Land-use classification was performed by using a set of ERS-1, JERSand Radarsat images. Classes were water, forests (with subclasses according to stem volume), agricultural field, mire and urban area. Median filtering was used for speckle reduction and principal component analysis for feature extraction. Spectral classification was performed by using self-organizing feature map and learning vec...

Extraction of vegetation is an important step for agricultural, forest and greenery mapping. The proposed method examines the complex process of land cover vegetation pattern classification using an IRS-1C LISS III image. Pre-processing was done by employing partial differential equation (PDE). Normalized differential vegetation index (NDVI) was applied to separate vegetation features from the ...

Accounting for China’s Growth China has achieved impressive growth over the last three decades. However, there has been debate over the sources of the growth, and the role of the intensive versus extensive margin. Growth accounting exercises at the aggregate level (Rawski and Perkins, 2008; Bosworth and Collins, 2008) suggest an equal role for both. For the non-agricultural sector, there have b...

In 2008, agricultural producers planted more than 80% of US cotton and corn acreage and more than 90% of soybean acreage to transgenic glyphosate-tolerant, Roundup Ready® (RR) seed varieties (US Department of Agriculture Agricultural Marketing Service [USDA AMS], 2008; USDA National Agricultural Statistics Service [NASS], 2008). Many studies report significant pecuniary and non-pecuniary benefi...

Based on the mathematical model of crop, an algorithm for quantitative assessment agricultural risk crops cultivated in specific soil and climatic conditions has been developed. Classification risks according to crop losses is proposed, similar gradation adopted insurance payments, but more detailed. It established that indicators do not depend level nutrition, each year are determined only by ...