Application of remote sensing and GIS for sustainable development

Bibliographic data

Monograph

Persistent identifier:: 856472832

Title:: Application of remote sensing and GIS for sustainable development

Sub title:: [Workshop on "Environmental Modelling Using RS & GIS for Sustainable Development" ... on 11th March 1999]

Scope:: 82 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856472832

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: REMOTE SENSING AND GIS FOR AGRICULTURAL CROP ACREAGE AND YIELD ESTIMATION. Vinay K. Dadhwal

Document type:: Monograph

Structure type:: Chapter

58 REMOTE SENSING AND GIS FOR AGRICULTURAL CROP ACREAGE AND YIELD ESTIMATION Vinay K. Dadhwal Space Applications Centre, Ahmedabad ABSTRACT The use of satellite remote sensing data (RS) for operational crop assessment and forecasting at regional scales is of great significance for food security and policy decisions. Improvements in sensor capability and analysis techniques now allow accurate crop discrimination. Through use of GIS, regional sampling strategy using land cover, crop distribution and administrative boundary information, large area crop inventory is carried out. The use of RS data for yield forecasting, with high and coarse resolution and single or multiple acquisitions has generally followed empirical regression approach. The information on soil and weather can be integrated for yield modelling through use of crop simulation models. GIS plays an important role in converting the input data to a common format for use in the model. The recent Indian experience in developing techniques for estimation of summarised. REMOTE SENSING IN CROP ACREAGE ESTIMATION The use of spaceborne RS data for large area crop survey was first explored under CITARS Project in USA and was followed by an attempt to forecast wheat for major growing regions of the world under LACIE (Large Area Crop Inventory Experiment, 1974-1977) (MacDonald and Hall, 1980). Since then, large scale methodology development-cum-demonstration studies for crop statistics have been carried out in Africa and Europe as well as in a number of other countries (Argentina, Australia, Brazil, Canada, Japan etc.). Currently major programs are underway in Europe under MARS (Monitoring Agriculture through Remote Sensing). Remote Sensing (RS) can be used for crop acreage estimation in either for making area sampling frame (crop inventory being done by field survey), or for crop discrimination. Current regional crop inventory studies use RS for both applications, GIS-based sampling and digital image processing for crop discrimination. In case, the accuracy of RS-based discrimination is not acceptable, it has to be combined with field survey information. RS-BASED ACREAGE : INDIAN EXPERIENCE CAPE PROJECT Systematic studies on district-level crop inventory were taken up for single crop dominated districts (Karnal, Haryana for wheat, Dadhwal and Parihar, 1985) and promising results led to state level wheat acreage estimation in Haryana and Punjab using a sample crop area and forecast of likely yield using both RS and GIS is segment approach. It used 10 x 10 km segments, a stratified sample design and 10 percent sampling fraction and a single acquisition at optimal bio-window (Dadhwal, 1986). This approach has been followed in Crop Acreage and Production Estimation (CAPE) Project, which is sponsored by Ministry of Agriculture and covered six major crops in 15 States (Navalgund et al., 1991). The study areas for these crops are summarised in Table 1. A summary of results of CAPE project for 1997-98 crop season are provided in Table 2. A procedure using multi date WiFS data and GIS for sample design, developed for national-level multiple wheat assessments (Oza et al, 1996) is described below. Improving the accuracy of RS-based crop inventory The CAPE procedure is being continuously revised and upgraded to improve upon accuracy and timeliness of crop estimates. These efforts are related to improving a) Sample design, b) Ground truth data collection, c) Optimising date of data acquisition, d) Including data from additional spectral regions in the digital analysis, e) Multi date data analysis, f) Use of higher spatial resolution data, g) Adopting different classification procedures, and h) Use of microwave data for crop inventory in kharif season. Significant results from these studies are summarised below. Sample Design Studies carried out on rice for Orissa and wheat for Haryana have clearly shown that two-step stratification based on agro-physical and crop distribution improves efficiency of stratification (Panigrahy et al., 1991). Size of the sample segments and sampling fraction are two

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