Browsing by Author "Luo, Kaisheng"

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Attribution of hydrological change in Heihe River Basin to climate and land use change in the past three decades
(Nature Portfolio, 2016-09-20) Luo, Kaisheng
The contributions of climate and land use change (LUCC) to hydrological change in Heihe River Basin (HRB), Northwest China were quantified using detailed climatic, land use and hydrological data, along with the process-based SWAT (Soil and Water Assessment Tool) hydrological model. The results showed that for the 1980s, the changes in the basin hydrological change were due more to LUCC (74.5%) than to climate change (21.3%). While LUCC accounted for 60.7% of the changes in the basin hydrological change in the 1990s, climate change explained 57.3% of that change. For the 2000s, climate change contributed 57.7% to hydrological change in the HRB and LUCC contributed to the remaining 42.0%. Spatially, climate had the largest effect on the hydrology in the upstream region of HRB, contributing 55.8%, 61.0% and 92.7% in the 1980s, 1990s and 2000s, respectively. LUCC had the largest effect on the hydrology in the middle-stream region of HRB, contributing 92.3%, 79.4% and 92.8% in the 1980s, 1990s and 2000s, respectively. Interestingly, the contribution of LUCC to hydrological change in the upstream, middle-stream and downstream regions and the entire HRB declined continually over the past 30 years. This was the complete reverse (a sharp increase) of the contribution of climate change to hydrological change in HRB.
Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China
(Wiley, 2016-07-27) Luo, Kaisheng
Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET0) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET0 was driven mainly by wind speed. ET0 was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd.
Comparison of two object-oriented technologies for detecting land use change
(Springer Science+Business Media, 2021) Luo, Kaisheng
Fine Monitoring of Wetlands at Provincial Large-Scale Using Object-Based Technique and Medium-Resolution Image
(Institute of Electrical and Electronics Engineers, 2019-06-12) Luo, Kaisheng
Due to extreme similarity of wetland spectra, a significant uncertainty lies in the accuracy of the traditional pixel-based classification, which is a bottleneck in the extraction of wetland information. Object-based image analysis (OBIA) has brought opportunity for fine monitoring of wetland information. However, previous studies on monitoring wetlands have focused mainly on exploratory experiments involving high-resolution images for small areas. The application of OBIA in various medium-resolution images for large areas needs further verification. Here, Landsat and China's HJ-CCD images, a new OBIA mixed binary decision tree, tasseled cap transformation, and field samples were used to refine monitoring of changes in wetlands in Hubei Province. The results showed that while the overall accuracy and Kappa coefficient of the extracted wetland information for 2000 were, respectively, 88.98% and 0.87, the overall accuracy and Kappa coefficient of the detected change were 94.75% and 89.41. This indicated that OBIA performed well with medium-resolution HJ-CCD and Landsat images in monitoring changes in wetlands at provincial scale. The area of wetlands in Hubei increased by 171.03 km2during 2000-2010. Lakes and reservoirs/ponds increased the most in the province, with respective contributions to the total wetland area of 40.21% (108.97 km2) and 59.17% (160.37 km2). At administrative unit scale, Shiyan Prefecture (157.53 km2) and Fangxian County (317.33 km2) contributed the most to the increase of wetland area. The main reason for the increase in wetland area in Hubei in 2000-2010 was the implementation of major ecological projects during that decade.
Monitoring Land-Use/Land-Cover Changes at a Provincial Large Scale Using an Object-Oriented Technique and Medium-Resolution Remote-Sensing Images
(Multidisciplinary Digital Publishing Institute, 2018-12-12) Luo, Kaisheng
An object-based image analysis (OBIA) technique is replacing traditional pixel-based methods and setting a new standard for monitoring land-use/land-cover changes (LUCC). To date, however, studies have focused mainly on small-scale exploratory experiments and high-resolution remote-sensing images. Therefore, this study used OBIA techniques and medium-resolution Chinese HJ-CCD images to monitor LUCC at the provincial scale. The results showed that while woodland was mainly distributed in the west, south, and east mountain areas of Hunan Province, the west had the largest area and most continuous distribution. Wetland was distributed mainly in the northern plain area, and cultivated land was distributed mainly in the central and northern plains and mountain valleys. The largest impervious surface was the Changzhutan urban agglomerate in the northeast plain area. The spatial distribution of land cover in Hunan Province was closely related to topography, government policy, and economic development. For the period 2000–2010, the areas of cultivated land transformed into woodland, grassland, and wetland were 183.87 km2, 5.57 km2, and 70.02 km2, respectively, indicating that the government-promoted ecologically engineered construction was yielding some results. The rapid economic growth and urbanization, high resource development intensity, and other natural factors offset the gains made in ecologically engineered construction and in increasing forest and wetland areas, respectively, by 229.82 km2 and 132.12 km2 from 2000 to 2010 in Hunan Province. The results also showed large spatial differences in change amplitude (LUCCA), change speed (LUCCS), and transformation processes in Hunan Province. The Changzhutan urban agglomerate and the surrounding prefectures had the largest LUCCA and LUCCS, where the dominant land cover accounted for the conversion of some 189.76 km2 of cultivated land, 129.30 km2 of woodland, and 6.12 km2 of wetland into impervious surfaces in 2000–2010. This conversion was attributed to accelerated urbanization and rapid economic growth in this region.
Rapid monitoring of abandoned farmland and information on regulation achievements of government based on remote sensing technology
(Elsevier BV, 2022-02-24) Luo, Kaisheng
Sensitivity of the land surface hydrological cycle to human activities in China
(Elsevier BV, 2022-04-06) Luo, Kaisheng
Transfer of Virtual Water of Woody Forest Products from China
(Multidisciplinary Digital Publishing Institute, 2018-02-05) Luo, Kaisheng
Global freshwater resources are under increasing pressure. It is reported that international trade of water-intensive products (the so-called virtual water trade) can be used to ease global water pressure. In spite of the significant amount of international trade of woody forest products, virtual water of woody forest products (VWWFP) and the corresponding international trade are largely ignored. However, virtual water research has progressed steadily. This study maps VWWFP and statistically analyzes China’s official data for the period 1993–2014. The results show a rapid increase in the trend of VWWFP flow from China, reaching 7.61 × 1012 m3 or 3.48 times annual virtual water trade for agricultural products. The export and import volumes of China are respectively 1.27 × 1012 m3 and 6.34 × 1012 m3 for 1993–2014. China imported a total of 5.07 × 1012 m3 of VWWFP in 1993–2014 to lessen domestic water pressure, which is five times the annual water transfer via China’s South–North Water Transfer project. Asia and Europe account for the highest contribution (50.52%) to China’s import. Other contributors include the Russian Federation (16.63%), Indonesia (13.45%), Canada (13.41%), the United States of America (9.60%), Brazil (7.23%) and Malaysia (6.33%). China mainly exports VWWFP to Asia (47.68%), North America (23.24%), and Europe (20.01%). The countries which export the highest amount of VWWFP include the United States of America, Japan, Republic of Korea and Canada. Then the countries which import the highest amount of VWWFP include the Russian Federation, Canada, United States of America, and Brazil. The VWWFP flow study shows an obvious geographical distribution that is driven by proximity and traffic since transportation cost of woody forest products could be significant.
When to Detect Changes in Object-Based Image Analysis: Before or after Classification?
(2017-09-29) Luo, Kaisheng
This study compared two object-oriented land use change detection methods—detection after classification (DAC) and classification after detection (CAD) —based on a digital elevation model, slope data, and multi-temporal Landsat images (TM image for 2000 and ETM image for 2010). We noted that the overall accuracy of the DAC (86.42%) was much higher than that of the CAD (71.71%). However, a slight difference between the accuracies of the two methods exists for deciduous broadleaf forest, evergreen coniferous forest, mixed wood, upland, paddy, reserved land, and settlement. Owing to substantial spectrum differences, these land use types can be extracted using spectral indexes. The accuracy of DAC was much higher than that of CAD for industrial land, traffic land, green shrub, reservoir, lake, river, and channel, all of which share similar spectrums. The discrepancy was mainly because DAC can completely utilize various forms of information apart from spectrum information during a two-stage classification. In addition, the change-area boundary was not limited at first, but was adjustable in the process of classification. DAC can overcome smoothing effects to a great extent using multi-scale segmentations and multi-characters in detection. Although DAC yielded better results, it was more time-consuming (28 days) because it uses a two-stage classification approach. Conversely, CAD consumed less time (15 days). Thus, a hybrid of the two methods is recommended for application in land use change detection.