Heli Lu

More than carbon stocks: A case study of ecosystem-based benefits of REDD+ in Indonesia

During the 15th Conference of the Parties (COP 15), Parties agreed that reducing emissions from deforestation and forest degradation and enhancing ‘removals of greenhouse gas emission by forests’ (REDD+) in developing countries through positive incentives under the United Nations Framework Convention on Climate Change (UNFCCC) was capable of dealing with global emissions. As REDD+ seeks to lower emissions by stopping deforestation and forest degradation with an international payment tier according to baseline scenarios, opportunities for ecosystem benefits such as slowing habitat fragmentation, conservation of forest biodiversity, soil conservation may be also part of this effort. The primary objective of this study is to evaluate ecosystem-based benefits of REDD+, and to identify the relationships with carbon stock changes. To achieve this goal, high resolution satellite images are combined with Normalized Difference Vegetation Index (NDVI) to identify historical deforestation in study area of Central Kalimantan, Indonesia. The carbon emissions for the period of 2000–2005 and 2005–2009 are 2.73 × 105 t CO2 and 1.47 × 106 t CO2 respectively, showing an increasing trend in recent years. Dring 2005–2009, number of patches (NP), patch density (PD), mean shape index distribution (SHAPE_MN) increased 30.8%, 30.7% and 7.6%. Meanwhile, largest patch index (LPI), mean area (AREA_MN), area-weighted mean of shape index distribution (SHAPE_AM), neighbor distance (ENN_MN) and interspersion and juxtaposition index (IJI) decreased by 55.3%, 29.7%, 15.8%, 53.4% and 21.5% respectively. The area regarding as positive correlation between carbon emissions and soil erosion was approximately 8.9 × 103 ha corresponding to 96.0% of the changing forest. These results support the view that there are strong synergies among carbon loss, forest fragmentation and soil erosion in tropical forests. Such mechanism of REDD+ is likely to present opportunities for multiple benefits that fall outside the scope of carbon stocks.

Recent Observations of Human-induced Asymmetric Effects on Climate in Very High-Altitude Area

Like urban heat islands (UHI), human-induced land degradation (HLD) is a phenomenon attributed to human activities, but this phenomenon occurs in non-urban areas. Although a large body of work has demonstrated that land-cover change influences local climate systems, little work has been done on separating the impact of HLD from naturally-occurring fluctuations in very high-altitude areas. We developed an innovative NDVI-difference method in order to evaluate HLD effects upon the climate system in the central Tibet Plateau. The results show that the minimum temperature increased at a significantly faster pace than the maximum temperature in the growing season at HLD meteorological stations, but this was reversed at stations with natural forces only. Further analysis revealed that abrupt changes of minimum temperature occurred five years earlier and amplitudes of these changes were 1.4 times larger than at stations with natural forces only. Therefore, our results complement other evidence that points to the fact that local effects from UHI contribute to climatic asymmetry observed between minimum and maximum temperature trends. Accordingly, we stress the need for consideration of non-urban factors from anthropogenic activities, such as human-induced land degradation, in understanding these asymmetric diurnal changes.

Characteristics of the Temporal Variation in Temperature and Precipitation in China’s Lower Yellow River Region

We analyzed the spatial and temporal distributions of temperature and precipitation in China’s Yellow River Region between 1960 and 2001 by compiling meteorological data using anomalies, climate trend rate, linear regression, trend analysis, spline functions, and other methods. The results show that the average temperatures in the Region have an upward trend at a rate of 0.19°C every 10 years. There are no significant changes in the Region’s summers, but the winters have become visibly warmer, with the temperatures significantly increasing from the 1980s. The average annual precipitation rate has shown a downwards trend at a rate of −11.7 mm every 10 years. Even though the precipitation rate shows variations, the amount of precipitation is inconsistent with the most significant decrease in precipitation rates being seen during summer followed by autumn, while the rates actually slightly increased during spring and winter. Over the 42 years, the Region as a whole showed a trend of climate warming and drying with 77% of the total sites studied showing these combined trends. Before the 1980s, mainly a drying and cooling trend was observed. In the mid-to-late 80s the temperatures rose, resulting in the change to a warming and drying trend.

Multi-objective land use optimization based on low-carbon development using NSGA-II

Land use/land cover change (LUCC) caused by human beings is the main source of the increases of CO2 in the atmosphere. Land resource is not only the natural carrier of carbon emission of land ecosystems, but also the spatial carrier of carbon emission from human society. Human activity and its carbon emission intension have a very close relationship with the land use pattern, exploration on the low-carbon oriented land use scope, and land use structure can effectively reduce the rate of carbon emission, and also provides consults to low-carbon oriented land use planning. This paper presents a multi-objective land use optimization model based on low-carbon development. Carbon emission, economic benefit objectives, and constraint conditions are integrated into the multi-objectives optimization model of land use, and the model was solved with non-dominated sorting genetic algorithm-II (NSGA-II). And through providing weight coefficients to the objective functions, land use patterns in three scenarios (low-carbon, mid-carbon, high-carbon) were obtained.

Carbon, soil, and ecological benefits of REDD+ policies in Southwest China

Taking the Xishuangbanna district in Southwest China as the study region, we made a systematic and comprehensive evaluation of the carbon benefits and ecological benefits of the programme for reducing emissions from deforestation and forest degradation (REDD+) while enhancing forest carbon sequestration capacity in developing countries. It was found that carbon emissions in the study region increased and the landscape tended to fragment. Furthermore, the average carbon emissions of areas with severe soil erosion were more than 6 times higher than that of areas with minor erosion. These results indicate that REDD+ not only reduces carbon emissions caused by deforestation and forest degradation, but also provides other ecological benefits, such as mitigating forest fragmentation, preserving biodiversity, and conserving soil and water. From this perspective, REDD+ provides sustainable forest management and ecological benefits.

A novel approach to assess and monitor forests for REDD

Reducing emissions from deforestation and forest degradation, plus conservation of forest carbon stocks, sustainable management of forests, and enhancement of forest carbon stocks, is a set of steps designed to use market and financial incentives in order to reduce the emissions of greenhouse gases. The paper addresses the role of satellite remote sensing technologies as a tool for monitoring, assessment, reporting and verification of carbon credits. In particular, image fusion techniques were used to assess and monitor forests based on moderate resolution images of MODIS and TM data. The result showed that satellite image fusion could provide more spatial details and better spectral information compared with the original image and thus prove to be an excellent tool for monitoring carbon storage change for REDD.

Current remote sensing options for monitoring carbon emissions

Estimating carbon emissions from deforestation and forest degradation requires the expertise of forestry science, ecological modeling, statistics, remote sensing, and field measurement. In particular, remote sensing technology is capable of measurements of carbon contents of forest types, if supported by field information such as sample plots to calibrate the technology. In this paper current remote sensing options for monitoring carbon emissions were presented. We concluded that the combined application of optical and microwave remote sensing data is expected to provide an opportunity to estimate emissions both on a global scale and specifically in places where existing information is not reliable or consistent by overcoming their own current disadvantages.

Land use change monitoring on the process of urbanization in the Central Plains Economic Zone based on remote sensing and GIS technologies

Analysis of land use change for urban sprawl is of great value for the management of urban and rural planning and regional sustainable development. In this study, an important city of the Central Plains Economic Zone - Luoyang City was used as an example to explore the land use monitoring framework for the process of urbanization based on remote sensing and GIS technologies. At first, suitable classification systems of urban land information for the Central Plains Economic Zone was discussed. Then thematic maps of land use change in Luoyang City were extracted through the combination of computer automatic classification methods and visual interpretation. Finally, land use change due to urbanization in Luoyang City from 2006 to 2009 was analyzed. The results show that: the speed of urbanization of Luoyang City in the period 2006-2009 accelerated significantly. For example construction land area increased from 91350ha to 104193ha from 2006 to 2009, with a total change area of 12843ha and increased rate of 4281ha per year. The rate of construction land change increased by 47.11% than that in the period 2000-2006. The high growth rate, which was even higher than that in the same period in Zhengzhou City, shows that Luoyang City was in her stage of rapid urbanization in recent years.

Decade 1km resolution monthly temperature data for China

Air temperature near the surface is an important controlling parameter for land surface processes, and is crucial to ecological, environmental, and hydrological modeling. Temperature records observed at meteorological stations have been widely used, but there has been an increasing need for temperature data in grid for modeling especially those using remote sensing data. Although grid temperature can be estimated from in-situ temperature records using interpolation algorithm, low accuracy has been found in the estimation due to limited ground stations, especially when there were insufficient sites to represent all land cover types and terrain conditions in the area. NCEP/NCAR reanalysis project produced climate variables uses a frozen state-of-art global data assimilation system and a database as complete as possible. Although resolution of the NCEP data has a coarse resolution (0.5 degree), it provides global, consistent, and long term estimation of climate variables. This paper presents a downscaling approach for deriving monthly temperature at 1km resolution from the NCEP by utilizing derived relationships between monthly aggregated NCEP temperature and other ground elements, such as terrain, vegetation, and geographic locations. Regression tree model was chosen for detecting the possible relationships. Monthly temperature with 1km resolution for China land area has been produced using the approach. The final predicted temperatures were compared with observed records at 380 meteorological stations in China. The results indicated that the downscaled estimations can represent the spatial distribution and trends and the magnitude of temperature in inter-month, with R2ranging from 0.861 to 0.948, and RMSE from 1.88°C to 2.681°C.

Evaluation of land use classification accuracy based upon TM and CBERS-02B HR data fusion

Data fusions from SAR and TM, SPOT and TM, ASTER and TM, MODIS and ETM, etc are the common methods. But that from TM and CBERS-02B is rare. With HR camera working in September 19th 2007, Chinese-Brazil Earth Resources Satellite 02B (CBERS-02B) became the first civilian high-resolution satellite in China. It could provide 2.36m panchromatic image which is better to Landsat TM. Meanwhile the spectral resolution of TM is better than CBERS-02B. So its a good idea to take advantage of benefits from CBERS-02B HR and TM through data fusion. In this study, images of TM and CBERS-02B HR in 2007 were used as data sources. After image registration and noiseremoval process, data fusion methods of IHS and PCA were adopted. Then unsupervised classification and supervised classification were used for land use classification. Finally, classification accuracy between original image and fusion image was compared and evaluated. The result shows: (1) Compared with original TM or CBERS-02B HR image, the fusion image not only retains abundance spectrum but also enhances the object details. Residential texture, lake morphological, the relative position between roads, industrial and mining sites, etc, was identified easily. (2) Results from IHS and PCA are different. IHS image had higher spatial resolution but more spectral distortion. Spectral differences between some objects became smaller and classification accuracy was lower. Supervised classification accuracy assessment shows that overall Kappa index and overall land use classification accuracy decreased by 0.237 and 11% respectively. Meanwhile PCA image not only had high spatial resolution, but also smaller spectral distortion. Different land use / cover types can be better distinguished. (3) Disadvantages of low spatial resolution in TM and single color in CBERS-02B HR image are overcome in PCA fusion image to a certain extent. In this research under supervised classification in PCA image Kappa index of farm land, forest land and bare land increased by 0.097, 0.176 and 0.242 respectively. Overall Kappa index and overall land use classification accuracy were improved by 0.092 and 7.24% respectively.