A comparative study of Frequency Ratio(FR)and Analytic Hierarchy Process(AHP)models are performed for forest fire risk(FFR)mapping in Melghat Tiger Reserve forest,central India.Identification of FFR depends on various...A comparative study of Frequency Ratio(FR)and Analytic Hierarchy Process(AHP)models are performed for forest fire risk(FFR)mapping in Melghat Tiger Reserve forest,central India.Identification of FFR depends on various hydrometeorological parameters altitude,slope,aspect,topographic position index,normalized differential vegetation index,rainfall,air temperature,land surface temperature,wind speed,distance to settlements,and distance by road are integrated using a GIS platform.The results from FR and AHP show similar trends.The FR model was significantly higher accurate(overall accuracy of 81.3%,kappa statistic 0.78)than the AHP model(overall accuracy 79.3%,kappa statistic 0.75).The FR model total forest fire risk areas were classified into five classes:very low(7.1%),low(22.2%),moderate(32.3%),high(26.9%),and very high(11.5%).The AHP fire risk classes were very low(6.7%),low(21.7%),moderate(34.0%),high(26.7%),and very high(10.9%).Sensitivity analyses were performed for AHP and FR models.The results of the two different models are compared and justified concerning the forest fire sample points(Forest Survey of India)and burn images(2010-2016).These results help in designing more effective fire management plans to improve the allocation of resources across a landscape framework.展开更多
Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS...Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results.展开更多
文摘A comparative study of Frequency Ratio(FR)and Analytic Hierarchy Process(AHP)models are performed for forest fire risk(FFR)mapping in Melghat Tiger Reserve forest,central India.Identification of FFR depends on various hydrometeorological parameters altitude,slope,aspect,topographic position index,normalized differential vegetation index,rainfall,air temperature,land surface temperature,wind speed,distance to settlements,and distance by road are integrated using a GIS platform.The results from FR and AHP show similar trends.The FR model was significantly higher accurate(overall accuracy of 81.3%,kappa statistic 0.78)than the AHP model(overall accuracy 79.3%,kappa statistic 0.75).The FR model total forest fire risk areas were classified into five classes:very low(7.1%),low(22.2%),moderate(32.3%),high(26.9%),and very high(11.5%).The AHP fire risk classes were very low(6.7%),low(21.7%),moderate(34.0%),high(26.7%),and very high(10.9%).Sensitivity analyses were performed for AHP and FR models.The results of the two different models are compared and justified concerning the forest fire sample points(Forest Survey of India)and burn images(2010-2016).These results help in designing more effective fire management plans to improve the allocation of resources across a landscape framework.
文摘Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results.
