N: 90 S: -90 E: 180 W: -180
Description
The Landsat-Derived Global Rainfed and Irrigated-Cropland Product (LGRIP) provides high resolution, global cropland data to assist and address food and water security issues of the twenty-first century. As an extension of the Global Food Security-support Analysis Data (GFSAD) project, LGRIP maps the world’s agricultural lands by dividing them into irrigated and rainfed croplands and calculates irrigated and rainfed areas for every country in the world. LGRIP data are produced using Landsat 8 time-series satellite sensor data for the 2014-2017 time period to create a nominal 2015 product.
Each LGRIP 30 meter resolution GeoTIFF file contains a contains a layer that identifies areas of rainfed cropland (cropland areas that are purely dependent on direct precipitation), irrigated cropland (cropland that had at least one irrigation during the crop growing period), non-cropland, and water bodies over a 10° by 10° area, as well as an accuracy assessment of the product. A low-resolution browse image is also available.
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Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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File Naming Convention
The file name begins with Product Short Name (LGRIP30) followed by the Year of Acquisition (2015), the Latitude and Longitude of the lower left corner of the tile (N20E00), the Version of the data product (001), the Julian Date and Time of Processing designated as YYYYDDDHHMMSS (2023014175240), and the Data Format (tif).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Annual irrigated cropland mapping reveals uneven expansion and rising | Tolera, Abera Misgana, Zhang, Chao, You, Nanshan, Dong, Jinwei | Reflectance, Vegetation Cover, Cropland | |
| Crop and irrigation types ground-truth dataset for Moroccan agricultural regions | Ouassanouan, Youness, Elfarkh, Jamal, Grich, Said, Liblab, Abderrahman, Chehbouni, Abdelghani | Land Use/Land Cover Classification | |
| Biophysical regulation mechanisms of land surface temperature driven by | Xv, Zheng, Lv, Aifeng | ||
| Groundwater resources in the Greater Mekong Region: A review | Viossanges, M., Batelaan, O., Pavelic, P., Banks, E.W., Tam, V.T., Bui, D., Wongsomsak, S., Zaw, U.T., Zin, U.T., Oeurng, C., Ty, S., Srisuk, K., Pholkern, K., Saraphirom, P., Douangsavanh, S., Xayviliya, O., Vongphachanh, S. | ||
| High-resolution maize yield mapping across Africa using earth observation and machine learning, deep learning, and foundation model | Halder, Krishnagopal, Ewert, Frank, Ghosh, Anitabha, Muduchuru, Kaushik, Sweet, Lily-belle, Elshawi, Radwa, Timko, Jan, Zheng, Wenhi, Alsafadi, Karam, Zhao, Gang, Maerker, Michael, Singh, Manmeet, Guoging, Lei, Gaiser, Thomas, Behrend, Dominik, Shi, Yue, Han, Liangxiu, Ryo, Masahiro, Srivastava, Amit Kumar | ||
| Increased Dependency on Extreme Precipitation in a Warmer Climate | Ombadi, Mohammed, Nguyen, Lisa, Gaur, Srishti, Gronewold, Andrew, Reich, Peter B. | ||
| Large-scale irrigation area mapping: Status and challenges | Zhu, Wanxue, Donmez, Elif, Storm, Hugo, Heckelei, Thomas, Siebert, Stefan | ||
| The buffer value of groundwater increases under trade restrictions | Haqiqi, Iman, Hertel, Thomas W, Grogan, Danielle S | ||
| Progress in wheat farm yield improvement has largely stagnated across the US Pacific Northwest | Adams, Curtis B., Graebner, Ryan, Durfee, Nicole | ||
| Saltwater Intrusion Vulnerability of Soil and Groundwater Near Estuaries | Tackley, Hayden A., Kurylyk, Barret L., Lake, Craig B. | ||
| Remote sensing and TerraClimate datasets for wheat yield prediction using machine learning | Araghi, Alireza, Daccache, Andre | ||
| Field-scale irrigated winter wheat mapping using a novel cross-region slope length index in 3D canopy hydrothermal and spectral feature space | Zhang, Youming, Yang, Guijun, Thenkabail, Prasad S., Li, Zhenhong, Wu, Wenbin, Yang, Xiaodong, Song, Xiaoyu, Long, Huiling, Liu, Miao, Zhang, Jing, Zuo, Lijun, Meng, Yang, Gao, Meiling, Zhu, Wu | ||
| Global Rice Paddy Inventory (GRPI): A High-Resolution Inventory of | Chen, Zichong, Lin, Haipeng, Balasus, Nicholas, Hardy, Andy, East, James D., Zhang, Yuzhong, Runkle, Benjamin R. K., Hancock, Sarah E., Taylor, Charles A., Du, Xinming, Sander, Bjoern Ole, Jacob, Daniel J. | ||
| An annual cropland extent dataset for Africa at 30 m spatial resolution from 2000 to 2022 | Lou, Zihang, Peng, Dailiang, Shi, Zhou, Wang, Hongyan, Liu, Ke, Zhang, Yaqiong, Yan, Xue, Chen, Zhongxing, Ye, Su, Yu, Le, Hu, Jinkang, Lv, Yulong, Peng, Hao, Zhang, Yizhou, Zhang, Bing | Land Use/Land Cover Classification | |
| A reply to Lankford and Agol (2024). Irrigation is more than irrigating: agricultural green water interventions contribute to blue water depletion and the global water ... | Rockstrom, Johan, Barron, Jennie | ||
| Artificial Neural Network Multi-layer Perceptron Models to Classify | McCormick, Richard, Thenkabail, Prasad S., Aneece, Itiya, Teluguntla, Pardhasaradhi, Oliphant, Adam J., Foley, Daniel | ||
| Catchment Attributes and MEteorology for Large-Sample SPATially | Knoben, Wouter J. M., Thebault, Cyril, Keshavarz, Kasra, Torres-Rojas, Laura, Chaney, Nathaniel W., Pietroniro, Alain, Clark, Martyn P. | Land Use/Land Cover Classification, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Stratigraphic Sequence, Digital Elevation/Terrain Model (DEM), Soil Depth, Sediments, Maximum/Minimum Temperature, 24 Hour Precipitation Amount, Snow Water Equivalent, Vapor Pressure, Shortwave Radiation | |
| Connecting the drops: A methodological challenge for the deployment of | Daudin, Kevin, Belaud, Gilles, Leauthaud, Crystele, Bouzidi, Zhour, Lejars, Caroline | ||
| GMIE: a global maximum irrigation extent and central pivot irrigation system dataset derived via irrigation performance during drought stress and deep ... | Tian, Fuyou, Wu, Bingfang, Zeng, Hongwei, Zhang, Miao, Zhu, Weiwei, Yan, Nana, Lu, Yuming, Li, Yifan | ||
| Large-scale irrigation mapping at field level in Northern Germany with integrated use of Sentinel-2, Landsat 8 and Sentinel-1 time series | Ghazaryan, Gohar, Ernst, Stefan, Sempel, Farina, Nendel, Claas | ||
| Joint assimilation of satellite soil moisture and vegetation conditions | Chakraborty, Arijit, Saharia, Manabendra | Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| Multi-model ensemble mapping of irrigated areas using remote sensing | Akbar, Muhammad Umar, Mirchi, Ali, Arshad, Arfan, Alian, Sara, Mehata, Mukesh, Taghvaeian, Saleh, Khodkar, Kasra, Kettner, Jacob, Datta, Sumon, Wagner, Kevin | ||
| Quantifying Meltwater Contributions and Socio-Economy Impacts of Future | Liu, Hu, Wang, Lei, Chen, Deliang, Yao, Tandong, Bashir, Ahmad | Population Estimates, Socioeconomics | |
| Landsat-Derived Global Food Security-Support Analysis Data @ 30M (LGFSAD30) to Help Address World's Food and Water Security | Thenkabail, Prasad S., Teluguntla, Pardhasaradhi, Oliphant, Adam, Aneece, Itiya, Foley, Daniel | Crop/Plant Yields, Land Use Classes, Landscape Patterns | |
| Landsat-Derived Rainfed and Irrigated-Area Product for Conterminous United States for the Year 2020 (LRIP30 CONUS 2020) Using Supervised and Unsupervised Machine Learning on the Cloud | Teluguntla, Pardhasaradhi, Thenkabail, Prasad S., Oliphant, Adam, Aneece, Itiya, Biggs, Trent, Gumma, Murali Krishna, Foley, Daniel, McCormick, Richard, Neelam, Rohitha, Long, Emerson, Lawton, Jake | Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Vegetation Cover, Reflectance |