Rapid economic development in the Asia and Pacific region has caused serious environmental degradation, such as decrease in forest area, desertification, salinisation, water resource depletion and soil loss. They become a serious constraint for a balanced and sustainable economic development in the region. In this situation, it is necessary to examine the present condition and changes in natural resources in order to take countermeasures against depletion and degradation.

The project »Asia-Pacific Environmental Innovation Strategy (APEIS)«, launched in 2001 by the Ministry of the Environment, Japan, aims at building the necessary scientific infrastructure to develop innovative policies for sustainable development, promote environmental co-operation and capacity building in the Asia-Pacific region, and propose an »Asia-Pacific model« for sustainable development. The National Institute for Environmental Studies (NIES) in Japan and the Institute for Geographical Sciences and Natural Resources Research (IGSNRR) of the Chinese Academy of Science have joined forces and set up collaborative research to develop a scientific environmental monitoring system, which will cover the whole Asia-Pacific region by using MODIS (Moderate Resolution Imaging Spectrometer) sensors mounted on a satellite (EOS-Terra) and include co-operative research with Asian and Oceania countries.

The monitoring system includes setting-up satellite data receiving stations, ground-truth observation sites for various ecosystems, and a data-analysing network; integrated monitoring of environmental degradation and disasters; and integrated modelling of land-atmospheric processes and ecological functions at watershed scale. Implementing this integrated monitoring system will allow monitoring of the state of ground cover over time, soil erosion, water resources, environmental disasters and agricultural production.

APEIS Integrated Monitoring System

The system is composed of three satellite data-receiving stations of Terra-MODIS in Beijing, Urumqi and Singapore (National University of Singapore), which cover the entire Asia-Pacific region, two data-analysing centres in IGSNRR and NIES, and five ground-truth monitoring stations at Yucheng in Shandong Province, Fukang in the Xinjiang Vigor Autonomous Region, Taoyuan in Hunan Province, Haibei in Qinghai Province and Qianyanzhou in Jiangxi Province, China. The Data Analysis Center has stored a database including satellite data (MODIS, LANDSAT, ASTER, TRMM, etc.), GIS data, and measurements of ground-truth ecological stations.

The receiving station in Beijing was set up in February 2001; another station in Urumqi was completed in April 2002. The two stations can receive data twice a day covering a vast area including Japan, China, Mongolia, Korea and Western Asia. Data (about 3GB/per day) received by Urumqi station are transported daily via a network cable to the Data Analysis Center in IGSNRR, China, where the data of two stations are referenced and corrected geometrically and then merged. The merged data (about 6GB/per day) is stored and sent to the Data Analysis Center in NIES, Japan. The data provide a possibility for up-to-date monitoring of land-cover changes and developing an integrated model for environmental assessment in the Asia-Pacific Region.

MODIS is the key instrument aboard the Terra satellite that is viewing the entire Earth’s surface every 1 to 2 days, acquiring data in 36 spectral bands between 0.405 and 14.385 µm, and at three spatial resolutions – 250m (Bands 1-2), 500m (Bands 3-7), and 1,000m (Bands 8-36). The MODIS Science Team, NASA, has already developed 44 products (MOD01-MOD44), but most of them have not yet been completely calibrated or validated by ground-truth data in various ecological systems. Developing the next-generation of high quality data sets for the study of regional environmental change and ecological system assessment is our next challenge. The concrete tasks include the following aspects: validation of (1) Land Surface Temperature; (2) Land Surface Reflectance and Albedo; (3) Snow Cover; (4) Leaf Area Index - LAI/FPAR; (5) Vegetation Indices with Surface Flux Applications; (6) Terrestrial Carbon Cycle; (7) Net Primary Productivity.

Long-term measurements of water vapour, energy exchange, and carbon dioxide from a variety of ecosystems in Haibei (grass land), Yucheng (dry field), Taoyuan (paddy field), Qianyanzhou (forest) and Fukang (semi-arid) are integrated into a consistent, quality-assured and documented dataset. The dataset includes micrometeorological factors, eddy covariance fluxes, vegetation characteristics, and soil physical and chemical properties.

Integrated Monitoring of Disasters and Environmental Degradation

In eastern Asia, serious disasters occur frequently on large regional scales due to environmental degradation. For example, dust storms have occurred every year in spring and their number has increased in the past decades. The scale of dust storms has become wider and the damage they cause has increased each year. Meanwhile, desertification and grassland degradation in these areas are becoming more severe due to human-driven factors, such as over-cultivation, over-grazing, over-exploitation, and misuse of water resources. Satellite observation provides a possibility to monitor these phenomena in time.

Another example is soil moisture, which plays the most important role in the soil-vegetation-atmosphere continuum. However, it is one of the factors that are most difficult to estimate at a regional scale because of the heterogeneity of land surface characteristics. As most studies determining soil moisture address observational data analysis and biophysical mechanism modelling at a point or a micro-scale, an upscaling to a regional or a macro-scale is very difficult. Satellite data provide a great potential for solving this problem.

The APEIS Integrated Monitoring System will be used to monitor both natural and human-driven disasters, such as dust storms, air pollution, floods, marine pollution, fires, oil spills, earthquake damage, algal blooms and damage from insects. At the same time, environmental degradation can be monitored by a set of indices, such as (1) Aerosol Index (ASI), (2) Snow Cover Area Index (SCAI); (3) Desertified Area Index (DAI); (4) Land Use/Cover Change (LUCC); (5) Water Deficit Index (WDI), and (6) Vegetation Index (VI).

Integrated Modelling of Ecological Functions and Sustainability

There is an emerging need to support policy formulation and decision-making in environmental management at very large geographic scales. Typical issues include global change impact assessment and formulation of mitigating measures, water resource allocation in a river basin at sub-continental scale, and environmental impact assessment of agriculture activities in large river basins. In order to develop a decision support system, biophysical processes and human interactions have to be modelled. For example, the model should simulate how environmental changes, such as climate change and soil erosion, may influence crop yield, and how the changes in cropping pattern, cultivation intensity and management practices may affect the environment over time. For sound management and decision making for sustainable development of the Changjiang river catchment in China, the catchment-based ecosystem assessment, emphasising the hydro-biogeochemical processes and ecosystem function, has been accepted in the Millennium Ecosystem Assessment (MEA). Its objective focuses mainly on answering the following questions in the MEA framework: 1) what are the major pressures on the ecosystem function? 2) What are the major impacts on the ecosystem function, goods and services, such as water, food, biodiversity, carbon sequestration and flood protection? 3) What kind of policy can be implemented in order to achieve sustainability in the Changjiang river catchment?

To answer the above questions, it is necessary to develop a catchment-based integrated model to estimate the spatial and temporal distributions of the water cycle, carbon cycle, heat fluxes, elements and nutrient cycles, sediment transport as well as land productivity on regional and watershed scales. An integrated methodology to predict land use/cover changes due to both natural factors and socio-economic driving forces will be included. By using the integrated model, the future impacts on the ecosystem function will be predicted based on scenarios, such as 1) the decrease in crop production due to water cycle change, and 2) the increase in soil erosion, desertification, dust storms and flood events due to the land use/cover changes.

Masataka Watanabe, Shogo Murakami, Qinxue Wang, and Seiji Hayashi are researchers at the National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan; masawata@nies.go.jp; http://www.nies.go.jp

Jiyuan Liu is with the Institute for Geographical Sciences and Natural Resources Research, Chinese Academy of Science, China.