Accuracy assessment in cotton acreage estimation using Indian remote sensing satellite data

The accuracy of cotton crop classification using satellite data has been assessed with respect to a detailed land cover map prepared by field survey. The effect of spatial resolution on classification accuracy was studied using LISS-I (spatial resolution 72.6 m) and LISS-II data (spatial resolution 36.25 m) of the Indian remote sensing satellite IRS-1B. The performances of the maximum likelihood and the minimum distance to mean as classifiers have also been assessed. LISS-II data have been found to give a higher classification accuracy. The estimate of cotton acreage using LISS-II data was closer to that obtained from the base map. The maximum likelihood classifier (MXL) and the minimum distance to mean (MDM) classifier performed equally well.     

Bridging High School and Introductory Undergraduate Courses in Geographic Information Science and Technology

This article presents the findings of a study to determine the degree of consistency in what is taught and learned in high school and college-level introductory courses in geographic information science and technology (GIS&T). A content analysis identified sixteen topics that are generally representative of the knowledge, skills, and abilities developed in introductory undergraduate courses. The findings were used to propose a standard college-level survey course in GIS&T that could inform future efforts to introduce more academically rigorous GIS&T coursework in high schools, such as through the Advanced Placement Program.     

Crop classification accuracy as influenced by training strategy,data transformation and spatial resolution of data

The possibility of improving classification accuracies using different training strategies and data transformations within the framework of a supervised maximum likelihood classification scheme was explored in this study. The effect of spatial resolution of data on the accuracy of classification was also studied Single-pixel training strategy resulted in improved classification accuracy over the block-training method. Data transformations gave no significant improvements in accuracy over untransformed data. There was a reduction in classification accuracy as resolution of data improved from 72 m (LISS I) to 36 m (LISS II) while other sensor characteristics remained same.     

Wheat acreage estimation for Haryana using satellite digital data

This paper summarizes the procedures adopted and results obtained since 1985–86 for wheat inventory for Haryana using satellite digital data (MSS: 1985–86 to 1987–88, LISS-I: 1988–89 onwards). The approach followed is based on sample segments (10 × 10 km during 1985–86 to 1988–89, 7.5 × 7.5 km during 1989–90) and 10 percent sampling fraction and stratified sample design. There has been consistent improvement in accuracy over the years as judged from lower biases when compared with Bureau of Economics and Statistics (BES) acreage estimates and higher precision. In 1989–90, the state-level estimate achieved an accuracy goal of 90 percent at 90 percent confidence interval. A number of studies which have been carried out to study effect of choice of sensor, acquisition date, stratification approach, classification procedure on wheat inventory are also mentioned.     

Effect of acquisition date and TM spectral bands on wheat,mustard and gram classification accuracies

Single date classification accuracies of wheat, mustard and gram were investigated using TM data of five acquisition dates (January 24, February 9, 16,25 and March 12, 1988) and four band-combinations (TM 234 TM 345, TM 1234 and TM 2345) over an irrigated, optimum fertility site in Hisar (Haryana). Accuracies for wheat and gram were lowest on January 24 for all band-combinations and improved with later acquisitions. An interaction between acquisition date and band combination was apparent as accuracies with most optimal combinations remained high over the period from February 9 to March 12 ,while those with sub optimal combinations fluctuated widely from one date to another. The band-combinations which included middle-infrared (TM 2345 and TM 345) showed highest accuracies irrespective of crop and acquisition date while band combination of TM 234 consistently had lowest accuracies.     

俄罗斯阿尔泰-Sayan地区Aksug斑岩Cu-Mo体系的地质与地球化学特征

The Aksug deposit, located in Altay-Sayan region of Russia, is one of the largest porphyry Cu-Mo deposits in Southern Siberia. The ore-bearing porphyries of the Aksug porphyry Cu-Mo system were formed in post-collisional environment. Geochemically they belong to calk-alkaline and high K-calk-alkaline series. Rocks are characterized by enrichment of LILE and depletion of HSFE and HREE, showing the importance of subduction-related components in magma generation. Large plutonic intrusions that host porphyry systems have been formed during collision. The origin of porphyritic rocks is dominantly the mantle with lower crustal contribution. The mainly economically important Cu-Mo mineralization is closely related to a porphyry series in time and space, being emplaced towards the end of magmatic activity. Though the emplacement of plutonic and ore-bearing porphyry complexes took place in different geodynamic environments, both complexes are characterized by certain similarity in geochemical composition, alkalinity, trace element content, Sr isotopic composition. This fact evidently indicates a common deep-seated magmatic source (at the lower crust-upper mantle level). Low initial ⁸⁷ Sr/⁸⁶ Sr, sulfur isotopic characteristics and presence of PGE-Co-Ni mineralization in associated pyrite-chalcopyrite ores suggest that mantle source of chalcophile elements was of high importance in porphyry Cu-Mo mineralization of the Aksug deposit.