Soil map of Vo Nhai district are oriented establishments to offer appropriately land use for each land unit that using of advantages as well as troubleshoot limitations of each land unit, and propose the suitable solution in the soil reform.
Tag: classification
Crop diversity and classification of homegardens in Central Sulawesi, Indonesia
Homegardens are considered a sustainable production system in the tropics, which contributes to biodiversity conservation. The aim of this study was the description of crop diversity, structure and management of homegardens in Central Sulawesi and their classification. In 30 homegardens randomly selected from three villages adjacent to the Lore Lindu National Park, species diversity and abundance were assessed and the Shannon index was calculated. Overall 149 crop species were identified, mainly fruit, vegetable, spice, or medicinal plants. The number of vegetation layers differed depending on age and size of homegardens. Cluster analysis of crop species composition was used to classify different garden types. Not only the spectrum of species cultivated in the homegardens but also the occurrence of these garden types was different among the three villages. This finding was supported by Sørensen’s coefficient. Homegardens from one village, mainly inhabited by transmigrants, contrasted strongly with those from the other two. A markedly lower number of crop species was cultivated there, and species composition was clearly different. The number of crop species and species composition found in homegardens may be attributed to socio-economic conditions of garden keepers as well as to soil quality. Both productivity and sustainability can be enhanced, e.g., by improved soil fertility management such as applying available farm yard manure.
Scrutinizing Urbanization in Kathmandu Using Google Earth Engine Together with Proximity-Based Scenario Modelling
‘Urbanization’ refers to the expansion of built-up areas caused by several factors. This study focuses on the urbanization process in Kathmandu, the capital of Nepal. Supervised classification was conducted in Google Earth Engine by using Landsat data for years 2001, 2011 and 2021. The random forest classifier with 250 trees was used for classification to generate land-cover map. A land-cover map of 2021 was used as base map in the InVEST tool for scenario modelling. An accuracy assessment with 20% of sample points was conducted with different metrics, such as overall accuracy, kappa coefficient, producer accuracy, and consumer accuracy. The results show an increment of built-up areas by around 67 km2 over 20 years in a centrifugal pattern from the core district, converting agricultural and forest land. ‘Forest’ is still dominant land-use class, with an area of 177.97 km2. Agricultural land was highly converted to urban area. The overall accuracy of this classification process ranged 0.96–1.00 for different years. The scenario modelling further elaborated an amiability of drastic shift in land-use classes to ‘built-up’, especially forest and agriculture, by around 33 km2 and 66 km2, respectively. This study recommends the consideration of ecological approaches during the planning process.
Changes in mangrove coverage classification criteria could impact the conservation of mangroves in Mexico
Accurate estimates of habitat extent and rates of change are crucial inputs for the global, regional, and national assessments that guide policy-making and prioritize strategies. This can contribute to an understanding of ecosystems in the landscape for their use, management, and preservation. Mangroves are one of the types of ecosystems in which estimation discrepancies have been analyzed to determine the impacts of data quality on conservation and policy-making. We identify significant discrepancies in the extent of the last map of Mexican mangroves (i.e., 2020) produced by the Mexican Mangrove Monitoring System (MMMS). We performed a comparative assessment between the 2020 and 2015 maps by using geographical information systems to analyze the spatial extent across these years and estimate the accuracy of map changes with airborne data. We observed a spurious gain of 129,531 ha between 2015 and 2020, including 102,610 ha (79% of total changes) in the Sian Ka’an Biosphere Reserve and its surroundings. Furthermore, the mangrove definition changed, causing the MMMS to map other coastal wetlands with the presence of Rhizophora mangle scrubs dispersed in the landscape. The analysis of MMMS airborne data demonstrates that this significant increase is due to changes in mangrove mapping criteria and definitions. The definition and spatial delimitation of “mangrove” (i.e., mangrove community or stands forest) has implications relevant to the conservation policy of these coastal wetlands/coastal resources. MMMS discrepancies in mangrove extent could generate misleading perspectives on different sectors. A cartographic solution is to separate the other coastal wetland areas with the presence of R. mangle from all MMMS products and reclassify them as “other wetlands with the presence of R. mangle.” Robust ecosystem extent data is crucial for the design and implementation of efficient land use and conservation policies.
A dynamic portal for a community-driven, continuously updated classification of Fungi and fungus-like organisms: Outlineoffungi.org
The website http://outlineoffungi.org, is launched to provide a continuous up-to-date classification of the kingdom Fungi (including fossil fungi) and fungus-like taxa. This is based on recent publications and on the outline of fungi and fungus-like taxa published recently (Mycosphere 11, 1060-1456, doi 10.5943/mycosphere/11/1/8). The website is continuously updated according to latest classification schemes, and will present an important platform for researchers, industries, government officials and other users. Users can provide input about missing genera, new genera, and new data. They will also have the opportunity to express their opinions on classifications with notes published in the ‘Notes’ section of the webpage following review and editing by the curators and independent experts. The website will provide a system to stay abreast of the continuous changes in fungal classification and provide a general consensus on the systematics of fungi. © 2020, Guizhou Key Laboratory of Agricultural Biotechnology.