Changing Traditional Land use Patterns in the Great Himalayas: A Case Study of Lahaul Valley

1996 ◽  
Vol 25 (2) ◽  
pp. 195-211 ◽  
Author(s):  
G. S. Singh ◽  
S. C. Ram ◽  
J. C. Kuniyal
Keyword(s):  
Land Use ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Traditional Land Use

Sustainable land-use patterns for arid lands: A case study in the northern slope areas of the Tianshan Mountains

2010 ◽  
Vol 20 (4) ◽  
pp. 510-524 ◽  
Author(s):  
Geping Luo ◽  
Yixing Feng ◽  
Baiping Zhang ◽  
Weiming Cheng
Keyword(s):  
Land Use ◽  
Tianshan Mountains ◽  
Arid Lands ◽  
Sustainable Land Use ◽  
Northern Slope ◽  
Land Use Patterns ◽  
Use Patterns

scholarly journals A comparison between soil loss evaluation index and the C-factor of RUSLE: a case study in the Loess Plateau of China

2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Drainage Network ◽  
Land Use Patterns ◽  
Low Area ◽  
Use Patterns ◽  
High Area ◽  
Land Use Types

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.

Distribution of heavy metals in topsoils affected by land use patterns at a small watershed scale: a case study in the Bantou Reservoir watershed in Xiamen, China

2015 ◽  
Vol 35 (16) ◽  
Author(s):  
李清良 LI Qingliang ◽  
吴倩 WU Qian ◽  
高进波 GAO Jinbo ◽  
马军 MA Jun ◽  
徐秋芳 XU Qiufang ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Land Use ◽  
Watershed Scale ◽  
Small Watershed ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Reservoir Watershed

Changing land use patterns in the Lower Rio Grande Valley: A case study of Cameron and Hidalgo counties

1988 ◽  
Vol 3 (2) ◽  
pp. 97-105 ◽  
Author(s):  
Charles J. Ellard ◽  
J. Michael Patrick
Keyword(s):  
Land Use ◽  
Rio Grande Valley ◽  
Rio Grande ◽  
Land Use Patterns ◽  
Lower Rio Grande Valley ◽  
Use Patterns ◽  
Lower Rio Grande

Land use patterns, temperature distribution, and potential heat stress risk – The case study Berlin, Germany

2014 ◽  
Vol 48 ◽  
pp. 86-98 ◽  
Author(s):  
Pierre-Adrien Dugord ◽  
Steffen Lauf ◽  
Christian Schuster ◽  
Birgit Kleinschmit
Keyword(s):  
Land Use ◽  
Heat Stress ◽  
Temperature Distribution ◽  
Land Use Patterns ◽  
Use Patterns

scholarly journals The Hidden Characteristics of Land-Use Mix Indices: An Overview and Validity Analysis Based on the Land Use in Melbourne, Australia

2021 ◽  
Vol 13 (4) ◽  
pp. 1898
Author(s):  
Jiacheng Jiao ◽  
John Rollo ◽  
Baibai Fu
Keyword(s):  
Land Use ◽  
Screening Method ◽  
Comparative Trial ◽  
Dissimilarity Index ◽  
City Center ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Land Use Types ◽  
Land Use Mix

The land-use mix index is a way to quantify the mixture of land-use patterns. Due to practical limitations, few studies have highlighted the validity of land-use mix indices. This paper aims to explore the potential characteristics of land-use mix indices using a three-step screening method. The data precision of indices was concluded after the first-step screening. A total of 10 virtual blocks and 217 blocks in Melbourne city center served as a case study and reflected the various land-use structures. The randomized controlled comparative trial was incorporated into the second- and third-screening to indicate the applicable condition and validity. The results illustrate that the value Herfindahl–Hirschman index related to the diversity of land-use types. The results also confirmed that Dissimilarity index-I was significantly associated with the balance status of the land-use mix. Entropy index reflects the evenness but did not correlate to the diversity or balance of the land-use mix. In addition, the study also provides a set of general recommendations for the application conditions of land-use mix indices.

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