22.1.1.2 Classification for Crops, Specific Crops

Chapter Contents (Back)
Classification. Crop Classification. Remote Sensing. Agricultural. See also Classification for Urban Area Land Cover, Remote Sensing.

Haralick, R.M.[Robert M.], Caspall, F., and Simonett, D.S.,
Using Radar Imagery for Crop Discrimination: A Statistical and Conditional Probability Study,
RSE(1), 1970, pp. 131-142. BibRef 7000

Haralick, R.M.[Robert M.], Hlavka, C.A., Carlyle, S.M., and Yokoyama, R.,
The Discrimination of Winter Wheat Using a Growth-State Signature,
RSE(9), 1980, pp. 277-294. BibRef 8000

Badhwar, G.D., Austin, W.W., Carnes, J.G.,
A semi-automatic technique for multitemporal classification of a given crop within a landsat scene,
PR(15), No. 3, 1982, pp. 217-230.
WWW Version. 0309
BibRef

Davis, L.S., Wang, C.Y., Xie, H.C.,
An Experiment in Multispectral, Multitemporal Crop Classification Using Relaxation Techniques,
CVGIP(23), No. 2, August 1983, pp. 227-235.
WWW Version. BibRef 8308

Macleod, R.D., Congalton, R.G.,
Quantitative Comparison of Change-Detection Algorithms for Monitoring Eelgrass from Remotely-Sensed Data,
PhEngRS(64), No. 3, March 1998, pp. 207-216. 9803
BibRef

Sun, W.X.[Wan-Xiao], Heidt, V., Gong, P.[Peng], Xu, G.[Gang],
Information fusion for rural land-use classification with high-resolution satellite imagery,
GeoRS(41), No. 4, April 2003, pp. 883-890.
IEEE Abstract. 0307
BibRef

Aplin, P.[Paul], Atkinson, P.M.[Peter M.],
Predicting Missing Field Boundaries to Increase Per-Field Classification Accuracy,
PhEngRS(70), No. 1, January 2004, pp. 141-150.
WWW Version. 0403
Missing field boundaries were predicted by comparing the within-field modal land-cover proportion and local variance to increase the accuracy of per-field classification. See also Super-resolution target identification from remotely sensed images using a Hopfield neural network. BibRef

Pearlstine, L.[Leonard], Portier, K.M.[Kenneth M.], Smith, S.E.[Scot E.],
Textural Discrimination of an Invasive Plant, Schinus terebinthifolius, from Low Altitude Aerial Digital Imagery,
PhEngRS(71), No. 3, March 2005, pp. 289-298.
WWW Version. 0509
Texture features derived from first and second order statistics and edge components in high-resolution digital color infrared images were tested for their ability to discriminate Schinus terebinthifolius in multiple linear logistic regressions. BibRef

Lathrop, R.G.[Richard G.], Montesano, P.[Paul], Haag, S.[Scott],
A Multi-scale Segmentation Approach to Mapping Seagrass Habitats Using Airborne Digital Camera Imagery,
PhEngRS(72), No. 6, June 2006, pp. 665-676.
WWW Version. 0610
BibRef

Somers, B.[Ben], Delalieux, S.[Stephanie], Verstraeten, W.W.[Willem W.], Coppin, P.[Pol],
A Conceptual Framework for the Simultaneous Extraction of Sub-pixel Spatial Extent and Spectral Characteristics of Crops,
PhEngRS(75), No. 1, January 2009, pp. 57-68.
WWW Version. 0902
BibRef

Lucas, R.[Richard], Rowlands, A.[Aled], Brown, A.[Alan], Keyworth, S.[Steve], Bunting, P.[Peter],
Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping,
PandRS(62), No. 3, August 2007, pp. 165-185.
WWW Version. 0709
Time-series imagery; Landsat; Segmentation; Decision rules; Fuzzy membership BibRef

Yang, P., Shibasaki, R., Wu, W., Zhou, Q., Chen, Z., Zha, Y., Shi, Y., Tang, H.,
Evaluation of MODIS Land Cover and LAI Products in Cropland of North China Plain Using In Situ Measurements and Landsat TM Images,
GeoRS(45), No. 10, October 2007, pp. 3087-3097.
IEEE DOI Link 0711
BibRef

Karjalainen, M.[Mika], Kaartinen, H.[Harri], Hyyppä, J.[Juha],
Agricultural Monitoring Using Envisat Alternating Polarization SAR Images,
PhEngRS(74), No. 1, January 2008, pp. 117-128
WWW Version. 0803
Satellite images will improve yield estimation in the future because they can provide objective information about crop growth over large areas; in this context SAR images are extremely useful due to their high revisit imaging capability. BibRef

Aguera, F.[Francisco], Aguilar, F.J.[Fernando J.], Aguilar, M.A.[Manuel A.],
Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses,
PandRS(63), No. 6, November 2008, pp. 635-646.
WWW Version. 0811
QuickBird; IKONOS; Texture; Land use BibRef

Carvajal, F., Crisanto, E., Aguilar, F.J., Aguera, F., Aguilar, M.A.,
Greenhouses Detection Using an Artificial Neural Network with a Very High Resolution Satellite Image,
IfromI06(xx-yy).
PDF Version. 0607
BibRef

Aguilar, M.A.[Manuel A.], Aguilar, F.J.[Fernando J.], Agüera, F.[Francisco],
Assessing Geometric Reliability of Corrected Images from Very High Resolution Satellites,
PhEngRS(74), No. 12, December 2008, pp. 1551-1560.
WWW Version. 0804
Validation of two theoretical models for estimating the reliability of geometric accuracies measured as Root Mean Square Error over corrected single images from QuickBird and Ikonos imagery. BibRef

Johnson, D.M.[David M.],
A Comparison of Coincident Landsat-5 TM and Resourcesat-1 AWiFS Imagery for Classifying Croplands,
PhEngRS(74), No. 11, November 2008, pp. 1413-1424.
WWW Version. 0804
Testing the suitability of AWiFS imagery with TM as a benchmark for deriving row crop focused cover type maps over highly cultivated regions of the central U.S. BibRef

Silva, W.F.[Wagner F.], Rudorff, B.F.T.[Bernardo F.T.], Formaggio, A.R.[Antonio R.], Paradella, W.R.[Waldir R.], Mura, J.C.[Jose C.],
Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data,
PandRS(64), No. 5, September 2009, pp. 458-463.
Elsevier DOI Link
WWW Version. 0910
Remote sensing; Classification; Multi-polarization; Contextual classifier; Image classification BibRef

Formaggio, A.R.[Antonio R.], Vieira, M.A., Rennó, C.D., Aguiar, D.A., Mello, M.P.,
Object-Based Image Analysis and Data Mining for Mapping Sugarcane with Landsat Imagery in Brazil,
GEOBIA10(xx-yy).
PDF Version. 1007
BibRef

Leite, P.B.C.[Paula Beatriz Cerqueira], Feitosa, R.Q.[Raul Queiroz], Formaggio, A.R.[Antonio Roberto], da Costa, G.A.O.P.[Gilson Alexandre Ostwald Pedro], Pakzad, K.[Kian], Sanches, I.D.[Ieda Del'Arco],
Hidden Markov Models for crop recognition in remote sensing image sequences,
PRL(31), No. 1, January 2010, pp. 19-26.
Elsevier DOI Link
WWW Version. 1011
Hidden Markov Models; Crop recognition; Remote sensing BibRef

Velpuri, N.M., Thenkabail, P.S., Gumma, M.K., Biradar, C., Dheeravath, V., Noojipady, P., Yuanjie, L.,
Influence of Resolution in Irrigated Area Mapping and Area Estimation,
PhEngRS(75), No. 12, December 2009, pp. 1383-1396.
WWW Version. 1001
A comparison of irrigated areas derived from four different spatial resolutions is performed to ascertain the influence of resolution on irrigated area mapping and area estimation. BibRef

Zheng, L.Y.[Li-Ying], Shi, D.M.[Da-Ming], Zhang, J.T.[Jing-Tao],
Segmentation of green vegetation of crop canopy images based on mean shift and Fisher linear discriminant,
PRL(31), No. 9, 1 July 2010, pp. 920-925.
Elsevier DOI Link
WWW Version. 1004
Mean shift; Fisher linear discriminant; Point-line distance; Crop image; Segmentation BibRef

Potgieter, A.B., Apan, A., Hammer, G., Dunn, P.,
Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery,
PandRS(65), No. 4, July 2010, pp. 380-387.
Elsevier DOI Link
WWW Version. 1003
Early-season; Crop area estimates; Simple metric; Multi-temporal; Shire-scale BibRef

Yang, D., Yang, Y., Yang, C., Zhao, J., Sun, Z.,
Detection of seagrass in optical shallow water with quickbird in the Xincun Bay, Hainan province, China,
IET-IPR(5), No. 5, 2011, pp. 363-368.
WWW Version. 1108
BibRef

Song, S.[Shalei], Gong, W.[Wei], Zhu, B.[Bo], Huang, X.[Xin],
Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance,
PandRS(66), No. 5, September 2011, pp. 672-682.
Elsevier DOI Link
WWW Version. 1110
Hyperspectral data; Wavelength selection; Spectral discrimination; Rice BibRef

Sakamoto, T.[Toshihiro], Shibayama, M.[Michio], Kimura, A.[Akihiko], Takada, E.[Eiji],
Assessment of digital camera-derived vegetation indices in quantitative monitoring of seasonal rice growth,
PandRS(66), No. 6, November 2011, pp. 872-882.
Elsevier DOI Link
WWW Version. 1112
Crop phenology; Active sensing; Flashlight BibRef

Burgin, M., Clewley, D., Lucas, R.M., Moghaddam, M.,
A Generalized Radar Backscattering Model Based on Wave Theory for Multilayer Multispecies Vegetation,
GeoRS(49), No. 12, December 2011, pp. 4832-4845.
IEEE DOI Link 1201
BibRef

Biliouris, D., van der Zande, D., Verstraeten, W., Stuckens, J., Muys, B., Dutré, P., Coppin, P.,
RPV Model Parameters Based on Hyperspectral Bidirectional Reflectance Measurements of Fagus sylvatica L. Leaves.,
RS(1), No. 2, June 2009, pp. 92-106.
WWW Version.
WWW Version. 1203
BibRef

Lyons, M., Phinn, S., Roelfsema, C.,
Integrating Quickbird Multi-Spectral Satellite and Field Data: Mapping Bathymetry, Seagrass Cover, Seagrass Species and Change in Moreton Bay, Australia in 2004 and 2007,
RS(3), No. 1, January 2011, pp. 42-64.
WWW Version.
WWW Version. 1203
BibRef

Laurila, H., Karjalainen, M., Kleemola, J., Hyyppä, J.,
Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing,
RS(2), No. 9, September 2010, pp. 2185-2239.
WWW Version.
WWW Version. 1203
BibRef

Laurila, H., Karjalainen, M., Hyyppä, J., Kleemola, J.,
Integrating Vegetation Indices Models and Phenological Classification with Composite SAR and Optical Data for Cereal Yield Estimation in Finland (Part I),
RS(2), No. 1, January 2010, pp. 76-114.
WWW Version.
WWW Version. 1203
BibRef

Pittman, K., Hansen, M., Becker-Reshef, I., Potapov, P., Justice, C.,
Estimating Global Cropland Extent with Multi-year MODIS Data,
RS(2), No. 7, July 2010, pp. 1844-1863.
WWW Version.
WWW Version. 1203
BibRef

Hunt, E., Hively, W., Fujikawa, S., Linden, D., Daughtry, C., McCarty, G.,
Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring,
RS(2), No. 1, January 2010, pp. 290-305.
WWW Version.
WWW Version. 1203
BibRef

Serbin, G., Hunt, E., Daughtry, C., McCarty, G., Doraiswamy, P.,
An Improved ASTER Index for Remote Sensing of Crop Residue,
RS(1), No. 4, December 2009, pp. 971-991.
WWW Version.
WWW Version. 1203
BibRef

Panda, S., Ames, D., Panigrahi, S.,
Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques,
RS(2), No. 3, March 2010, pp. 673-696.
WWW Version.
WWW Version. 1203
BibRef

Conrad, C., Fritsch, S., Zeidler, J., Rücker, G., Dech, S.,
Per-Field Irrigated Crop Classification in Arid Central Asia Using SPOT and ASTER Data,
RS(2), No. 4, April 2010, pp. 1035-1056.
WWW Version.
WWW Version. 1203
BibRef

Rudorff, B., Aguiar, D., Silva, W., Sugawara, L., Adami, M., Moreira, M.,
Studies on the Rapid Expansion of Sugarcane for Ethanol Production in São Paulo State (Brazil) Using Landsat Data,
RS(2), No. 4, April 2010, pp. 1057-1076.
WWW Version.
WWW Version. 1203
BibRef

Becker-Reshef, I., Justice, C., Sullivan, M., Vermote, E., Tucker, C., Anyamba, A., Small, J., Pak, E.[Ed], Masuoka, E.[Ed], Schmaltz, J., Hansen, M., Pittman, K., Birkett, C., Williams, D., Reynolds, C., Doorn, B.,
Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project,
RS(2), No. 6, June 2010, pp. 1589-1609.
WWW Version.
WWW Version. 1203
BibRef

Martinez, B., Cassiraga, E., Camacho, F., Garcia-Haro, J.,
Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment,
RS(2), No. 11, November 2010, pp. 2584-2606.
WWW Version.
WWW Version. 1203
BibRef

Olsson, A., van Leeuwen, W., Marsh, S.,
Feasibility of Invasive Grass Detection in a Desertscrub Community Using Hyperspectral Field Measurements and Landsat TM Imagery,
RS(3), No. 10, October 2011, pp. 2283-2304.
WWW Version.
WWW Version. 1203
BibRef

Fletcher, R., Everitt, J., Elder, H.,
Evaluating Airborne Multispectral Digital Video to Differentiate Giant Salvinia from Other Features in Northeast Texas,
RS(2), No. 10, October 2010, pp. 2413-2423.
WWW Version.
WWW Version. 1203
BibRef

Jones, D., Pike, S., Thomas, M., Murphy, D.,
Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK),
RS(3), No. 2, February 2011, pp. 319-342.
WWW Version.
WWW Version. 1203
BibRef

Aguiar, D., Rudorff, B., Silva, W., Adami, M., Mello, M.,
Remote Sensing Images in Support of Environmental Protocol: Monitoring the Sugarcane Harvest in São Paulo State, Brazil,
RS(3), No. 12, December 2011, pp. 2682-2703.
WWW Version.
WWW Version. 1203
BibRef

Ramoelo, A.[Abel], Skidmore, A.K.[Andrew K.], Schlerf, M.[Martin], Mathieu, R.[Renaud], Heitkonig, I.M.A.[Ignas M.A.],
Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations,
PandRS(66), No. 4, July 2011, pp. 408-417.
Elsevier DOI Link
WWW Version. 1107
Nitrogen concentration; Phosphorus concentration; Water removal; Continuum removal; Bootstrapping BibRef

Darvishzadeh, R.[Roshanak], Atzberger, C.[Clement], Skidmore, A.[Andrew], Schlerf, M.[Martin],
Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models,
PandRS(66), No. 6, November 2011, pp. 894-906.
Elsevier DOI Link
WWW Version. 1112
Mediterranean grassland; Mapping LAI; Hyperspectral; Modeling; Partial least square regression; Vegetation indices BibRef

Borzuchowski, J., Schulz, K.,
Retrieval of Leaf Area Index (LAI) and Soil Water Content (WC) Using Hyperspectral Remote Sensing under Controlled Glass House Conditions for Spring Barley and Sugar Beet,
RS(2), No. 7, July 2010, pp. 1702-1721.
WWW Version.
WWW Version. 1203
BibRef

Wu, J.D.[Jin-Dong], Bauer, M.E.[Marvin E.],
Estimating Net Primary Production of Turfgrass in an Urban-Suburban Landscape with QuickBird Imagery,
RS(4), No. 4, April 2012, pp. 849-866.
WWW Version.
WWW Version. 1202
BibRef


da Silva, W.L., Goncalves, R.R.V., Siqueira, A.S., Zullo, J., Gomes Neto, F.A.M.,
Feature extraction for NDVI AVHRR/NOAA time series classification,
MultiTemp11(233-236).
IEEE DOI Link 1109
Crop forecasts. BibRef

D'Andrimont, R.[Raphael], Duveiller, G.[Gregory], Defourny, P.[Pierre],
Exploring the capacity to grasp multi-annual seasonal variability of winter wheat in Continental Climates with MODIS,
MultiTemp11(221-224).
IEEE DOI Link 1109
BibRef

Zorer, R.[Roberto], Rocchini, D.[Duccio], Delucchi, L.[Luca], Zottele, F.[Fabio], Meggio, F.[Franco], Neteler, M.[Markus],
Use of multi-annual MODIS Land Surface Temperature data for the characterization of the heat requirements for grapevine varieties,
MultiTemp11(225-228).
IEEE DOI Link 1109
BibRef

Goncalves, R.R.V., Zullo, J., Ferraresso, C.S., Sousa, E.P.M., Romani, L.A.S., Traina, A.J.M.,
Analysis of NOAA/AVHRR multitemporal images, climate conditions and cultivated land of sugarcane fields applied to agricultural monitoring,
MultiTemp11(229-232).
IEEE DOI Link 1109
BibRef

Romani, L.A.S., Goncalves, R.R.V., Amaral, B.F., Chino, D.Y.T., Zullo, J., Traina, C., Sousa, E.P.M., Traina, A.J.M.,
Clustering analysis applied to NDVI/NOAA multitemporal images to improve the monitoring process of sugarcane crops,
MultiTemp11(33-36).
IEEE DOI Link 1109
BibRef

Duveiller, G.[Gregory], Baret, F.[Frederic], Defourny, P.[Pierre],
Monitoring crop growth inter-annual variability from MODIS time series: Performance comparison between crop specific green area index and current global leaf area index products,
MultiTemp11(21-24).
IEEE DOI Link 1109
BibRef

Vancutsem, C., Pekel, J.F., Kayitakire, F.,
Dynamic mapping of cropland areas in Sub-Saharan Africa using MODIS time series,
MultiTemp11(25-28).
IEEE DOI Link 1109
BibRef

Hoberg, T.[Thorsten], Rottensteiner, F.[Franz], Heipke, C.[Christian],
Classification of multitemporal remote sensing data of different resolution using Conditional Random Fields,
CVRSE11(235-242).
IEEE DOI Link 1201
BibRef

Hoberg, T., Müller, S.,
Multitemporal Crop Type Classification using Conditional Random Fields and RapidEye Data,
HighRes11(xx-yy).
PDF Version. 1106
BibRef

Ok, A.O.[A. Ozdarici], Akyurek, Z., Clinton, N.,
Automatic Training Site Selection of Agricultural Crop Classification: A Case Study on Karacabey Plain, Turkey,
HighRes11(xx-yy).
PDF Version. 1106
BibRef

Recio, J.A., Helmholz, P., Müller, S.,
Potential Evaluation of Different Types Of Images and Their Combination for the Classification of GIS Objects Cropland and Grassland,
HighRes11(xx-yy).
PDF Version. 1106
BibRef

Chmiel, J., Fijakowska, A.,
Thematic Accuracy Assessment for Object Based Classification in Agriculture Areas: Comparative Analysis of Selected Approaches,
GEOBIA10(xx-yy).
PDF Version. 1007
BibRef

Jones, G., Gee, C., Villette, S., Truchetet, F.,
Validation of a virtual agronomic image modelling,
IPTA10(517-520).
IEEE DOI Link 1007
Detailed crop analysis. BibRef

Farzaneh, A.[Ali],
Cadastral mapping of Agricultural lands and Natural Resources by using image and non-image data,
CGC10(10).
PDF Version. 1006
BibRef

Aguilar, M., Pozo, J.L., Aguilar, F.J., Gracia, A.M., Fernandez, I., Sanchez-Hermosilla, J., Negreiros, J.,
Application Of Close-range Photogrammetry And Digital Photography Analysis For The Estimation Of Leaf Area Index In A Greenhouse Tomato Culture,
CloseRange10(xx-yy).
PDF Version. 1006
BibRef

Lohmann, P.[Peter], Soergel, U., Tavakkoli, M., Farghaly, D.,
Multi-temporal Classification for Crop Discrimination using TerraSAR-X Spotlight images,
HighRes09(xx-yy).
PDF Version. 0906
BibRef

Helmholz, P., Rottensteiner, F.,
Automatic Verification of Agricultural Areas using IKONOS Satellite Images,
HighRes09(xx-yy).
PDF Version. 0906
BibRef

Helmholz, P., Gerke, M., Heipke, C.,
Automatic Discrimination of Farmland Types Using IKONOS Imagery,
PIA07(81).
PDF Version. 0711
BibRef

Carvalho, F.A., Lacerda, M.P.C.,
Monitoring Environmental Impact of Land Use: Evaluating an Agricultural Area of Distrito Federal, Brazil,
IfromI06(xx-yy).
PDF Version. 0607
BibRef

Alves, H.M.R., Vieira, T.G.C., Souza, V.C.O., Bertoldo, M.A., Lacerda, M.P.C., Andrade, H., Bernardes, N.,
Monitoring the Relationships between Environment and Coffee Production in Agroecosytems of the State of Minas Gerais in Brazil,
IfromI06(xx-yy).
PDF Version. 0607
BibRef

Fisette, T., Chenier, R., Maloley, M., Gasser, P., Huffman, T., White, L., Ogston, R., Elgarawany, A.,
Methodology for a Canadian agricultural land cover classification,
OBIA06(xx-yy).
PDF Version. 0607
BibRef

Ozdarici, A., Turker, M.,
Field-based classification of agricultural crops using multi-scale images,
OBIA06(xx-yy).
PDF Version. 0607
BibRef

Turker, M., Kok, E.H.,
Developing an integrated system for the extraction of sub-fields within agricultural parcels from remote sensing images,
OBIA06(xx-yy).
PDF Version. 0607
BibRef

Guzman-Arenas, A., Seco, R.M.[Rosa Ma], and Sanchez, V.G.[Victor G.],
Computer Analysis of Images for Crop Identification in Mexico,
TRIIMAS, Vol. 7, no. 135, 1976, UNAM. Crop i-d - wheat/cotton in NW Mexico; standard classification techniques; spectral signature and set of heuristic functions that the user defines. BibRef 7600

Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
Land Cover Change Analysis, Temporal Analysis .


Last update:May 16, 2012 at 20:31:07