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return residuals and waste to the environment. As a result of human activities, environmental conditions, natural processes, and the capacity of ecosystems to provide
their goods and services all experience change. These changes, in turn, initiate
changes in the human subsystem’s economic and social processes. Immediate
objective of environment statistics is to provide quantitative information about the
environment’s state and its most important changes over time and across territories.
Operationally, the objective and ultimate purpose of environment statistics can be
achieved by setting up, strengthening, and sustaining environment statistics programs and units that function on a regular basis in each country, similar to those
already operating in economic and social statistics. Environment statistics is a
cross-cutting statistical domain with specific complexities. The demand for environment statistics is increasing rapidly everywhere. Environment statistics production
requires combined technical expertise on environmental themes, statistical technical capacities, and institutional coordination capacities. By definition, environment
statistics are multidisciplinary and cross-cutting, involving numerous stakeholders.
Environment statistics’ sources are dispersed, and a variety of methods are
applied in their compilation. They are collected through censuses, surveys, and the
use of administrative records, but also from specific types of sources such as monitoring stations, remote sensing, and scientific research. The way of collecting data
from the specific types of sources differs considerably from the survey techniques
employed in social and economic statistics: from the environment to the production
of biophysical data describing natural resources and environmental quality.
1.4.4 Quality of Prediction and Model Validation
The interdisciplinary and inter-institutional characteristics of environment statistics
and the variety of data producers and users require collaboration among institutions,
practitioners, and experts in different fields. To effectively transform environmental
information into official environment statistics, the collaboration and coordination
of a significant number of actors and institutions is required. Institutions with strong
leadership and the skills and resources to facilitate multi-stakeholder processes are
required. Thus, institutional strengthening and inter-institutional collaboration and
coordination are inherent to environment statistics data production, processing, and
dissemination.
Environmental phenomena take place in dispersed manner, constantly over time
and across territories, as a fluid set of processes, each with different velocities. At
the primary sources, measuring and monitoring requires careful selection.
Transforming raw data from primary sources to statistics takes expertise and institutional capacities. Developing countries face budgetary constraints, and the funds
allocated to statistics are subject to restrictions. In general, environmental issues are
given a lower priority than social and economic statistics. The cost of monitoring
systems and remote sensing is falling over time, and some of the primary production
of raw data (in monitoring and remote sensing agencies) require the investment,
1 General Aspects of Environmental Degradation vs. Technological Development…
return residuals and waste to the environment. As a result of human activities, environmental conditions, natural processes, and the capacity of ecosystems to provide
their goods and services all experience change. These changes, in turn, initiate
changes in the human subsystem’s economic and social processes. Immediate
objective of environment statistics is to provide quantitative information about the
environment’s state and its most important changes over time and across territories.
Operationally, the objective and ultimate purpose of environment statistics can be
achieved by setting up, strengthening, and sustaining environment statistics programs and units that function on a regular basis in each country, similar to those
already operating in economic and social statistics. Environment statistics is a
cross-cutting statistical domain with specific complexities. The demand for environment statistics is increasing rapidly everywhere. Environment statistics production
requires combined technical expertise on environmental themes, statistical technical capacities, and institutional coordination capacities. By definition, environment
statistics are multidisciplinary and cross-cutting, involving numerous stakeholders.
Environment statistics’ sources are dispersed, and a variety of methods are
applied in their compilation. They are collected through censuses, surveys, and the
use of administrative records, but also from specific types of sources such as monitoring stations, remote sensing, and scientific research. The way of collecting data
from the specific types of sources differs considerably from the survey techniques
employed in social and economic statistics: from the environment to the production
of biophysical data describing natural resources and environmental quality.
1.4.4 Quality of Prediction and Model Validation
The interdisciplinary and inter-institutional characteristics of environment statistics
and the variety of data producers and users require collaboration among institutions,
practitioners, and experts in different fields. To effectively transform environmental
information into official environment statistics, the collaboration and coordination
of a significant number of actors and institutions is required. Institutions with strong
leadership and the skills and resources to facilitate multi-stakeholder processes are
required. Thus, institutional strengthening and inter-institutional collaboration and
coordination are inherent to environment statistics data production, processing, and
dissemination.
Environmental phenomena take place in dispersed manner, constantly over time
and across territories, as a fluid set of processes, each with different velocities. At
the primary sources, measuring and monitoring requires careful selection.
Transforming raw data from primary sources to statistics takes expertise and institutional capacities. Developing countries face budgetary constraints, and the funds
allocated to statistics are subject to restrictions. In general, environmental issues are
given a lower priority than social and economic statistics. The cost of monitoring
systems and remote sensing is falling over time, and some of the primary production
of raw data (in monitoring and remote sensing agencies) require the investment,
1 General Aspects of Environmental Degradation vs. Technological Development…