Irrigation Monitoring, Irrigated Field Detection, Land Use Analysis

Chapter Contents (Back)

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

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

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

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

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

Hagimoto, Y.[Yutaka],
Application of Landsat to Evaluate Effects of Irrigation Forbearance,
RS(5), No. 8, 2013, pp. 3776-3802.
DOI Link 1309

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

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

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

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

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

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

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
And: Erratum: RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Wang, C.H.,
Using Remote Sensing Technology on the Delimitation of the Conservation Area for the Jianan Irrigation System Cultural Landsccape,
DOI Link 1508

Wittamperuma, I., Hafeez, M., Pakparvar, M., Louis, J.,
Remote-sensing-based Biophysical Models For Estimating LAI of Irrigated Crops In Murry Darling Basin,
DOI Link 1209

Abuzar, M., Mcallister, A., Whitfield, D., Sheffield, K.,
Satellite-based Measurements For Benchmarking Regional Irrigation Performance In Goulburn-murray Catchment,
DOI Link 1209

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,

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