Impact Analysis of Land Use and Land Cover Change on Karez in Turpan Basin of China

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Abstract

Karez systems are ancient hydraulic works that use underground waterways to divert water by gravity and have historically been popular in arid regions across Central Asia. Karez systems have undergone thousands of years of development and have been used for irrigation in 40 countries and regions worldwide. Although there are different opinions about the origin of karezes, the role and significance of karezes are similar. The Turpan Basin is a relatively closed inland basin in China, far from the ocean, with a very dry climate and high evaporation rates. However, due to the ice and snow meltwater of the Tianshan Mountains, the groundwater resources in the basin are abundant. Karezes are an important support for Turpan’s farming civilization and tourism culture and represent a great masterpiece of how people in arid areas have used the natural environment. This study used historical CORONA images to visually interpret the karez system in the 1970s and compared it with the karez system in 2020 to analyze the spatial distribution variation characteristics of the karezes. The impact of land use/land cover change on the karezes was also analyzed. The results showed that from 1970 to 2020, as the population grew, there was an increase in arable land and built-up areas while the water area decreased. In general, the increase in arable land and built-up areas, the decrease in water area, and the increase in the number of electromechanical wells have combined to reduce the number of karez systems. Based on the CORONA image from 1970, it is possible to visualize the shaft area that existed in 1970 but did not exist in 2020. Some karez shafts that existed in bare terrain areas in 1970 were truncated when the land use/land cover type changed to arable land. The area where the disappeared karez shafts were located is approximately 87.77 square kilometers. Through the study of the changes in the spatial distribution of karezes and the impact of land use/land cover change on karezes, this research provides a valuable reference for the construction of karez conservation areas or urban planning. The investigation of the distribution of historical karezes is of great significance for studying the changes in karezes and excavating the historical and cultural value of karezes.

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Global land cover mapping at 30m resolution: A POK-based operational approach

Lijun Chen, Xuehong Chen, Chaoying He … (2015)

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The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019

Jie Yang, Xin Huang (2021)

Abstract. Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's spheres. Accurate LC information is a fundamental parameter for the environment and climate studies. Considering that the LC in China has been altered dramatically with the economic development in the past few decades, sequential and fine-scale LC monitoring is in urgent need. However, currently, fine-resolution annual LC dataset produced by the observational images is generally unavailable for China due to the lack of sufficient training samples and computational capabilities. To deal with this issue, we produced the first Landsat-derived annual China land cover dataset (CLCD) on the Google Earth Engine (GEE) platform, which contains 30 m annual LC and its dynamics in China from 1990 to 2019. We first collected the training samples by combining stable samples extracted from China's land-use/cover datasets (CLUDs) and visually interpreted samples from satellite time-series data, Google Earth and Google Maps. Using 335 709 Landsat images on the GEE, several temporal metrics were constructed and fed to the random forest classifier to obtain classification results. We then proposed a post-processing method incorporating spatial–temporal filtering and logical reasoning to further improve the spatial–temporal consistency of CLCD. Finally, the overall accuracy of CLCD reached 79.31 % based on 5463 visually interpreted samples. A further assessment based on 5131 third-party test samples showed that the overall accuracy of CLCD outperforms that of MCD12Q1, ESACCI_LC, FROM_GLC and GlobeLand30. Besides, we intercompared the CLCD with several Landsat-derived thematic products, which exhibited good consistencies with the Global Forest Change, the Global Surface Water, and three impervious surface products. Based on the CLCD, the trends and patterns of China's LC changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and grassland (−3.29 %), and increase in forest (+4.34 %). In general, CLCD reflected the rapid urbanization and a series of ecological projects (e.g. Gain for Green) in China and revealed the anthropogenic implications on LC under the condition of climate change, signifying its potential application in the global change research. The CLCD dataset introduced in this article is freely available at https://doi.org/10.5281/zenodo.4417810 (Yang and Huang, 2021).

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Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015)

Shushi Peng, Natasha MacBean, Wei Li … (2018)

Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km 2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km 2 respectively, resulting in a net forest loss of 0.6 million km 2 , mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Sect. 5). The PFT map translation protocol and an example in 2000 can be downloaded from https://doi.org/10.5281/zenodo.834229 . The annual ESA CCI PFT maps from 1992 to 2015 at 0.5° × 0.5° resolution can also be downloaded from https://doi.org/10.5281/zenodo.1048163 .