共查询到20条相似文献,搜索用时 10 毫秒
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Swapnil Vyas Rahul Nigam N. K. Patel Sushma Panigrahy 《Journal of the Indian Society of Remote Sensing》2013,41(4):855-864
Monitoring of Agricultural crops using remote sensing data is an emerging tool in recent years. Spatial determination of sowing date is an important input of any crop model. Geostationary satellite has the capability to provide data at high temporal interval to monitor vegetation throughout the entire growth period. A study was conducted to estimate the sowing date of wheat crop in major wheat growing states viz. Punjab, Haryana, Uttar Pradesh (UP), Madhya Pradesh (MP), Rajasthan and Bihar. Data acquired by Charged Couple Detector (CCD) onboard Indian geostationary satellite INSAT 3A have continental (Asia) coverage at 1 km?×?1 km spatial resolution in optical spectral bands with high temporal frequency. Daily operational Normalized Difference Vegetation Index (NDVI) product from INSAT 3A CCD available through Meteorological and Oceanographic Satellite Data Archival Centre (MOSDAC) was used to estimate sowing date of wheat crop in selected six states. Daily NDVI data acquired from September 1, 2010 to December 31, 2010 were used in this study. A composite of 7 days was prepared for further analysis of temporal profile of NDVI. Spatial wheat crop map derived from AWiFS (56 m) were re-sampled at INSAT 3A CCD parent resolution and applied over each 7 day composite. The characteristic temporal profiles of 7 day NDVI composite was used to determine sowing date. NDVI profile showed decreasing trend during maturity of kharif crop, minimum value after harvest and increasing trend after emergence of wheat crop. A mathematical model was made to capture the persistent positive slope of NDVI profile after an inflection point. The change in behavior of NDVI profile was detected on the basis of change in NDVI threshold of 0.3 and sowing date was estimated for wheat crop in six states. Seven days has been deducted after it reached to threshold value with persistent positive slope to get sowing date. The clear distinction between early sowing and late sowing regions was observed in study area. Variation of sowing date was observed ranging from November 1 to December 20. The estimated sowing date was validated with the reported sowing date for the known wheat crop regions. The RMSD of 3.2 (n?=?45) has been observed for wheat sowing date. This methodology can also be applied over different crops with the availability of crop maps. 相似文献
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Anirban Akhand Anirban Mukhopadhyay Abhra Chanda Sandip Mukherjee Abhishek Das Sourav Das Sugata Hazra Debasis Mitra S. B. Choudhury K. H. Rao 《Journal of the Indian Society of Remote Sensing》2017,45(1):147-154
Sundarban, the largest single patch of mangrove forest of the world is shared by Bangladesh (~ 60 %) and India (~ 40 %). Loss of mangrove biomass and subsequent potential emission of carbon dioxide is reported from different parts of the world. We estimated the loss of above ground mangrove biomass and subsequent potential emission of carbon dioxide in the Indian part of the Sundarban during the last four decades. The loss of mangrove area has been estimated with the help of remotely sensed data and potential emission of carbon dioxide has been evaluated with the help of published above ground biomass data of Indian Sundarban. Total loss of mangrove area was found to be 107 km2 between the year 1975 and 2013. Amongst the total loss ~60 % was washed away in the water by erosion, ~ 23 % was converted into barren lands and the rest were anthropogenically transformed into other landforms. The potential carbon dioxide emission due to the degradation of above ground biomass was estimated to be 1567.98 ± 551.69 Gg during this period, which may account to 64.29 million $ in terms of the social cost of carbon. About three-forth of the total mangrove loss was found in the peripheral islands which are much more prone to erosion. Climate induced changes and anthropogenic land use change could be the major driving force behind this loss of ‘blue carbon’. 相似文献
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《The Cartographic journal》2013,50(3):257-261
Abstracttitle/>Patterns consisting of point symbols are commonly applied to symbolize land cover. Tree symbols, for example, indicate forested areas; small irregular dots show quarries and pits; or regular line symbols represent a vineyard. This paper presents an automatic method for synthesizing patterns consisting of one or more point symbols. Symbols of varying sizes or graphical appearance can be combined according to user-defined ratios. The automatic method generates patterns of regularly or irregularly distributed symbols. It ensures that symbols do not overlap and do not graphically conflict with other map features. The method has been implemented in a free plug-in for the Adobe Illustrator vector graphics editor. 相似文献
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在解决 GML 数据存储问题之前必须首先考虑如何存储 GML 文档,因为只有通过对 GML应用模式的分析才能确定 GML 数据库的存储模型。简单介绍了 XML 的一般性概念,以及目前GIS 领域的通用交流语言——地理标记语言(GML),重点探讨了 GML 的标准模式。 相似文献
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Pattern based map comparisons 总被引:5,自引:0,他引:5
Roger White 《Journal of Geographical Systems》2006,8(2):145-164
Map comparison techniques based on a pixel-by-pixel comparison are useful for many purposes, but fail to reveal important aspects of map similarities and differences. In contrast, pattern based map comparison techniques address the question of structural similarity, although with these approaches the comparison problem becomes open ended, since there is an unlimited number of ways to characterise a pattern. Two types of pattern based technique are used here to analyse the test sets of maps. The first, a fuzzy polygon based matching technique, focuses on the meso-scale aspects of pattern. It is based on the areal intersection of land use polygons on the two maps being compared. The areal intersection, areal complement, and polygon size values are fuzzified into an appropriate set of categories, a set of fuzzy inference rules is applied to derive memberships in local matching categories, and finally the local matching category memberships are defuzzified to yield local matching values for each land use polygon on the reference map. The second approach, fractal analysis, captures macro-scale or global qualities of the maps. Two measures are calculated here: the radial dimension and the cluster size—frequency dimension. The polygon matching approach provides only limited insight when applied to the case of the map set representing differences in classification. It proves much more effective when applied to the problem of change detection, revealing areas where the pattern has changed and giving local measures of the degree of change. The approach is particularly useful in the case where there is a considerable degree of random change at the pixel level, as changes in the underlying pattern are extracted from the noise, while pixel based approaches largely detect the noise. 相似文献
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