Land degradation is a major challenge in Nepal. A lot of degraded land is available within the C... more Land degradation is a major challenge in Nepal. A lot of degraded land is available within the Community Forests in the Mid-hills which are being aimed to be utilized for ecological restoration as well as supporting livelihoods of the local people. In this context, the study was conducted in the Chautaradanda Community Forest (27°44’05’’ N and 85o04’60’’ E) of Thakre Village Development Committee of Dhading District in the lower Mid-hills of Central Nepal to test the survival capacity and growth performance of different tree species (native, naturalized as well as exotic) that can be used for the rehabilitation of degraded sites. Firstly, Stylo (Stylosanthes spp.), a leguminous grass, was introduced on a degraded site for enriching nutrients in June 2008. Secondly, six different native, naturalized as well as exotic tree species (Sapindus mukorossi, Prunus cerasoides, Choerospondias axillaris, Melia azedarach, Pinus patula and Robinia pseudoacacia) were planted in a randomized comp...
While deforestation has traditionally been the focus for forest canopy disturbance detection, for... more While deforestation has traditionally been the focus for forest canopy disturbance detection, forest degradation must not be overlooked. Both deforestation and forest degradation influence carbon loss and greenhouse gas emissions and thus must be included in activity data reporting estimates, such as for the Reduced Emissions from Deforestation and Degradation (REDD+) program. Here, we report on efforts to develop forest degradation mapping capacity in Nepal based on a pilot project in the country’s Terai region, an ecologically complex physiographic area. To strengthen Nepal’s estimates of deforestation and forest degradation, we applied the Continuous Degradation Detection (CODED) algorithm, which uses a time series of the Normalized Degradation Fraction Index (NDFI) to monitor forest canopy disturbances. CODED can detect low-grade degradation events and provides an easy-to-use graphical user interface in Google Earth Engine (GEE). Using an iterative process, we were able to creat...
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scannin... more This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scanning (ALS) and RapidEye image-derived parameters with field-measured biomass using Random forests (RF) to predict the tropical forest biomass (FB). The multi-sensor parameters which include combined spectral, textural and ALS derived 119 variables provided a better result, R2 = 0.95 and relative RMSE (relRMSE) = 17.25%, as compared to any single sensor parameter for the FB estimation. The top 20 variables were used to compute FB and its distribution map with the R2, RMSE and relRMSE values of 0.93, 35.46 Mg ha-1 and 17.40% respectively. Furthermore, its validation was checked with the in-situ biomass to obtain satisfactory accuracy (R2 = 0.72, RMSE = 47.71 Mg ha-1 and relRMSE = 23.41%). The result showed that the integration of multi-sensor data using RF regression algorithm proves to be a reliable algorithm for accurate FB estimation.
1 Forest Research and Training Centre, Pokhara, Gandaki Province, Nepal. *Email: raj_malla@yahoo.... more 1 Forest Research and Training Centre, Pokhara, Gandaki Province, Nepal. *Email: raj_malla@yahoo.com 2 Forest Research and Training Centre, Kathmandu, Nepal 3 International Centre for Integrated Mountain Development, Lalitpur, Nepal Large-scale plantations of pine species were done in the bare hills of the Middle Mountain region of Nepal during the early 1980s. There is a growing concern on the sustainability of the planted pine forests in the country due to the presence of invasive alien plant species (IAPS). Invasive alien plant species are considered as one of the drivers of forest degradation and deforestation. Ageratina adenophora is one of the problematic IAPS found in the planted pine forests throughout the country. In this study, we employed different treatments to control the invasion of A. adenophora in the planted pine (Pinus patula) forest. The research design included four different treatments, viz., (i) control, (ii) stem felling, (iii) floor clearance, and (iv) stem f...
Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region, 2021
The land cover across the HKH region is changing at an accelerated rate due to the rapid economic... more The land cover across the HKH region is changing at an accelerated rate due to the rapid economic growth and population pressures that are impacting the long-term sustainability of ecosystems.
Not available.Banko JanakariA Journal of Forestry Information for Nepal Special Issue No. 4, 2018... more Not available.Banko JanakariA Journal of Forestry Information for Nepal Special Issue No. 4, 2018, Page:150-153
The study, carried out at Laljhadi corridor in Kanchanpur district of Nepal, aimed at assessing f... more The study, carried out at Laljhadi corridor in Kanchanpur district of Nepal, aimed at assessing forest cover change and fragmentation using multi-temporal Landsat data. Post classifi cation change detection was applied on temporal forest cover class datasets obtained by supervised classifi cation technique with maximum likelihood algorithm. The overall change analysis indicated a decreasing trend in forest cover. Statistics on selected landscape metrics were generated to quantify the change in spatial structure resulting from fragmentation. The analysis of the landscape metrics depicted increase in fragmentation over the analysis time period along with progression of deforestation.DOI: http://dx.doi.org/10.3126/banko.v21i2.9142Banko Janakari Vol. 21, No. 2, 2011 Page: 40-44 Uploaded date: November 11, 2013
This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scannin... more This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scanning (ALS) and RapidEye image-derived parameters with field-measured biomass using Random forests (RF) to predict the tropical forest biomass (FB). The multi-sensor parameters which include combined spectral, textural and ALS derived 119 variables provided a better result, R2 = 0.95 and relative RMSE (relRMSE) = 17.25%, as compared to any single sensor parameter for the FB estimation. The top 20 variables were used to compute FB and its distribution map with the R2, RMSE and relRMSE values of 0.93, 35.46 Mg ha-1 and 17.40% respectively. Furthermore, its validation was checked with the in-situ biomass to obtain satisfactory accuracy (R2 = 0.72, RMSE = 47.71 Mg ha-1 and relRMSE = 23.41%). The result showed that the integration of multi-sensor data using RF regression algorithm proves to be a reliable algorithm for accurate FB estimation.
Land degradation is a major challenge in Nepal. A lot of degraded land is available within the C... more Land degradation is a major challenge in Nepal. A lot of degraded land is available within the Community Forests in the Mid-hills which are being aimed to be utilized for ecological restoration as well as supporting livelihoods of the local people. In this context, the study was conducted in the Chautaradanda Community Forest (27°44’05’’ N and 85o04’60’’ E) of Thakre Village Development Committee of Dhading District in the lower Mid-hills of Central Nepal to test the survival capacity and growth performance of different tree species (native, naturalized as well as exotic) that can be used for the rehabilitation of degraded sites. Firstly, Stylo (Stylosanthes spp.), a leguminous grass, was introduced on a degraded site for enriching nutrients in June 2008. Secondly, six different native, naturalized as well as exotic tree species (Sapindus mukorossi, Prunus cerasoides, Choerospondias axillaris, Melia azedarach, Pinus patula and Robinia pseudoacacia) were planted in a randomized comp...
While deforestation has traditionally been the focus for forest canopy disturbance detection, for... more While deforestation has traditionally been the focus for forest canopy disturbance detection, forest degradation must not be overlooked. Both deforestation and forest degradation influence carbon loss and greenhouse gas emissions and thus must be included in activity data reporting estimates, such as for the Reduced Emissions from Deforestation and Degradation (REDD+) program. Here, we report on efforts to develop forest degradation mapping capacity in Nepal based on a pilot project in the country’s Terai region, an ecologically complex physiographic area. To strengthen Nepal’s estimates of deforestation and forest degradation, we applied the Continuous Degradation Detection (CODED) algorithm, which uses a time series of the Normalized Degradation Fraction Index (NDFI) to monitor forest canopy disturbances. CODED can detect low-grade degradation events and provides an easy-to-use graphical user interface in Google Earth Engine (GEE). Using an iterative process, we were able to creat...
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scannin... more This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scanning (ALS) and RapidEye image-derived parameters with field-measured biomass using Random forests (RF) to predict the tropical forest biomass (FB). The multi-sensor parameters which include combined spectral, textural and ALS derived 119 variables provided a better result, R2 = 0.95 and relative RMSE (relRMSE) = 17.25%, as compared to any single sensor parameter for the FB estimation. The top 20 variables were used to compute FB and its distribution map with the R2, RMSE and relRMSE values of 0.93, 35.46 Mg ha-1 and 17.40% respectively. Furthermore, its validation was checked with the in-situ biomass to obtain satisfactory accuracy (R2 = 0.72, RMSE = 47.71 Mg ha-1 and relRMSE = 23.41%). The result showed that the integration of multi-sensor data using RF regression algorithm proves to be a reliable algorithm for accurate FB estimation.
1 Forest Research and Training Centre, Pokhara, Gandaki Province, Nepal. *Email: raj_malla@yahoo.... more 1 Forest Research and Training Centre, Pokhara, Gandaki Province, Nepal. *Email: raj_malla@yahoo.com 2 Forest Research and Training Centre, Kathmandu, Nepal 3 International Centre for Integrated Mountain Development, Lalitpur, Nepal Large-scale plantations of pine species were done in the bare hills of the Middle Mountain region of Nepal during the early 1980s. There is a growing concern on the sustainability of the planted pine forests in the country due to the presence of invasive alien plant species (IAPS). Invasive alien plant species are considered as one of the drivers of forest degradation and deforestation. Ageratina adenophora is one of the problematic IAPS found in the planted pine forests throughout the country. In this study, we employed different treatments to control the invasion of A. adenophora in the planted pine (Pinus patula) forest. The research design included four different treatments, viz., (i) control, (ii) stem felling, (iii) floor clearance, and (iv) stem f...
Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region, 2021
The land cover across the HKH region is changing at an accelerated rate due to the rapid economic... more The land cover across the HKH region is changing at an accelerated rate due to the rapid economic growth and population pressures that are impacting the long-term sustainability of ecosystems.
Not available.Banko JanakariA Journal of Forestry Information for Nepal Special Issue No. 4, 2018... more Not available.Banko JanakariA Journal of Forestry Information for Nepal Special Issue No. 4, 2018, Page:150-153
The study, carried out at Laljhadi corridor in Kanchanpur district of Nepal, aimed at assessing f... more The study, carried out at Laljhadi corridor in Kanchanpur district of Nepal, aimed at assessing forest cover change and fragmentation using multi-temporal Landsat data. Post classifi cation change detection was applied on temporal forest cover class datasets obtained by supervised classifi cation technique with maximum likelihood algorithm. The overall change analysis indicated a decreasing trend in forest cover. Statistics on selected landscape metrics were generated to quantify the change in spatial structure resulting from fragmentation. The analysis of the landscape metrics depicted increase in fragmentation over the analysis time period along with progression of deforestation.DOI: http://dx.doi.org/10.3126/banko.v21i2.9142Banko Janakari Vol. 21, No. 2, 2011 Page: 40-44 Uploaded date: November 11, 2013
This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scannin... more This study aimed to integrate and optimise multi-sensor data consisting of airborne laser scanning (ALS) and RapidEye image-derived parameters with field-measured biomass using Random forests (RF) to predict the tropical forest biomass (FB). The multi-sensor parameters which include combined spectral, textural and ALS derived 119 variables provided a better result, R2 = 0.95 and relative RMSE (relRMSE) = 17.25%, as compared to any single sensor parameter for the FB estimation. The top 20 variables were used to compute FB and its distribution map with the R2, RMSE and relRMSE values of 0.93, 35.46 Mg ha-1 and 17.40% respectively. Furthermore, its validation was checked with the in-situ biomass to obtain satisfactory accuracy (R2 = 0.72, RMSE = 47.71 Mg ha-1 and relRMSE = 23.41%). The result showed that the integration of multi-sensor data using RF regression algorithm proves to be a reliable algorithm for accurate FB estimation.
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Papers by Raja Ram Aryal