First comprehensive quantification of annual land use/cover from 1990 to 2020 across mainland Vietnam

Abstract

Extensive studies have highlighted a need for frequently consistent land cover information for interdisciplinary studies. This paper proposes a comprehensive framework for the automatic production of the first Vietnam-wide annual land use/land cover (LULC) data sets (VLUCDs) from 1990 to 2020, using available remotely sensed and inventory data. Classification accuracies ranged from 85.7 ± 1.3 to 92.0 ± 1.2% with the primary dominant LULC and 77.6 ± 1.2% to 84.7 ± 1.1% with the secondary dominant LULC. This confirmed the potential of the proposed framework for systematically long-term monitoring LULC in Vietnam. Results reveal that despite slight recoveries in 2000 and 2010, the net loss of forests (19,940 km2) mainly transformed to croplands over 30 years. Meanwhile, productive croplands were converted to urban areas, which increased approximately ten times. A threefold increase in aquaculture was a major driver of the wetland loss (1914 km2). The spatial–temporal changes varied, but the most dynamic regions were the western north, the southern centre, and the south. These findings can provide evidence-based information on formulating and implementing coherent land management policies. The explicitly spatio-temporal VLUCDs can be benchmarks for global LULC validation, and utilized for a variety of applications in the research of environmental changes towards the Sustainable Development Goals.

A review of Google Earth Engine application in mapping aquaculture ponds

“…Next, Random Forest Classifiers were used for aquaculture area mapping in the Pearl River Basin, with an overall accuracy of 89.5%. Phan et al [26] developed a framework to monitor the yearly LULC of Vietnam over the past 3 decades. Landsat and Sentinel SAR images were obtained and pre-processed on GEE and used the Random Forest classifier to obtain the area of LULC classes, one of which is the aquaculture area.…”

Revealing the Land Use Volatility Process in Northern Southeast Asia

“…Different land use types will directly affect land use volatility [37]. Considering there is a large number of shifting cultivation behaviors in the study area, in order to veal the relationship between land use volatility and current land use/cover types (tha land use types in 2018), dividing land use types into land cover types closely relate shifting cultivation could be more feasible, considering the local land use characteris The land classification results were derived from our previous research [36].…”

“…Considering the agglomeration effect of land use [36], in order to analyze the impact of large land use volatility on the surrounding land, we measured the distance from small land use volatility (NBR < 500, that is, the change values of NBR were less than 500, the same below) to large land use volatility (NBR > 500), and finally completed the cluster/outlier analysis of land use volatility. Land use/cover types also have a significant impact on land use volatility [37], both in terms of change cycle and change time. Therefore, we further coupled the spatial relationship between the latest land use types and different land use volatility to reveal how land use affected the land use volatility (Figure 4).…”

Spatio-temporal Analysis of Land Use/Land Cover Changes in Urban Forest Ecosystem

“…LULC studies are effective in providing valuable data needed for the assessment of qualitative and quantitative changes brought by human activities that have an adverse bearing on the forest ecosystems and biodiversity (Cheng, Chen et al, 2019;Kumne and Samanta, 2019;Sharma, Chaudhry et al, 2017;Srivastava, Singh et al, 2020). Hadagha, Farhi et al (2021) investigated the impact of urbanization on palm groves and desert oasis ecosystems while Phan, Trung et al (2021) reported a tenfold increase in urban areas across Vietnam which came at the expanse of the productive agricultural ecosystem. Some researchers have also used GIS as a tool to quantify the negative impact of urbanization on ecosystem services such as carbon sequestration (Han, Y., Kang et al, 2018), impact on land surface temperature (Hussain and Karuppannan, 2021) and habitat quality (He, Huang et al, 2017).…”