Crop cover and crop phenological information from red and infrared spectral responses

Ayyangar, R. S.; Rao, P. Parthasarathy; Rao, K. R.

doi:10.1007/bf02990665

Cited by 13 publications

(1 citation statement)

References 2 publications

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“…As scale of aerial photography was 1:30,000 or larger, individual fields, crop plants and crop row structure were detectable and inventory involved fieldwise visual delineation. The major crops mapped included (i) wheat in Patiala district of Punjab (Dhanju and Shankarnarayana, 1978) and Mehsana district of Gujarat, (ii) groundnut in Anantapur district of Andhra Pradesh (Sahai et al, 1977), (iii) rice and sugarcane in Mandya district (Karnataka) where 11-channel multispectral scanner was flown and subjected to digital interpretation (Ayyangar et al, 1980) and (iv) agricultural land use of both field and plantation crops (paddy, sugarcane, rubber, coconut, tea, tapioca and others in Idukki district of Kerala) (Sahai et al, 1985), to name a few. Visual interpretation of data of Landsat-1 was feasible at 1:1 million to 1:250,000 scale, and thus, digital crop inventory was not conducted.…”

Section: Eo Data For Agricultural Crops In India-evolution Over Five ...mentioning

confidence: 99%

Progress and Challenges in Earth Observation Data Applications for Agriculture at Field Scale in India and Small Farm Holdings Regions

Ray

Dadhwal

Navalgund

2022

J Indian Soc Remote Sens

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The paper traces the evolution of agricultural remote sensing in India through its four phases: initial exploratory and aerial data based (1969)(1970)(1971)(1972)(1973)(1974)(1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982), IRS Utilization Program led (1983( -1995( ), post-IRS-1C launch (1996( -2011 and since the establishment of a dedicated institution for EO-based crop forecasting and other agricultural applications (2012 onward). Published field-scale studies are discussed before introducing the submissions to the special issue of the journal, namely Advanced Geospatial Technologies for Agriculture with Special emphasis on field level Applications. A total of 17 articles grouped under crop discrimination and mapping, crop yield estimation, crop suitability analysis, irrigation management and others (UAV, fodder and field boundary extraction) and 15 of these describe work over India and remaining two have Iran as their study area. These studies are linked to other published work as well as challenges under major issues of data access, use of UAV, use of smartphones, data processing and crop simulation models. Taken together, these articles report substantial improvements in capabilities of field-scale monitoring for developing new class of agricultural applications in India as well as other regions in the world with small farm holdings.

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Section: Eo Data For Agricultural Crops In India-evolution Over Five ...mentioning

confidence: 99%