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In het boek wordt een nieuwe benadering in de bescherming van kinderen gepresenteerd. Hulpverleners in de jeugdzorg en kinderbescherming kunnen hiermee potentieel risicovolle situaties beoordelen en vinden hierin praktische hands-on strategieën voor het opbouwen van een samenwerkingrelatie met de ouders. Uit de praktijk blijkt dat dit op de lange termijn kindermishandeling en uithuisplaatsing kan voorkomen. Er zijn weinig beroepsgroepen waarbij emotie zo'n grote rol speelt als bij hulpverleners in de jeugdzorg en de kinderbescherming. Logisch; het gaat immers om kwetsbare kinderen die bedreigd worden in hun ontwikkeling, of erger. Daarom heeft ook iedereen een oordeel over het werk van deze hulpverleners. Zij liggen vaak onder vuur: omdat ze wél ingrijpen of omdat ze níet ingrijpen. Het gevolg is dat hulpverleners steeds vaker risicomijdend gedrag vertonen - het beruchte Savanna-effect - dat tot meer uithuisplaatsingen van kinderen leidt. De auteurs bieden een beter alternatief: ze hebben in de praktijk vastgesteld dat samenwerking met het gezin de beste resultaten oplevert. In 9 hoofdstukken worden zowel het theoretische kader als de praktijkelementen van Signs of Safety uitgebreid behandeld. Dit praktijkboek laat zien hoe je deze benadering steeds kunt toepassen: van intake via onderzoek en beoordeling tot afsluiting van het dossier

Social policy and particular groups --- jeugdbescherming --- jeugdhulpverlening --- methoden van het sociaal werk --- Jeugdzorg --- Jeugdbescherming --- Gezinsproblemen --- Gezinsgericht werken --- Hulpverlening --- Gezin --- Teamwerk --- Ouders --- 323.4 --- gezin --- good practice --- jeugdzorg --- kindermishandeling --- kwetsbare jongeren --- 364.044 --- Kinderbescherming --- Kindermishandeling --- Methodiek --- Jeugdbescherming. --- Jeugdzorg. --- gezin. --- good practice. --- jeugdzorg. --- kindermishandeling. --- kwetsbare jongeren. --- kinderen

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The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.

Research & information: general --- Environmental economics --- forest structure change --- EBLUP --- small area estimation --- multitemporal LiDAR and stand-level estimates --- forest cover --- Sentinel-1 --- Sentinel-2 --- data fusion --- machine-learning --- Germany --- South Africa --- temperate forest --- savanna --- classification --- Sentinel 2 --- land use land cover --- improved k-NN --- logistic regression --- random forest --- support vector machine --- statistical estimator --- IPCC good practice guidelines --- activity data --- emissions factor --- removals factor --- Picea crassifolia Kom --- compatible equation --- nonlinear seemingly unrelated regression --- error-in-variable modeling --- leave-one-out cross-validation --- digital surface model --- digital terrain model --- canopy height model --- constrained neighbor interpolation --- ordinary neighbor interpolation --- point cloud density --- stereo imagery --- remotely sensed LAI --- field measured LAI --- validation --- magnitude --- uncertainty --- temporal dynamics --- state space models --- forest disturbance mapping --- near real-time monitoring --- CUSUM --- NRT monitoring --- deforestation --- degradation --- tropical forest --- tropical peat --- forest type --- deep learning --- FCN8s --- CRFasRNN --- GF2 --- dual-FCN8s --- random forests --- error propagation --- bootstrapping --- Landsat --- LiDAR --- La Rioja --- forest area change --- data assessment --- uncertainty evaluation --- inconsistency --- forest monitoring --- drought --- time series satellite data --- Bowen ratio --- carbon flux --- boreal forest --- windstorm damage --- synthetic aperture radar --- C-band --- genetic algorithm --- multinomial logistic regression --- forest structure change --- EBLUP --- small area estimation --- multitemporal LiDAR and stand-level estimates --- forest cover --- Sentinel-1 --- Sentinel-2 --- data fusion --- machine-learning --- Germany --- South Africa --- temperate forest --- savanna --- classification --- Sentinel 2 --- land use land cover --- improved k-NN --- logistic regression --- random forest --- support vector machine --- statistical estimator --- IPCC good practice guidelines --- activity data --- emissions factor --- removals factor --- Picea crassifolia Kom --- compatible equation --- nonlinear seemingly unrelated regression --- error-in-variable modeling --- leave-one-out cross-validation --- digital surface model --- digital terrain model --- canopy height model --- constrained neighbor interpolation --- ordinary neighbor interpolation --- point cloud density --- stereo imagery --- remotely sensed LAI --- field measured LAI --- validation --- magnitude --- uncertainty --- temporal dynamics --- state space models --- forest disturbance mapping --- near real-time monitoring --- CUSUM --- NRT monitoring --- deforestation --- degradation --- tropical forest --- tropical peat --- forest type --- deep learning --- FCN8s --- CRFasRNN --- GF2 --- dual-FCN8s --- random forests --- error propagation --- bootstrapping --- Landsat --- LiDAR --- La Rioja --- forest area change --- data assessment --- uncertainty evaluation --- inconsistency --- forest monitoring --- drought --- time series satellite data --- Bowen ratio --- carbon flux --- boreal forest --- windstorm damage --- synthetic aperture radar --- C-band --- genetic algorithm --- multinomial logistic regression

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.

Research & information: general --- Environmental economics --- forest structure change --- EBLUP --- small area estimation --- multitemporal LiDAR and stand-level estimates --- forest cover --- Sentinel-1 --- Sentinel-2 --- data fusion --- machine-learning --- Germany --- South Africa --- temperate forest --- savanna --- classification --- Sentinel 2 --- land use land cover --- improved k-NN --- logistic regression --- random forest --- support vector machine --- statistical estimator --- IPCC good practice guidelines --- activity data --- emissions factor --- removals factor --- Picea crassifolia Kom --- compatible equation --- nonlinear seemingly unrelated regression --- error-in-variable modeling --- leave-one-out cross-validation --- digital surface model --- digital terrain model --- canopy height model --- constrained neighbor interpolation --- ordinary neighbor interpolation --- point cloud density --- stereo imagery --- remotely sensed LAI --- field measured LAI --- validation --- magnitude --- uncertainty --- temporal dynamics --- state space models --- forest disturbance mapping --- near real-time monitoring --- CUSUM --- NRT monitoring --- deforestation --- degradation --- tropical forest --- tropical peat --- forest type --- deep learning --- FCN8s --- CRFasRNN --- GF2 --- dual-FCN8s --- random forests --- error propagation --- bootstrapping --- Landsat --- LiDAR --- La Rioja --- forest area change --- data assessment --- uncertainty evaluation --- inconsistency --- forest monitoring --- drought --- time series satellite data --- Bowen ratio --- carbon flux --- boreal forest --- windstorm damage --- synthetic aperture radar --- C-band --- genetic algorithm --- multinomial logistic regression --- n/a