Zhiming Feng

Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) Sensors

Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) are currently operational for routine Earth observation. There are substantial differences between instruments onboard both satellites. The enhancements achieved with Landsat-8 refer to the scanning technology (replacing of whisk-broom scanners with two separate push-broom OLI and TIRS scanners), an extended number of spectral bands (two additional bands provided) and narrower bandwidths. Therefore, cross-comparative analysis is very necessary for the combined use of multi-decadal Landsat imagery. In this study, 3,311 independent sample points of four major land cover types (primary forest, unplanted cropland, swidden cultivation and water body) were used to compare the spectral bands of ETM+ and OLI. Eight sample plots with different land cover types were manually selected for comparison with the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), the Land Surface Water Index (LSWI) and the Normalized Burn Ratio (NBR). These indices were calculated with six pairs of ETM+ and OLI cloud-free images, which were acquired over the border area of Myanmar, Laos and Thailand just two days apart, when Landsat-8 achieved operational obit. Comparative results showed that: (1) the average surface reflectance of each band differed slightly, but with a high degree of similarities between both sensors. In comparison with ETM+, the OLI had higher values for the near-infrared band for vegetative land cover types, but lower values for non-vegetative types. The new sensor had lower values for the shortwave infrared (2.11–2.29 µm) band for all land cover types. In addition, it also basically had higher values for the shortwave infrared (1.57–1.65 µm) band for non-water land cover types. (2) The subtle differences of vegetation indices derived from both sensors and their high linear correlation coefficient (R2 > 0.96) demonstrated that ETM+ and OLI imagery can be used as complementary data. (3) LSWI and NBR performed better than NDVI and MNDWI for cross-comparison analysis of satellite sensors, due to the spectral band difference effects.

A review of swidden agriculture in Southeast Asia

Swidden agriculture is by far the dominant land use system in the mountainous regions of Southeast Asia (SEA). It provides various valuable subsistence products to local farmers, mostly the poor ethnic minority groups. Controversially, it is also closely connected with a number of environmental issues. With the strengthening regional economic cooperation in SEA, swidden agriculture has experienced drastic transformations into other diverse market-oriented land use types since the 1990s. However, there is very limited information on the basic geographical and demographic data of swidden agriculture and the socio-economic and biophysical effects of the transformations. International programs, such as the Reducing Emissions from Deforestation and forest Degradation (REDD), underscore the importance of monitoring and evaluating swidden agriculture and its transition to reduce carbon emission due to deforestation and forest degradation. In this context, along with the accessibility of Landsat historical imagery, remote sensing based techniques will offer an effective way to detect and monitor the locations and extent of swidden agriculture. Many approaches for investigating fire occurrence and burned area can be introduced for swidden agriculture mapping due to the common feature of fire relatedness. In this review paper, four broad approaches involving spectral signatures, phenological characteristics, statistical theory and landscape ecology were summarized for swidden agriculture delineation. Five research priorities about swidden agriculture involving remote sensing techniques, spatial pattern, change, drivers and impacts were proposed accordingly. To our knowledge, a synthesis review on the remote sensing and outlook on swidden agriculture has not been reported yet. This review paper aims to give a comprehensive overview of swidden agriculture studies in the domains of debated definition, trends, remote sensing methods and outlook research in SEA undertaken in the past two decades.

Changes in rice cropping systems in the Poyang Lake Region, China during 2004–2010

Rice cropping systems not only characterize comprehensive utilization intensity of agricultural resources but also serve as the basis to enhance the provision services of agro-ecosystems. Yet, it is always affected by external factors, like agricultural policies. Since 2004, seven consecutive No.1 Central Documents issued by the Central Government have focused on agricultural development in China. So far, few studies have investigated the effects of these policies on the rice cropping systems. In this study, based upon the long-term field survey information on paddy rice fields, we proposed a method to discriminate the rice cropping systems with Landsat data and quantified the spatial variations of rice cropping systems in the Poyang Lake Region (PLR), China. The results revealed that: (1) from 2004 to 2010, the decrement of paddy rice field was 46.76 km2 due to the land use change. (2) The temporal dynamics of NDVI derived from Landsat historical images could well characterize the temporal development of paddy rice fields. NDVI curves of single cropping rice fields showed one peak, while NDVI curves of double cropping rice fields displayed two peaks annually. NDVI of fallow field fluctuated between 0.15 and 0.40. NDVI of the flooded field during the transplanting period was relatively low, about 0.20±0.05, while NDVI during the period of panicle initiation to heading reached the highest level (above 0.80). Then, several temporal windows were determined based upon the NDVI variations of different rice cropping systems. (3) With the spatial pattern of paddy rice field and the NDVI threshold within optimum temporal windows, the spatial variation of rice cropping systems was very obvious, with an increased multiple cropping index of rice about 20.2% from 2004 to 2010. The result indicates that agricultural policies have greatly enhanced the food provision services in the PLR, China.

Relief degree of land surface and its influence on population distribution in China

The relief degree of land surface (RDLS) is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the entire country. Based on the concept and macro-scale digital elevation model datum and ARC/INFO software, the RDLS at a 10 km×10 km grid size of China is extracted. This paper depicts systemically the spatial distributions of RDLS through analyzing the ratio structure and altitudinal characters of RDLS in China. The conclusions are drawn as follows: the RDLS in more than 63% of the area is less than one (1) (relative altitude is less than 500 m), reflecting the fact that most of RDLS in China is low. In general, the RDLS in the west is larger than that in the east and so is the south than that of the north in China. The RDLS decreases with the increase of longitude and latitude and the change of RDLS at the latitudes of 28°N, 35°N, 42°N, as well as at the longitudes of 85°E, 102°E, 115°E could reflect the three major ladders of China. In the vertical direction, the RDLS increases with the increase of altitude. Analysis of the correlation between RDLS and population distribution in China and its regional difference shows that the R2 value between RDLS and population density is 0.91 and RDLS is an important factor influencing the spatial distribution of population. More than 85% of the people in China live in areas where the RDLS is less than one (1), while the population in areas with RDLS greater than 3 accounts only for 0.57% of the total. The regional difference of correlation between RDLS and population within China is significant and such correlation is significant in Central China and South China and weak in Inner Mongolia and Tibet.

Rubber plantation and its relationship with topographical factors in the border region of China, Laos and Myanmar

Rubber plantation is the major land use type in Southeast Asia. Monitoring the spatial-temporal pattern of rubber plantation is significant for regional land resource development, eco-environmental protection, and maintaining border security. With remote sensing technologies, we analyzed the rubber distribution pattern and spatial-temporal dynamic; with GIS and a newly proposed index of Planted Intensity (PI), we further quantified the impacts and limits of topographical factors on rubber plantation in the border region of China, Laos and Myanmar (BRCLM) between 1980 and 2010. The results showed that: (1) As the dominant land use type in this border region, the acreage of rubber plantation was 6014 km2 in 2010, accounting for 8.17% of the total area. Viewing from the rubber plantation structure, the ratio of mature- (≥10 year) and young rubber plantation (<10 year) was 5:7. (2) From 1980 to 2010, rubber plantation expanded significantly in BRCLM, from 705 km2 to 6014 km2, nearly nine times. The distribution characteristics of rubber plantation varied from concentrated toward dispersed, from border inside to outside, and expanded further in all directions with Jinghong City as the center. (3) Restricted by the topographical factors, more than 4/5 proportion of rubber plantation concentrated in the appropriate elevation gradients between 600 and 1000 m, rarely occurred in elevations beyond 1200 m in BRCLM. Nearly 2/3 of rubber plantation concentrated on slopes of 8°–25°, rarely distributed on slopes above 35°. Rubber plantation was primarily distributed in south and east aspects, relatively few in north and west aspects. Rubber planted intensity displayed the similar distribution trend. (4) Comparative studies of rubber plantation in different countries showed that there was a remarkable increase in area at higher elevations and steeper slopes in China, while there were large appropriate topographical gradients for rubber plantation in Laos and Myanmar which benefited China for rubber trans-boundary expansion. (5) Rubber plantation in BRCLM will definitely expend cross borders of China to the territories of Laos and Myanmar, and the continuous expansion in the border region of China will be inevitable.

Monitoring the spatio-temporal dynamics of swidden agriculture and fallow vegetation recovery using Landsat imagery in northern Laos

Swidden agriculture is an age-old, widespread but controversial farming practice in Montane Mainland Southeast Asia (MMSEA). In the uplands of northern Laos, swidden agriculture has remained a predominant human-dominated land-use type for centuries. However, swidden system has undergone dramatic transformations since the mid-1990s. Debates on changes in swidden cultivation are linked to globally critical issues, such as land use/cover changes (LUCC), biodiversity loss and environmental degradation. Since the implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD), much attention has been paid nationally and internationally to swidden agriculture in the tropics. However, knowledge of the explicitly spatial characteristics of swidden agriculture and the consequences of these transitions at macroscopic scale is surprisingly scarce. In this study, the intensity of swidden use and fallow forest recovery in northern Laos in 1990, 2002, and 2011 were delineated by means of Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM+) imagery (30 m) using a decision tree classification approach, followed by an analysis of the spatio-temporal changes in swidden agriculture. Next, annual successive TM/ETM+ images during 2000–2010 were used to delineate the dynamics of the burning and cropping phase. Subsequently, the burned pixels identified in 2000 were compared respectively with their counterparts in the following years (2001–2011) to investigate temporal trends, land-use frequency, and the swidden cycle using time-series Landsat-based Normalized Difference Vegetation Index (NDVI) data. Finally, as the swidden cycle changed from 1 to 11 years, the fallow vegetation recovery process was studied. The results showed that: (1) from 1990 to 2011, the area of swidden agriculture increased by 54.98%, from 1.54×105 ha to 2.38×105 ha in northern Laos. The increased swidden cultivation area was mainly distributed in Luang Prabang and southern Bokeo, whereas the decreased parts were mainly found in Phongsali; (2) swidden agriculture increased mainly at elevations of 500–800 m, 300–500 m, and 800–1000 m and on slopes of 10°–20° and 20°–30°. Over 80% of swidden fields were transformed from forests; (3) during 2000–2011, the frequency of swidden use in northern Laos was about two or three times. The interval between two successive utilization of a swidden ranged from one to seven years. Comparison of swidden cycles and the related proportions of swidden farming in 2000, 2003, and 2007 revealed that swidden cycles in most areas were shortened; and (4) there was a significant correlation (0.97) between fallow vegetation recovery and the swidden cycle. The NDVI of regenerated vegetation could approach the average level of forest when the swidden cycle reached 10 years.

Extent and Area of Swidden in Montane Mainland Southeast Asia: Estimation by Multi-Step Thresholds with Landsat-8 OLI Data

Information on the distribution, area and extent of swidden agriculture landscape is necessary for implementing the program of Reducing Emissions from Deforestation and Forest Degradation (REDD), biodiversity conservation and local livelihood improvement. To our knowledge, explicit spatial maps and accurate area data on swidden agriculture remain surprisingly lacking. However, this traditional farming practice has been transforming into other profit-driven land use, like tree plantations and permanent cash agriculture. Swidden agriculture is characterized by a rotational and dynamic nature of agroforestry, with land cover changing from natural forests, newly-cleared swiddens to different-aged fallows. The Operational Land Imager (OLI) onboard the Landsat-8 satellite has visible, near-infrared and shortwave infrared bands, which are sensitive to the changes in vegetation cover, land surface moisture content and soil exposure, and therefore, four vegetation indices (VIs) were calculated, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), the Normalized Burn Ratio (NBR) and the Soil Adjusted Vegetation Index (SAVI). In this study, we developed a multi-step threshold approach that uses a combination of thresholds of four VIs and local elevation range (LER) and applied it to detect and map newly-opened swiddens and different-aged fallows using OLI imagery acquired between 2013 and 2015. The resultant Landsat-derived swidden agriculture maps have high accuracy with an overall accuracy of 86.9% and a Kappa coefficient of 0.864. The results of this study indicated that the Landsat-based multi-step threshold algorithms could potentially be applied to monitor the long-term change pattern of swidden agriculture in montane mainland Southeast Asia since the late 1980s and also in other tropical regions, like insular Southeast Asia, South Asia, Latin America and Central Africa, where swidden agriculture is still common.

The change in population density from 2000 to 2010 and its influencing factors in China at the county scale

Studying the change in population distribution and density can provide important basis for regional development and planning. The spatial patterns and driving factors of the change in population density in China were not clear yet. Therefore, using the population census data in 2000 and 2010, this study firstly analyzed the change of population density in China and divided the change in all 2353 counties into 4 types, consisting of rapid increase, slow increase, slow decrease and rapid decrease. Subsequently, based on the partial least square (PLS) regression method, we recognized the significant factors (among 11 natural and social-economic factors) impacting population density change for the whole country and counties with different types of population change. The results showed that: (1) compared to the population density in 2000, in 2010, the population density in most of the counties (over 60%) increased by 21 persons per km2 on average, while the population density in other counties decreased by 13 persons per km2. Of all the 2353 counties, 860 and 589 counties respectively showed rapid and slow increase in population density, while 458 and 446 counties showed slow and rapid decrease in population density, respectively. (2) Among the 11 factors, social-economic factors impacted population density change more significantly than natural factors. The higher economic development level, better medical condition and stronger communication capability were the main pull factors of population increase. The dense population density was the main push factor of population decrease. These conclusions clarified the spatial pattern of population change and its influencing factors in China over the past 10 years and could provide helpful reference for the future population planning.

Measuring directional urban spatial interaction in China: A migration perspective

The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China’s urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities.

Monitoring phenological stages of swiddening in northern Laos during the dry season

Swidden cultivation is a unique land use category and has undergone rapid transitions in the uplands of Mainland Southeast Asia. Monitoring the scale and magnitude of changes is very challenging due to the year-to-year fluctuations of land cover, which substantially constrains our understanding of the interactions between swidden system and the implementation of Reducing Emissions from Deforestation and forest Degradation (REDD) and its environmental effects. In this study, annual time-series of Landsat TM/ETM+ images in 2005 and 2012-2013 were used to observe the temporal development of swidden practice during the dry season. Three vegetation indices including Normalized Difference Vegetation Index (NDVI), Land Surface Water Index (LSWI) and Normalized Burn Ratio (NBR) were applied to characterize the different development phases (from pre-felling, felling/slashing, sun-air drying, burning to post-burn) at both the pixel and landscape levels. The results showed that: 1) the swidden system in the uplands of Laos generally starts the felling/slashing stage in mid-late February, keeps sun/air drying in whole March, and enters into the burning phase in April. The pre-felling phase usually ends in early February. 2) NDVI and LSWI were more sensitive to detect the changes of vegetation and moisture content from pre-felling to sun/air drying phase while NBR is more sensitive to detect fire-related disturbance. 3) The differences of NBR between pre-felling and post-burn phase were much bigger than those of NDVI and LSWI, which indicates the NBR as a potentially effective tool for detecting and mapping the spatio-temporal changes of swidden farming.