Barbosa, P.M.,
Casterad, M.A.,
Herrero, J.,
Performance of Several Landsat-5 Thematic Mapper (TM) Image Classification
Methods for Crop Extent Estimates in an Irrigation District,
JRS(17), No. 18, December 1996, pp. 3665-3674.
9701
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 Link.
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
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.
DOI Link
1203
BibRef
Ozdogan, M.,
Yang, Y.,
Allez, G.,
Cervantes, C.,
Remote Sensing of Irrigated Agriculture: Opportunities and Challenges,
RS(2), No. 9, September 2010, pp. 2274-2304.
DOI Link
1203
BibRef
Pervez, M.,
Brown, J.,
Mapping Irrigated Lands at 250-m Scale by Merging MODIS Data and
National Agricultural Statistics,
RS(2), No. 10, October 2010, pp. 2388-2412.
DOI Link
1203
BibRef
Jiménez-Bello, M.A.,
Ruiz, L.A.,
Hermosilla, T.,
Recio, J.A.,
Intrigliolo, D.S.,
Use of remote sensing and geographic information tools for
irrigation management of citrus trees,
Other2012, pp. 147-159.
In:
The use of remote sensing and geographic information systems for
irrigation amangement in Southwest Europe. CIHEAM.
PDF File.
BibRef
1200
Cuenca, R.H.[Richard H.],
Ciotti, S.P.[Shannon P.],
Edlinger, J.,
Conrad, C.,
Lamers, J.,
Khasankhanova, G.,
Koellner, T.,
Reconstructing the Spatio-Temporal Development of Irrigation Systems in
Uzbekistan Using Landsat Time Series,
RS(4), No. 12, December 2012, pp. 3972-3994.
DOI Link
1211
BibRef
Hagimoto, Y.[Yutaka],
Application of Landsat to Evaluate Effects of Irrigation Forbearance,
RS(5), No. 8, 2013, pp. 3776-3802.
DOI Link
1309
BibRef
Akdim, N.[Nadia],
Alfieri, S.M.[Silvia Maria],
Habib, A.[Adnane],
Choukri, A.[Abdeloihab],
Cheruiyot, E.[Elijah],
Labbassi, K.[Kamal],
Menenti, M.[Massimo],
Monitoring of Irrigation Schemes by Remote Sensing:
Phenology versus Retrieval of Biophysical Variables,
RS(6), No. 6, 2014, pp. 5815-5851.
DOI Link
1407
BibRef
Hagolle, O.[Olivier],
Tavernier, A.[Adrien],
Kharrou, M.H.[M. Hakim],
Er-Raki, S.[Salah],
Huc, M.[Mireille],
Kasbani, M.[Mohamed],
El Moutamanni, A.[Abdelilah],
Yousfi, M.[Mohamed],
Jarlan, L.[Lionel],
A Life-Size and Near Real-Time Test of Irrigation Scheduling with a
Sentinel-2 Like Time Series (SPOT4-Take5) in Morocco,
RS(6), No. 11, 2014, pp. 11182-11203.
DOI Link
1412
BibRef
Saadi, S.[Sameh],
Simonneaux, V.[Vincent],
Boulet, G.[Gilles],
Raimbault, B.[Bruno],
Mougenot, B.[Bernard],
Fanise, P.[Pascal],
Ayari, H.[Hassan],
Lili-Chabaane, Z.[Zohra],
Monitoring Irrigation Consumption Using High Resolution NDVI Image
Time Series: Calibration and Validation in the Kairouan Plain
(Tunisia),
RS(7), No. 10, 2015, pp. 13005.
DOI Link
1511
BibRef
Dubovyk, O.[Olena],
Menz, G.[Gunter],
Lee, A.[Alexander],
Schellberg, J.[Juergen],
Thonfeld, F.[Frank],
Khamzina, A.[Asia],
SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics:
A Case of Irrigated Croplands,
RS(7), No. 6, 2015, pp. 6763.
DOI Link
1507
BibRef
Jin, Q.J.[Qin-Jian],
Wei, J.F.[Jiang-Feng],
Yang, Z.L.[Zong-Liang],
Lin, P.R.[Pei-Rong],
Irrigation-Induced Environmental Changes around the Aral Sea:
An Integrated View from Multiple Satellite Observations,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link
1711
BibRef
Pun, M.[Mahesh],
Mutiibwa, D.[Denis],
Li, R.[Ruopu],
Land Use Classification: A Surface Energy Balance and Vegetation
Index Application to Map and Monitor Irrigated Lands,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link
1802
BibRef
Chance, E.W.[Eric W.],
Cobourn, K.M.[Kelly M.],
Thomas, V.A.[Valerie A.],
Dawson, B.C.[Blaine C.],
Flores, A.N.[Alejandro N.],
Identifying Irrigated Areas in the Snake River Plain, Idaho:
Evaluating Performance across Composting Algorithms, Spectral
Indices, and Sensors,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
And:
Erratum:
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Chance, E.W.[Eric W.],
Cobourn, K.M.[Kelly M.],
Thomas, V.A.[Valerie A.],
Trend Detection for the Extent of Irrigated Agriculture in Idaho's
Snake River Plain, 1984-2016,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link
1802
BibRef
Sharma, A.K.[Amit Kumar],
Hubert-Moy, L.[Laurance],
Buvaneshwari, S.[Sriramulu],
Sekhar, M.[Muddu],
Ruiz, L.[Laurent],
Bandyopadhyay, S.[Soumya],
Corgne, S.[Samuel],
Irrigation History Estimation Using Multitemporal Landsat Satellite
Images: Application to an Intensive Groundwater Irrigated
Agricultural Watershed in India,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Nhamo, L.[Luxon],
van Dijk, R.[Ruben],
Magidi, J.[James],
Wiberg, D.[David],
Tshikolomo, K.[Khathu],
Improving the Accuracy of Remotely Sensed Irrigated Areas Using
Post-Classification Enhancement Through UAV Capability,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Piedelobo, L.[Laura],
Ortega-Terol, D.[Damián],
del Pozo, S.[Susana],
Hernández-López, D.[David],
Ballesteros, R.[Rocío],
Moreno, M.A.[Miguel A.],
Molina, J.L.[José-Luis],
González-Aguilera, D.[Diego],
HidroMap: A New Tool for Irrigation Monitoring and Management Using
Free Satellite Imagery,
IJGI(7), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Gumma, M.,
Thenkabail, P.,
Hideto, F.,
Nelson, A.,
Dheeravath, V.,
Busia, D.,
Rala, A.,
Mapping Irrigated Areas of Ghana Using Fusion of 30m and 250m
Resolution Remote-Sensing Data,
RS(3), No. 4, April 2011, pp. 816-835.
DOI Link
1203
BibRef
Ferrant, S.[Sylvain],
Selles, A.[Adrien],
Le Page, M.[Michel],
Herrault, P.A.[Pierre-Alexis],
Pelletier, C.[Charlotte],
Al-Bitar, A.[Ahmad],
Mermoz, S.[Stéphane],
Gascoin, S.[Simon],
Bouvet, A.[Alexandre],
Saqalli, M.[Mehdi],
Dewandel, B.[Benoit],
Caballero, Y.[Yvan],
Ahmed, S.[Shakeel],
Maréchal, J.C.[Jean-Christophe],
Kerr, Y.[Yann],
Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to
Estimate Seasonal Groundwater Use in South India,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link
1712
BibRef
Gao, Q.[Qi],
Zribi, M.[Mehrez],
Escorihuela, M.J.[Maria Jose],
Baghdadi, N.[Nicolas],
Segui, P.Q.[Pere Quintana],
Irrigation Mapping Using Sentinel-1 Time Series at Field Scale,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Ghebreamlak, A.Z.[Araya Z.],
Tanakamaru, H.[Haruya],
Tada, A.[Akio],
Adam, B.M.A.[Bashir M. Ahmed],
Elamin, K.A.E.[Khalid A. E.],
Satellite-Based Mapping of Cultivated Area in Gash Delta Spate
Irrigation System, Sudan,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Akhtar, F.[Fazlullah],
Awan, U.K.[Usman Khalid],
Tischbein, B.[Bernhard],
Liaqat, U.W.[Umar Waqas],
Assessment of Irrigation Performance in Large River Basins under Data
Scarce Environment: A Case of Kabul River Basin, Afghanistan,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Blatchford, M.L.[Megan Leigh],
Karimi, P.[Poolad],
Bastiaanssen, W.G.M.,
Nouri, H.[Hamideh],
From Global Goals to Local Gains:
A Framework for Crop Water Productivity,
IJGI(7), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Kiptala, J.K.[Jeremiah K.],
Mul, M.[Marloes],
Mohamed, Y.[Yasir],
Bastiaanssen, W.G.M.[Wim G.M.],
van der Zaag, P.[Pieter],
Mapping Ecological Production and Benefits from Water Consumed in
Agricultural and Natural Landscapes: A Case Study of the Pangani
Basin,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Ragettli, S.[Silvan],
Herberz, T.[Timo],
Siegfried, T.[Tobias],
An Unsupervised Classification Algorithm for Multi-Temporal Irrigated
Area Mapping in Central Asia,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Bousbih, S.[Safa],
Zribi, M.[Mehrez],
El Hajj, M.[Mohammad],
Baghdadi, N.[Nicolas],
Lili-Chabaane, Z.[Zohra],
Gao, Q.[Qi],
Fanise, P.[Pascal],
Soil Moisture and Irrigation Mapping in A Semi-Arid Region, Based on
the Synergetic Use of Sentinel-1 and Sentinel-2 Data,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Xu, T.[Tianfang],
Deines, J.M.[Jillian M.],
Kendall, A.D.[Anthony D.],
Basso, B.[Bruno],
Hyndman, D.W.[David W.],
Addressing Challenges for Mapping Irrigated Fields in Subhumid
Temperate Regions by Integrating Remote Sensing and Hydroclimatic
Data,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Vogels, M.F.A.[Marjolein F.A.],
de Jong, S.M.[Steven M.],
Sterk, G.[Geert],
Douma, H.[Harke],
Addink, E.A.[Elisabeth A.],
Spatio-Temporal Patterns of Smallholder Irrigated Agriculture in the
Horn of Africa Using GEOBIA and Sentinel-2 Imagery,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Demarez, V.[Valérie],
Helen, F.[Florian],
Marais-Sicre, C.[Claire],
Baup, F.[Frédéric],
In-Season Mapping of Irrigated Crops Using Landsat 8 and Sentinel-1
Time Series,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Xiang, K.[Kunlun],
Ma, M.[Minna],
Liu, W.[Wei],
Dong, J.[Jie],
Zhu, X.[Xiufang],
Yuan, W.P.[Wen-Ping],
Mapping Irrigated Areas of Northeast China in Comparison to Natural
Vegetation,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Liu, Q.S.[Qing-Sheng],
Song, H.W.[Hong-Wei],
Liu, G.[Gaohuan],
Huang, C.[Chong],
Li, H.[He],
Evaluating the Potential of Multi-Seasonal CBERS-04 Imagery for
Mapping the Quasi-Circular Vegetation Patches in the Yellow River
Delta Using Random Forest,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Traoré, F.[Farid],
Bonkoungou, J.[Joachim],
Compaoré, J.[Jérôme],
Kouadio, L.[Louis],
Wellens, J.[Joost],
Hallot, E.[Eric],
Tychon, B.[Bernard],
Using Multi-Temporal Landsat Images and Support Vector Machine to
Assess the Changes in Agricultural Irrigated Areas in the Mogtedo
Region, Burkina Faso,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link
1907
BibRef
de C Teixeira, A.H.,
de Miranda, F.R.,
Leivas, J.F.,
Pacheco, E.P.,
Garçon, E.A.M.,
Water productivity assessments for dwarf coconut by using Landsat 8
images and agrometeorological data,
PandRS(155), 2019, pp. 150-158.
Elsevier DOI
1908
Evapotranspiration, Biomass production, Irrigation management,
Remote sensing, L.
BibRef
Xie, Y.H.[Yan-Hua],
Lark, T.J.[Tyler J.],
Brown, J.F.[Jesslyn F.],
Gibbs, H.K.[Holly K.],
Mapping irrigated cropland extent across the conterminous United
States at 30?m resolution using a semi-automatic training approach on
Google Earth Engine,
PandRS(155), 2019, pp. 136-149.
Elsevier DOI
1908
Irrigation agriculture, Landsat, Automatic classification,
Water use, Conterminous United States, Google Earth Engine
BibRef
Lovell, R.J.[Robin J.],
Identifying Alternative Wetting and Drying (AWD) Adoption in the
Vietnamese Mekong River Delta: A Change Detection Approach,
IJGI(8), No. 7, 2019, pp. xx-yy.
DOI Link
1908
Water saving practice for rice growing.
BibRef
Wittamperuma, I.,
Hafeez, M.,
Pakparvar, M.,
Louis, J.,
Remote-sensing-based Biophysical Models For Estimating LAI of Irrigated
Crops In Murry Darling Basin,
ISPRS12(XXXIX-B8:367-373).
DOI Link
1209
BibRef
Abuzar, M.,
Mcallister, A.,
Whitfield, D.,
Sheffield, K.,
Satellite-based Measurements For Benchmarking Regional Irrigation
Performance In Goulburn-murray Catchment,
ISPRS12(XXXIX-B8:221-223).
DOI Link
1209
BibRef
Dong, T.T.[Ting-Ting],
Wang, Z.Y.[Zhen-Ying],
A new method to distinguish between irrigated dry land and rain-fed dry
land using multi-temporal MODIS and ancillary data:
An application example in China,
IASP10(393-398).
IEEE DOI
1004
BibRef
Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
LAI, Leaf Area Index, Land Cover Analysis .