Remote Sensing, 19,152–159.
Morrison,J.E.,Huang,C.-H.,Lightle,D.T.,&Daughtry,C.S.T.(1993).Residue measure-ment techniques.Journal of Soil and Water Conservation,48,478–483.
NASA(2011).ASTER user advisory.Retrieved January,2011,from.asterweb.jpl.
58bd8d2b482fb4daa58d4bea/latest.asp.
NRCS(1992).Farming with crop residue brochure.Retrieved March15,2010,from.
58bd8d2b482fb4daa58d4bea/news/publications/brochures/farmcropres/
FarmCropRes-broc.
Roy,D.P.,Ju,J.,Kline,K.,Scaramuzza,P.L.,Kovalskyy,V.,Hansen,M.,et al.(2010).
Web-enabled Landsat Data(WELD):Landsat ETM+composited mosaics of the conterminous United States.Remote Sensing of Environment,114,35–49. Saseendran,S.A.,Ma,L.,Malone,R.,Heilman,P.,Ahuja,L.R.,Kanwar,R.S.,et al.(2007).
Simulating management effects on crop production,tile drainage,and water qual-ity using RZWQM-DSSAT.Geoderma,140,297–309.
Serbin,G.,Daughtry,C.S.T.,Hunt,E.R.,Jr.,Brown,D.J.,&McCarty,G.W.(2009).Effect of soil spectral properties on remote sensing of crop residue cover.Soil Science Society of America Journal,73,1545–1558.
