TY - JOUR ID - bastiaanssen2000 AU - Bastiaanssen, Wim G. M. AU - Molden, David J. AU - Makin, Ian W. TI - Remote sensing for irrigated agriculture: examples from research and possible applications UR - http://www.sciencedirect.com/science/article/pii/S0378377400000809 DO - 10.1016/s0378-3774(00)00080-9 T2 - Agricultural Water Management PY - 2000 SN - 0378-3774 VL - 46 IS - 2 SP - 137-155 AB - Researchers in various international programs have studied the potential use of remotely sensed data to obtain accurate information on land surface processes and conditions. These studies have demonstrated that quantitative assessment of the soil-vegetation-atmosphere-transfer processes can lead to a better understanding of the relationships between crop growth and water management. Information on land surface can now be obtained at a wide range of spatial (5–5000 m) and temporal resolutions (0.5–24 days). However, even though considerable progress has been made over the past 20 years in research applications, remotely sensed data remain underutilized by practicing water resource managers. This paper seeks to bridge the gap between researchers and practitioners, first, by illustrating where research tools and techniques have practical applications and, second, by identifying real problems that remote sensing could solve, albeit with additional research and development. As freshwater becomes an increasingly scarce resource, all opportunities to better manage water uses, particularly in irrigated agriculture, must be taken. An important challenge in the field of water resources is to utilize the timely, objective and accurate information provided by remote sensing. KW - Remote sensing KW - Irrigated farming KW - Land management KW - Water resources management KW - Crop yield KW - Water use efficiency KW - Water rights ER - TY - JOUR ID - moran1997 AU - Moran, M. S. AU - Inoue, Y. AU - Barnes, E. M. TI - Opportunities and limitations for image-based remote sensing in precision crop management UR - http://www.sciencedirect.com/science/article/pii/S003442579700045X DO - 10.1016/s0034-4257(97)00045-x T2 - Remote Sensing of Environment PY - 1997 SN - 0034-4257 VL - 61 IS - 3 SP - 319-346 AB - This review addresses the potential of image-based remote sensing to provide spatially and temporally distributed information for precision crop management (PCM). PCM is an agricultural management system designed to target crop and soil inputs according to within, field requirements to optimize profitability and protect the environment. Progress in. PCM has been hampered by a lack of timely, distributed information on crop and soil conditions. Based on a review of the information requirements of PCM, eight areas were identified in which image-based remote sensing technology could provide information that is currently lacking or inadequate. Recommendations were made for applications with potential for near-term implementation with available remote sensing technology and instrumentation. We found that both aircraft- and satellite-based re-trote sensing could provide valuable information for PCM applications. Images from aircraft-based sensors have a unique role for monitoring seasonally variable crop/soil conditions and for time specific and time-critical crop management; current satellitebased sensors have limited, but important, applications; and upcoming commercial Earth observation satellites may provide the resolution, timeliness, and high quality required for many PCM operations. The current limitations for image-based remote sensing applications are mainly due to sensor attributes, such as restricted spectral range, coarse spatial resolution, slow turnaround time, and inadequate repeat coverage. According to experts in PCM, the potential market for remote sensing products in PCM is good. Future work should be focused on assimilating remotely sensed infonna- tion into existing decision support systems (DSS), and conducting economic and technical analysis of remote sensing applications with season-long pilot projects. ER - TY - ELEC ID - idb AU - Henrich, V. AU - Krauss, G. AU - Götze, C. AU - Sandow, C. TI - The IndexDatabase UR - https://www.indexdatabase.de/ CY - Bonn PY - 2011 DA - 2011 ER -