{"id":3017,"date":"2022-05-27T16:07:41","date_gmt":"2022-05-27T16:07:41","guid":{"rendered":"https:\/\/icpa.ro\/point-databases\/"},"modified":"2026-04-29T13:58:26","modified_gmt":"2026-04-29T13:58:26","slug":"point-databases","status":"publish","type":"page","link":"https:\/\/icpa.ro\/en\/point-databases\/","title":{"rendered":"Point databases"},"content":{"rendered":"[vc_row type=”full_width_background” full_screen_row_position=”middle” column_margin=”default” equal_height=”yes” content_placement=”bottom” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” bg_color=”#fff6e2″ bg_image=”1734″ bg_position=”center top” background_image_loading=”default” bg_repeat=”no-repeat” scene_position=”center” top_padding=”18%” bottom_padding=”4%” text_color=”light” text_align=”center” row_border_radius=”none” row_border_radius_applies=”bg” color_overlay=”#ffdfaf” overlay_strength=”0.5″ gradient_direction=”left_to_right” shape_divider_position=”bottom” shape_divider_height=”350″ bg_image_animation=”fade-in” parallax_bg=”true” parallax_bg_speed=”fast” shape_type=”mountains”][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” centered_text=”true” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][split_line_heading animation_type=”line-reveal-by-space” font_style=”h1″ text_color=”#36361e” content_alignment=”default” mobile_content_alignment=”inherit” text_content=”Point databases” max_width=”800″][\/split_line_heading][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row type=”full_width_background” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” bg_color=”#eeeff4″ scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none” shape_type=””][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][divider line_type=”No Line” custom_height=”40px”][vc_column_text]Another type of data held in the patrimony of INCDPAPM-ICPA Bucharest is the point databases, which contain morphological description data and chemical, physical, and micromorphological analyses for a series of soil profiles. The data are stored in the INCDPAPM-ICPA Bucharest archive, within the PROFISOL database, as well as data that are part of the soil quality monitoring network administered by INCDPAPM-ICPA Bucharest and the Ministry of Agriculture and Rural Development.[\/vc_column_text][divider line_type=”No Line” custom_height=”10px”][\/vc_column][\/vc_row][vc_row type=”full_width_background” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none” shape_type=””][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][divider line_type=”No Line” custom_height=”40px”][vc_column_text]\n

PROFISOL database<\/em><\/h4>\n[\/vc_column_text][vc_column_text]The PROFISOL database (Canarache et al., 1998; Vlad et al., 1997) was developed within ICPA\u2019s research and development program in several stages between 1986 and 1996 (Vlad et al., 1997) and aimed to provide facilities for storing, retrieving, and processing data on the main soil profiles existing or to be developed within pedological studies and research in Romania. Over time, the soil profile database underwent successive changes and enabled validation of the entered data, calculation\u2014through pedotransfer functions\u2014of certain initially undetermined soil properties, conversion of measurement units, calculation of mean values for different soil layers, selection of profile groups according to various criteria and statistical calculations related to these groups, as well as, of course, the generation of various types of reports.<\/p>\n

The profiles (Fig. 1) entered into the database are identified by a chronological numeric code assigned at the time of computer storage. Alongside this code, the chronological serial number of the profile within the commune and the profile identification number in the respective mapping work are stored (Vlad et al., 1997).[\/vc_column_text][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” top_padding=”10″ bottom_padding=”20″ left_padding_desktop=”20″ right_padding_desktop=”20″ text_align=”left”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][image_with_animation image_url=”1745″ animation=”Fade In From Right” hover_animation=”none” alignment=”” border_radius=”none” box_shadow=”none” image_loading=”default” max_width=”100%” max_width_mobile=”default”][\/vc_column_inner][\/vc_row_inner][vc_column_text]\n

Figure 1. Location of georeferenced soil profiles and the associated database
\n<\/em><\/p>\n[\/vc_column_text][divider line_type=”No Line” custom_height=”10px”][vc_column_text]A series of new data (not provided for in the data collection sheet), derived from the corresponding primary data, where available, are determined according to classical formulas or definition algorithms: 4 general data items per profile; 12 morphological data items for the profile as a whole, required to obtain the formula of the field mapping unit; 20 physical data items by (sub)horizons; 8 chemical data items by (sub)horizons. In addition, 40 physical data items can be calculated for standard depths of the soil profile; there are 4 different predefined sets of standard depths (10, 20, 50, or 100 cm), and users may also specify other sets of up to a maximum of 9 desired standard depths. To these is added the calculation of missing primary data: 18 physical data items by (sub)horizons and 3 chemical data items by (sub)horizons.<\/p>\n

In addition, the PROFISOL database allows the indirect estimation of missing primary data by implementing algorithms (pedotransfer functions) developed at ICPA (Canarache, 1986, 1987), which enable the calculation of 9 physical properties by (sub)horizons when no measured values exist for them, but the corresponding primary data have been entered.[\/vc_column_text][nectar_cta btn_style=”arrow-animation” heading_tag=”h6″ text_color=”#33cc66″ button_color=”default” button_color_hover=”#fff6d2″ link_type=”regular” alignment=”left” alignment_tablet=”default” alignment_phone=”default” display=”block” link_text=”More information” url=”\/en\/profisol\/”][divider line_type=”No Line” custom_height=”20px”][\/vc_column][\/vc_row][vc_row type=”full_width_background” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” bg_color=”#eeeff4″ scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none” shape_type=””][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_spacing=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_shadow=”none” column_border_radius=”none” column_link_target=”_self” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” tablet_text_alignment=”default” phone_text_alignment=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][divider line_type=”No Line” custom_height=”50px”][vc_column_text]\n

MONITORING database<\/em><\/h4>\n[\/vc_column_text][vc_column_text]The \u201cMonitoring system for agricultural and forest soils\u201d was developed in successive stages:<\/p>\n
    \n
  • In the first stage, it was funded by the Ministry of Waters, Forests and Environmental Protection (1992\u20132000), when research was carried out within the national Level I monitoring network (16×16 km), thus covering the entire territory of the country (670 agricultural sites and 274 forest sites) (Dumitru et al., 2000).<\/li>\n
  • In the second stage (2000\u20132002), the second determination of monitoring parameters was carried out at 197 Level I agricultural sites within the Relansin Program.<\/li>\n
  • Starting in 2003, the second determination within the Level I agricultural network was continued for the 670 agricultural sites.<\/li>\n
  • At the same time, Level II studies were carried out on various soil pollution and degradation processes. Soil monitoring activity at local level was relaunched through pedological studies in administrative territories.<\/li>\n
  • Starting in 2010, an 8 x 8 km monitoring site network was established.<\/li>\n<\/ul>\n

    The determinations made it possible to establish trends in the main soil monitoring parameters in Romania. Fieldwork was carried out, for the most part, by the Offices for Pedological and Agrochemical Studies, while laboratory analyses, data centralization, and processing were performed by the Research Institute for Pedology and Agrochemistry. The monitored indicators were the physical and chemical characteristics and the load of potentially polluting elements and substances in the soils of the 16×16 km network. Level II monitoring of areas affected by various pollution processes was carried out by conducting studies on slope processes (erosion and landslides) in different areas of the country (Boto\u0219ani, Bac\u0103u, Ia\u0219i, Neam\u021b, Suceava, Vaslui counties, etc.), as well as processes of pollution with heavy metals and sulfur oxides (Baia Mare, Cop\u0219a Mic\u0103, Zlatna areas). Following soil erosion studies across the different stages, significant soil losses caused by slope processes were identified, and ways to reduce them were presented through appropriate measures (restructuring land use, applying soil amendments and organic and mineral fertilizers, etc.) (MM, ANMP, 2009).<\/p>\n

    The soil profiles in the Monitoring database were georeferenced (Fig. 2), and the attribute database contains data on a series of morphological, physical, and chemical properties related to those profiles.[\/vc_column_text][image_with_animation image_url=”1734″ animation=”Fade In From Left” hover_animation=”none” alignment=”” border_radius=”none” box_shadow=”none” image_loading=”default” max_width=”100%” max_width_mobile=”default”][vc_column_text]\n

    Figure 2. Location of soil profiles in the soil quality monitoring network <\/em><\/p>\n[\/vc_column_text][divider line_type=”No Line” custom_height=”10px”][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"

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